## Introduction

Water is an essential nutrient for all living beings. It is part of many body fluids such as blood and lymph. Water provides shape to the body cells. Biochemical and physiological reactions depend on a liquid medium and water functions as a solvent for transportation of nutrients and the excretion of waste products such as uric acid. The regulation of body temperature is an additional important role of water (Schmidt-Nielsen, 1997). Despite of the vital importance of water, only limited studies are available on water intake, water metabolism and water requirements of South American Camelids. The present paper reviews the current knowledge.

## Drinking behavior

South American camelids (SAC) suck in water with the mouth slightly opened. Interestingly, SAC are apparently unable to lick (San Martin & Bryant, 1989). The upper lip is divided by a labial cleft and each side of the lip can be moved independently, while the lower lip is less mobile. The upper lips are used as a tactile sense organ in food discrimination (Fowler, 2010). Thus, drinking from open water surfaces, such as ponds or running streams is most natural to SAC. Camelids have shown to use different types of automatic waterers, but are reluctant to use push valves water bowls where it is necessary to press a lever to have water dispensed. Float valve water bowls with an automatic float valve to maintain the water at a constant level are most suitable. SAC appear not to break through ice to obtain water and in cold climates heated waterers must be offered (Fowler, 2010).

In an ongoing experiment (unpublished data), we recorded drinking behavior of adult female llamas under temperate stable conditions. Water was offered in buckets with 10 l capacity ad libitum. The analyses of the 24 h video recordings revealed a large individual variation of drinking sessions/ day. Frequently, animals had only one drinking session/ day. Water intake occurred almost exclusively during the light hours of the morning and late afternoon while it was very rarely observed during the dark hours. Interestingly, llamas frequently raised the head and interrupted water intake for 10 to 30 sec, swallowed and masticated while looking around and then continued drinking. This behavioural pattern might indicate a vigilance strategy to prevent predation (Cappa et al., 2014).

## Total body water

Total body water in crias was found to be in the range of 70-72 % (Marcilese et al., 1994; Riek et al. 2007). Similar values were obtained by isotope labeling for kids (Makinde, 1993) and lambs (Dove, 1988). Dilution studies on adult llamas revealed lower values ranging between 57 to 70 % of the body mass (Rübsamen & Engelhardt, 1975; Riek et al., 2017). However, it is known that body water content decreases with age primarily due to fat accumulation (Oftedal and Iverson, 1989).
## Water intake and water turnover

Water requirements can be covered by intake of drinking water, water content of feed and water produced by metabolic processes. Metabolic water is formed during the metabolic oxidation of hydrogen-containing organic nutrients. According to Van Es (1969), fat and protein produce 1.07 and 0.42 g of water/g material oxidized, respectively. Water is lost by four main avenues: evaporation (via skin and lungs), urine, feces and lactation.

Under temperate conditions, water intake of llama crias was found to be re-
stricted to dams' milk during the first 10 weeks, whereafter they started to con-
sume additional drinking water (Riek et al., 2007). In the study of Rübsamen and
Engelhardt (1975), adult non pregnant llamas were kept in pens under temperate
climate and fed a hay diet. The average amount of drinking water consumed was
42.5 ml /BW<sup>0.82</sup> per 24 h, being equivalent for example of 2.2 l for a 120 kg llama.
At peak lactation, female llama dams drank approximately 9.8 l of water per day,
whereas in late lactation they only consumed about 5.5 l (Riek et al., 2007) under
temperate stable conditions and a hay based diet.

Body water turnover is an important parameter for characterization of water
metabolism and is defined as the replacement of body water that is lost in a de-
fined period of time. Species differ in their rates of water turnover, and in general
animals adapted to dry environments display lower rates of turnover than those
from temperate areas (King, 1979). Body water turnover is closely related to body
weight (Rübsamen & Engelhardt, 1975). But due to the complex role of water in
thermoregulation, energy metabolism and other processes, many factors influence
body water turnover.

For estimation of water turnover in camelids, isotope labeling techniques have
been applied (e.g., Rübsamen & Engelhardt, 1975; Riek et al., 2007, 2017). In an
indoor experiment with crias aged between 17 and 128 days, the fractional water
turnover decreased with increasing age. The highest fractional turnover at 17 days
of age corresponded to a biological half-life of 4.3 days. With lower fractional
turnover the biological half-life increased and accordingly the biological half-life
corresponded to 7.9 and 12.6 days at later ages of 66 and 128 days, respectively. In
contrast to growing llamas, Marcilese et al. (1994) showed that a lactating llama
takes approximately 3.3 days to turn over half of the body water. This difference
between growing and lactating llamas may be explained by the higher water de-
mand due to milk production. In the study of Rübsamen and Engelhardt (1975),
water turnover rates were 62.1 ±8.8 ml/kg BW<sup>0.82</sup> per 24 h in adult non lactating
llamas and were similar to those of goats (59.0 ±10.9 ml/kg BW<sup>0.82</sup>).

For female llamas kept in year round outdoor housing in Germany, total water
intake (from drinking water, preformed water ingested in food and metabolic wa-
ter) was found to fluctuate considerably. Animals ingested more than double the
amount of water (9.17 l/d) in summer compared to the winter season (4.22 l/d)
(Riek et al., 2017). These differences can be attributed to an increased ingestion of
drinking water during summer when animals had higher physical activities and the
environmental temperature increased above 25 °C. In addition, animals consumed more pasture in summer with a higher percentage of water compared to hay, which was the main food source in winter. Similarly, the water turnover rates in grazing llamas were found to be twice that recorded indoors (Rübsamen & Engelhardt, 1975).

As outlined before, water plays an important role in thermoregulation. SAC possess epitrichial sweet glands, which are especially numerous on the sparsely covered areas of the ventrum (Fowler, 2010). There was no detectable evaporative water loss in llamas kept at 20-25 °C. However, vapor loss increased to 100-240 g/m²/body surface/h when the ambient temperature was gradually raised to 40 °C (Allen & Bligh, 1969). Thus, substantial amounts of water will be dissipated with increasing ambient temperature, resulting in increased water ingestion and water turnover. In addition, the increased daily energy expenditure of grazing animals during summer months may also result in a greater production of metabolic water (Riek et al., 2017).

## Water deprivation

In the light of the vital importance of water for body functions, water deprivation poses a serious risk and animals have developed different mechanisms to prevent dehydration. Physiological strategies comprise decrease of renal urine flow, concentration of urine, and extraction of moisture from the feces. Among the channels of water loss from the body, less water tends to be lost through urine than through the feces, however, the scope for modulation of urine flow and concentration appears to be greater. In their normal habitat of the high Andes, SACs are confronted with conditions of poor vegetation, extreme temperatures and often limited water availability. For survival under these conditions, highly efficient adaptation constitutes a crucial prerequisite. The closely related Old World camels are legendary in their extremely efficient water metabolism and the question arises whether SAC possess similar physiological mechanisms to withstand dehydration.

In a comparative study, both llamas and goats reduced renal water losses when water intake was restricted (Rübsamen & Engelhardt, 1975). However, llamas were able to reduce their renal water loss to a greater degree than goats (17 vs. 29 % of total water loss). There were no significant differences between llamas and goats in their ability to concentrate the urine. Interestingly, under conditions of water restriction llamas were able to ingest more food than goats, thereby increasing their metabolic water gain. This may be an advantage when confronted with water deprivation. Guanacos demonstrated that they can withstand dehydration, but to a lesser degree and based on different mechanisms than the Old World camel (Mario & Morrison, 1963). When deprived of water for four days, while feed was offered ad libitum, a male guanaco lost 23.4 % of its body weight. However, body temperature was not elevated. The packed cell volume (PCV) increased from 30.6 to
43.6 %, indicating a reduction in blood plasma of about 40 %. In contrast, a camel only showed a 2.3 % reduction in blood plasma during similar dehydration underlining its better adaptation to dehydration (Mario & Morrison, 1963).

The high dehydration resistance in Old World camels might be explained by features of their erythrocytes which are able to avoid osmotic hazards by swelling to 240 % of their initial volume without rupturing. In other species, erythrocytes only swell to about 150 % (Fowler, 2010). It is assumed that South American camelids share some of these characteristics with Old World camels (Fowler, 2010). After severe dehydration, camels are able to consume high amounts of water at one drinking session to replace all the water lost (Engelhardt et al., 2006). Similarly, but to a lesser degree, a dehydrated guanaco (23.4 %) drank 9 l of water within 8 minutes, thus restoring 66 % of its deficit (Mario & Morrison, 1963). Such an amount of water would result in severe osmotic problems in other animals. The anatomy of the forestomach of camelids differs considerably from that of ruminants (Fowler, 2010). This fact may play an important role in slow absorption of the drinking water, allowing osmotic equilibrium to be established.

## Saline water

Due to global climatic changes, salinization of ground water and soil is an increasing worldwide phenomenon (IPCC, 2014; WWAP, 2015). In particular, Andean countries, such as Peru, are confronted with the challenge of soil degradation and salinization (Oldemann et al., 1991). Although sodium chloride salt (NaCl) is essential for regulating body water content, muscle and nerve functions and nutrient absorption (Suttle, 2010), excessive salt intake may affect feed and water consumption of animals or even cause severe health problems. Sheep have been shown to tolerate high salt concentrations between 5 % and 20 % in their diet (Digby et al., 2011). However, there is a different sensitivity to ingestion of salt either from food or drinking water (Masters et al., 2005). Drinking water with salt concentrations between 1.0 % and 1.3 % was tolerated by sheep (Peirce, 1968). However, ingestion of saline water with a salt concentration of 2 % or more led to severe reduction in food intake, and possibly death in sheep, goats and cattle (Peirce, 1957; Weeth and Haverland, 1961; Wilson and Dudzinski, 1973; Hamilton and Webster, 1987; McGregor, 2004).

It is obvious that Na+ intake needs to be regulated by the animal because it is the major extracellular element influencing osmolarity of body fluids. A key physiological response to high salt ingestion is to increase water intake as shown e.g., for sheep (Peirce, 1957; Wilson and Dudzinski, 1973) to regain an isotonic state. However, this adaptive reaction is limited when only saline drinking water is available, as it increases salt load in the body fluids. In such cases, the animals have limited other adaptive responses to draw upon, beyond the excretion of increased amounts of salt via urine and a reduction of feed and water intake.
Camels demonstrated a remarkable high salt tolerance and tolerated more than 1.5 % salt in water (Abou El-Nasr et al., 1988), compared to sheep and goats (Abou Hussien et al., 1994; Assad and El-Sherif, 2002). Interestingly, the salt load controlling mechanisms differ between species (Abou Hussien et al., 1994). While sheep and goats reduce high salt loads by increased water intake, increased glomerular filtration rate and renal salt excretion through urine (Potter, 1968; Dunson, 1974), camels protect themselves from salt stress by reducing water consumption per unit of body size (Abou Hussien et al., 1994; Assad and El-Sherif, 2002). In a comparative study, camels, goats and sheep increased their total water intake by 130 ml/kg<sup>0.82</sup>, 376 ml/kg<sup>0.82</sup> and 500 ml/kg<sup>0.82</sup>, respectively, when exposed to water salinity of up to 1.7 %.

In this context, the Old World camel has evolved specific adaptive capacities. The kidneys are able to concentrate urine so that it becomes very thick. Salt content of camel urine may increase to twice the salt concentration of sea water (Fowler, 2010). This mechanism may partly explain the high salt tolerance in drinking water found in camels. However, SAC seem not to possess the same capacity, as llamas were not superior to goats in their ability to concentrate the urine (Rübsamen & Engelhardt, 1975).

There are anecdotal reports on guanacos, the wild ancestor of the llama, drinking saline water (Darwin, 1844). However, no studies are available on taste responses to sodium chloride in drinking water in llamas. For the study of taste discrimination in animals, different methods have been applied including electrophysiological methods (Bernard, 1964), recording of gustatory nerve impulses (Bell & Kitchell, 1966) or preference tests (Goatcher and Church 1970a,b). The principle approach in preference or choice tests is to provide a simultaneous choice of selections and then measure the animals' responses to each (Raffa et al., 2002). Goats have demonstrated their capacity to select a balanced diet according to their nutrient requirements (Fedele et al., 2002) and to avoid excessive intake of saline water (Runa et al., 2018) in a free choice experiment. The choice may be associated with sensory components (e.g., smell, taste) and post-ingestive effects. Interestingly, herbivores can recognize sodium directly by taste and show a specific appetite when it is in short supply (Denton, 1982).

In our ongoing study (unpublished), adult llamas were exposed to a two choice tests to evaluate their taste responses towards saline water. Drinking water with ascending salt concentrations (form 0.25 to 1.5 % NaCl) was offered in one container and unsalted tap water in the other. The position of the saline water was changed at random to counterbalance position effects. The reactions of the llamas suggest a rejection of saline water between 1.25 and 1.5 % concentration. Similar preferences for low salt concentrations of 0.85 % and 1.25 % were found for goats and sheep by Goatcher and Church (1970b). However, two choice preference tests only evaluate the short term taste discrimination and sensitivity thresholds. To determine the long-term salt tolerance in drinking water of llamas, further studies are required.
## Conclusion

SAC have evolved efficient mechanisms using water indicating an evolutionary adaptation to limited water supply of the high Andes. These strategies to withstand water scarcity appear to be partly superior to those of goats. Interestingly, SAC and Old World camels share some physiological features with regard to their water efficiency, but they are less developed in SAC. As water is an essential nutrient, SACs should have ad libitum access to clean drinking water. Animals adjust their intake according to their requirements. In particular during lactation, unrestricted water supply is essential. In the case of water scarcity, dehydration and hyperthermia may result (Fowler, 2010).

**Acknowledgments.** This research was supported by a scholarship of the German Academic Exchange Service (DAAD) to R. A. Runa.

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<figure><img src="image_83.png" /></figure>
Meat and Fibre Production, Fibre Metrology

<figure><img src="image_84.png" /></figure>
<figure><img src="image_85.png" /></figure>
# Carne y charqui de llama

C. Ayala<fnref n="1" />, G. Condori<fnref n="1" />, C. Renieri², S. Pilco<fnref n="1" /> and J.L.Quispe<fnref n="1" />

E-Mail: celsoayalavargas@hotmail.com

²School of Farmacy University of Camerino Via Gentile III da Varano s/n I-62032 Camerino. Italy Tel / Fax.: +39-(0)737 403436.

**Abstract.** This paper summarizes several studies carried out over many years on the meat of South American camelids and llama meat in particular. The overview includes aspects of birth, growth, weaning, optimum age of slaughter, classification of the carcass, major and minor cuts, quality of the carcass and meat processing of charqui (traditional conservation of the meat), and technical aspects that have contributed to the legal commercialization of South American camelid meat in Bolivia.

**Resumen.** El presente trabajo es una recopilación de investigaciones realizadas durante muchos años sobre la carne de camélidos sudamericanos y específicamente de carne de llama. Se incluyen estudios desde el nacimiento, crecimiento, destete, edad óptima de faenamiento, clasificación de la canal, cortes mayores y menores, calidad de la canal, procesamiento de la carne en forma de charqui (conservación tradicional de la carne) y aspectos técnicos que han contribuido en la comercialización legal de carne de camélidos sudamericanos en Bolivia.

**Keywords:** meat, carcass quality, llamas, charqui

## Introducción

La problemática de la alimentación humana en el mundo presenta dos diferentes visiones: la de los países desarrollados en los que puede darse mal nutrición puntualmente, y la de los países pobres en los que se dan problemas de desnutrición. En la región de Altos Andes de Bolivia viven al alrededor de 70,000 familias. Están involucradas en la producción de alrededor de tres millones de cabezas de camélidos sudamericanos (CS), con una producción media de carne fresca de 13.884,19 TM/año y de 682.26 TM/año de charqui (carne salada y secada al sol), siendo importante también la producción de vísceras para el consumo humano. La cría de los CS garantiza el sustento alimenticio de estas poblaciones y edades hace menos de una década, la carne de CS en Bolivia se comercializa en forma legal. Antes de ello, la desinformación de sus características nutritivas y la

<footnote n="1">¹Instituto de Investigaciones Agropecuarias y Recursos Naturales, Facultad de Agronomía, Universidad mayor de San Andrés. Calle Landaeta 1583. La Paz-Bolivia</footnote>
atribución de innumerables enfermedades zoonóticas, fueron causantes de grandes prejuicios para su comercio por décadas, a pesar de que históricamente, el consumo de carne fresca y procesada (Charqui), por cientos de años ha garantizado la salud y el bienestar de habitantes con culturas ancestrales en los Andes.

## Metodología

El presente artículo, resume resultados de varios trabajos de investigación desarrollados en Bolivia, que se enmarcan dentro de metodologías estandarizadas para la obtención de carne de CS y en específico de carne de llama, desde el nacimiento del animal, el proceso de crecimiento, la edad óptima de faenado, crecimiento alométrico, proceso de maduración de la carne, parámetros bromatológicos, calidad de la carne, clasificación de la canal, cortes mayores y menores, análisis microbiológicos, procesamiento del charqui (método de conservación de la carne mediante el secado) y análisis químicos y bromatológicos de este subproducto.

## Resultados

### Curva de crecimiento

El crecimiento y desarrollo en los animales es una característica propia de las especies. Así Hammond (1997), define al crecimiento como el aumento de peso de los animales desde el nacimiento hasta su estabilización en la edad adulta. Se determinó el ritmo de crecimiento en llamas, que nacen en un rango de 8 a 12 kg de peso vivo (PV). Al destete alcanzan un promedio de 30 a 35 kg de PV y a los 21 meses logran un peso de 63 a 72 kg para machos y 58-64,5 kg para hembras, no existiendo diferencias significativas entre machos castrados y enteros. La máxima ganancia de peso diario ajustado en pradera nativa fue de 129.11 g/d y de 114.65 g/d para machos enteros y castrados respectivamente. El crecimiento se ajusta a una curva sigmoidea (Figura 1), en la que se pueden distinguir dos partes: a) fase acelerada al principio de la vida, de crecimiento rápido y elevado por unidad de tiempo, y b) la fase auto-inhibición. En la pubertad el crecimiento se desacelera y las ganancias de peso son cada vez más pequeñas hasta que finalmente el animal alcanza la madurez.

Se efectuaron dos métodos para evaluar el crecimiento: uno basado en el peso vivo y datos seriados del faenamiento. Para el ajuste del peso vivo (Y) en función de la edad (x) se utilizó una regresión polinómica de grado tres.

$$ \text{Ecuación 1: } Y = -0.0077 x^3 + 0.2711 x^2 + 0.7488 x + 8.1006 \qquad R^2 = 0.88 $$

$$ \text{Ecuación 2: } Y = -0.0041 x^3 + 0.1045 x^2 + 2.6005 x + 7.8848 \qquad R^2 = 0.90 $$

$$ \text{Ecuación 3: } Y = -0.30x^2 + 10.06x + 14.28 $$
Los animales presentaron diferencias altamente significativas (P<0.01) entre enteros y castrados a los 11 y 12 meses. A partir de los 13 meses y hasta los 15 meses de edad presentan diferencias menos significativas (P<0.05).

<figure><img src="image_86.png" /><figcaption>**Figura 1:** Curva de crecimiento en llamas de sexo macho, enteros y castrados</figcaption></figure>

El cuadro 1 muestra las medidas biométricas tomadas desde los 12 hasta los 23 meses de edad de los animales.

<table><caption>**Cuadro 1:** Medidas biométricas (cm) en llamas de sexo macho</caption><thead><tr><th rowspan="2">Carácter</th><th colspan="2">12 Meses</th><th colspan="2">23 Meses</th><th colspan="2">Incremento</th></tr><tr><th>Enteros</th><th>Castrados</th><th>Enteros</th><th>Castrados</th><th>Enteros</th><th>Castrados</th></tr></thead><tbody><tr><td>Perímetro torácico</td><td>85.55</td><td>86.76</td><td>101.33</td><td>100.78</td><td>15.78</td><td>14.02</td></tr><tr><td>Longitud de tronco</td><td>79.32</td><td>81.56</td><td>92.36</td><td>91.11</td><td>13.04</td><td>9.55</td></tr><tr><td>Ancho de anca</td><td>20.05</td><td>20.31</td><td>25.03</td><td>24.97</td><td>4.98</td><td>4.66</td></tr><tr><td>Altura a la cruz</td><td>84.41</td><td>85.76</td><td>97.11</td><td>96.88</td><td>12.7</td><td>11.12</td></tr></tbody></table>

## Ganancia de peso diario

La máxima ganancia de peso diario en machos enteros de llama fue de 129.11 g/d, que se dio a la edad de 12 meses, con un peso vivo de 42.82 kg, lo que supone el 36 % del peso adulto (Figura 2). A partir de esta edad comienza el denominado crecimiento lento. En machos castrados la máxima ganancia de peso fue de 114 g/d a la edad de 9 meses, con un peso vivo de 36.72 kg, lo que corresponde con el 31 % del peso adulto. En otras especies la máxima ganancia de peso diario, coincide con el inicio de la pubertad Lloyd (1982). Sumar (1991) define el inicio de la pubertad en alpacas a partir de los 11 meses.
<figure><img src="image_87.png" /><figcaption>**Figura 2:** Peso vivo (Kg, PV) y ganancia de peso diario (g/d, GMDT) en llamas machos enteros</figcaption></figure>

### Determinación de la edad óptima de faenamiento

Se determinó la edad óptima de faenamiento entre los 18 y los 21 meses, en el punto de equilibrio en el porcentaje de proteína entre la canal y el peso vivo, y con un periodo de acabado de entre 45 y 60 días.

La Figura 3 muestra la relación de parámetros de productividad y calidad de la carne de llama para determinar la óptima edad de faenamiento.

### Medidas zoométricas y sus correlaciones

Las correlaciones entre las medidas biométricas (perímetro torácico, longitud de tronco, ancho de ancas y altura a la cruz) resultaron entre altas y muy altas: entre perímetro torácico y peso vivo fue de r = 0.94, entre peso vivo y carcasa en caliente r = 0.97, entre peso vivo y canal en frío r = 0.97, siendo inferior la existante entre la altura a la cruz y la longitud de cuello, que presentó un valor de r = 0.59. La correlación entre el peso vivo y la altura a cruz y el ancho de ancas fueron r = 0.74 y r = 0.87 respectivamente. El crecimiento alométrico en la fase I demuestra que existe pleno desarrollo en las extremidades anteriores y posteriores, propio de animales jóvenes. En la fase II el lomo y costilla presentan un crecimiento mayor longitudinalmente. Hacia los 25 meses el incremento en peso tiende a distribuirse en mayor medida en los lomos y cuello.
<figure><img src="image_88.png" /><figcaption>Figura 3: Determinación de la edad óptima de faenamiento</figcaption></figure>

### Crecimiento alómetrico de órganos y vísceras

Se obtuvo una correlación muy alta ($r = 0.86$) entre el crecimiento en peso del conjunto del sistema digestivo y el peso vivo del animal. La media del peso del tracto gastrointestinal a los 13 meses fue de 2.790 g y alcanzó un valor medio de 5.600 g a los 31 meses de edad siendo el incremento de 2810 g durante este periodo de crecimiento. La correlación entre el peso vivo y la piel fue muy alta ($r = 0.88$). Sin embargo la correlación delcrecimiento con el peso de la cabeza fue muy baja ($r = 0.27$), al igual que con el peso de la sangre ($r = 0.17$).

La Figura 4 muestra el desarrollo alométrico relativo de los principales órganos de la cavidad torácica y abdominal, comprendida entre los 13 y 31 meses de edad. Hammond (1960) estableció que los diferentes órganos, tejidos y piezas anatómicas no tienen la misma velocidad de crecimiento. Los nutrientes se distribuyen siguiendo prioridades. La Figura 5 muestra el porcentaje que ocupan los diferentes órganos en el organismo adulto. El orden en que los distintos tejidos culminan su crecimiento es: nervioso, óseo, muscular y graso. La Figura 6 muestra las correlaciones entre el peso vivo y el desarrollo de los órganos. La correlación entre el peso vivo y el de la piel fue $r = 0.88$, entre el peso vivo y el del aparato digestivo $r = 0.86$, entre el peso vivo y el de la cabeza $r = 0.26$, y entre el peso vivo y el de la sangre $r = 0.18$. La correlación entre el peso vivo y el de la canal en caliente fue $r = 0.97$ y entre el peso vivo y el de la canal fría $r = 0.97$.
<figure><img src="image_89.png" /><figcaption>**Figura 4:** Desarrollo alométrico (%) de los órganos de la cavidad abdominal y torácica en función de la edad (meses)</figcaption></figure>

<figure><img src="image_90.png" /><figcaption>**Figura 5:** Distribución porcentual de órganos y tejidos en un animal adulto de 31 meses de edad</figcaption></figure>
<figure><img src="image_91.png" /><figcaption>**Figura 6:** Correlación entre el peso vivo y el de otros órganos</figcaption></figure>

## Rendimiento a la canal

Los valores promedios de rendimiento a la canal caliente y fría fue 57.48 % y 53.54 % respectivamente, similares a los reportados por Bravo (1981) de 58.1 % y 59.6 % en animales enteros y castrados, como muestra el cuadro 2 desde los 15 hasta los 25 meses de edad.

<table><caption>**Cuadro 2:** Rendimiento (%) de la canal caliente y frío según edad</caption><thead><tr><th rowspan="2">Edad (meses)</th><th colspan="2">Rendimiento (%)</th></tr><tr><th>Canal caliente</th><th>Canal frio</th></tr></thead><tbody><tr><td>13</td><td>57.68</td><td>54.33</td></tr><tr><td>16</td><td>60.03</td><td>54.76</td></tr><tr><td>19</td><td>55.29</td><td>51.63</td></tr><tr><td>22</td><td>59.21</td><td>54.21</td></tr><tr><td>25</td><td>55.59</td><td>52.38</td></tr><tr><td>Promedio general</td><td>57.56</td><td>53.46</td></tr></tbody></table>
El Cuadro 3 y la Figura 7 muestran las diferentes medidas realizadas en la media canal de llamas machos faenadas en diferentes períodos de crecimiento. Las medidas en la canal (longitud de la canal, perímetro torácico, longitud del cuello y longitud de pierna), muestran una correlación alta a muy alta con las variables pesos de lomo grueso, pierna, brazuelo y cuello. Las variables longitud del cuello y peso de lomo fino presentaron un coeficiente de correlación inferior al esperado de r = 0.5.

<table><caption>**Cuadro 3:** Medidas de la canal (cm) en machos enteros (E) y castrados (C) según edad</caption><thead><tr><th rowspan="2">Característica<br>(cm)</th><th colspan="8">Edad (meses)</th></tr><tr><th colspan="2">13</th><th colspan="2">16</th><th colspan="2">19</th><th colspan="2">22</th></tr><tr><th></th><th>E</th><th>C</th><th>E</th><th>C</th><th>E</th><th>C</th><th>E</th><th>C</th></tr></thead><tbody><tr><td>Longitud de la<br>canal</td><td>72</td><td>74</td><td>77</td><td>76</td><td>78</td><td>78</td><td>81</td><td>78</td></tr><tr><td>Profundidad<br>de tórax</td><td>24</td><td>24</td><td>25</td><td>26</td><td>28</td><td>28</td><td>28</td><td>28</td></tr><tr><td>Longitud de la<br>pierna</td><td>51</td><td>51</td><td>52</td><td>55</td><td>60</td><td>56</td><td>58</td><td>58</td></tr></tbody></table>

<figure><img src="image_92.png" /></figure>

A-B Longitud de pierna

B-C Largo de carcasa

D-E Profundidad de torax

<caption>**Figura 7:** Medidas de la canal</caption>
### Cortes comerciales

Los pesos de cortes comerciales (pesos de lomo grueso, lomo fino, pierna, brazuelo y cuello) presentaron un coeficiente de correlación alto a muy alto con las medidas biométricas, a excepción del el peso del costillar que presentó un coeficiente de correlación muy bajo con las medidas biométricas.

### Características físicas de la carne; pH

El valor de pH tomó un valor de 5.5 24 horas después del sacrificio, siendo el pH final bajo (5.55) 48 horas después del sacrificio. La Figura 8 muestra los valores de pH cercanos a la neutralidad (pH = 7) o alcalinos (pH > 7), que favorecen la reproducción de microorganismos, entre los culaes están los que originan putrefacción (Aldana 1984).

<figure><img src="image_93.png" /><figcaption>Figura 8: Variación del pH de la carne en 24 horas</figcaption></figure>

### Capacidad de retención hídrica

La canal caliente presenta proteínas con una alta capacidad de cohesión de agua, ya que aún no se ha formado el complejo actomiosina (Lieven 1986). La carne caliente en general presenta un pH = 6.2 lo que también favorece la cohesión de agua y grasas existiendo además una concentración limitada de ATP. Esto en vacunos sucede a las 4 horas y en cerdos en la primera hora. El análisis de varianza para la retención de agua a en la primera hora después del sacrificio mostró diferencias altamente significativas (P<0.01) para el factor edad, mientras que en las 6, 12, 24 y 48 horas siguientes no mostraron diferencias significativas (P<0.01) para los efectos edad, condición e interacción edad por condición (Cuadro 4 y Figura 9).
<table><caption>**Cuadro 4:** Capacidad de retención hídrica en la carne de llama</caption><thead><tr><th rowspan="2">Edad (meses)</th><th colspan="5">Tiempo en horas</th></tr><tr><th>1<sup>ns</sup></th><th>6<sup>ns</sup></th><th>12<sup>ns</sup></th><th>24<sup>ns</sup></th><th>48<sup>**</sup></th></tr></thead><tbody><tr><td>16</td><td>6.60</td><td>6.52</td><td>5.91</td><td>5.64</td><td>5.59<sup>ab</sup></td></tr><tr><td>19</td><td>6.67</td><td>6.49</td><td>5.96</td><td>5.55</td><td>5.52<sup>b</sup></td></tr><tr><td>22</td><td>6.75</td><td>6.47</td><td>5.89</td><td>5.57</td><td>5.54<sup>b</sup></td></tr><tr><td>25</td><td>6.83</td><td>6.67</td><td>6.15</td><td>5.62</td><td>5.64<sup>a</sup></td></tr><tr><td>Promedio</td><td>6.71</td><td>6.53</td><td>5.97</td><td>5.59</td><td><sup>a</sup>= 5.61<br><sup>b</sup>=5.55</td></tr></tbody></table>

<figure><img src="image_94.png" /><figcaption>**Figura 9:** Capacidad de retención hídrica en carne de llama</figcaption></figure>

## Rigidez cadavérica y maduración de la carne

Al examen físico la rigidez cadavérica es instaurada por completo entre 16 a 20 horas, con un pH aproximado de 5.78. La rigidez cadavérica culmina cuando las articulaciones vuelven a ser flexibles a la presión (Aldana 1984). En la llama ocurre transcurridas de 32 a 42 horas (dura de 20 a 24 h) a una temperatura promedio de 15.29 °C. La ruptura del complejo actomiosina de acuerdo a Varnam (1995), es el período donde la maduración de la carne ha concluido, y la carne está lista para el consumo, como muestra la Figura 10.

<footnote>** Diferencias altamente significativas para el factor edad (P< 0.01)</footnote>

<footnote>ns Diferencias entre edades no significativas (P< 0.01)</footnote>

<footnote>a,b Valores con letras iguales no tienen diferencias significativas (P<0.01)</footnote>
<figure><img src="image_95.png" /><figcaption>**Figura 10:** Proceso de rigidez cadavérica después del sacrificio</figcaption></figure>

La maduración de la carne concluye al mismo tiempo que la rigidez cadavérica al cabo de las 32 a 42 horas. La carne madurada y cocinada presenta una consistencia suave a la masticación por el hecho de que existe la degradación de proteínas miofibrilares que acompañan a una reducción de la dureza (Penny 1984). Esta degradación proteolítica según Varnam y Sutherland (1995) es el principal mecanismo de ablandamiento de la carne.

## Evaluación de componentes químicos de la carne

El Cuadro 5 muestra la variación del contenido bromatológico de la carne de llama entre los 13 y los 22 meses de edad.

<table><caption>**Cuadro 5:** Componentes químicos de la carne de machos de llama enteros y castrados</caption><thead><tr><th>Edad (meses)</th><th>Humedad (%)</th><th>Ceniza (%)</th><th>Grasa (%)</th><th>Proteína (%)</th><th>Colesterol (mg/100 g)</th></tr></thead><tbody><tr><td colspan="6">Enteros</td></tr><tr><td>13</td><td>74.77</td><td>1.97</td><td>3.25</td><td>26.93</td><td>54.75</td></tr><tr><td>16</td><td>69.19</td><td>1.20</td><td>5.56</td><td>24.39</td><td>57.50</td></tr><tr><td>19</td><td>71.44</td><td>1.12</td><td>3.03</td><td>24.19</td><td>43.00</td></tr><tr><td>22</td><td>71.98</td><td>1.25</td><td>3.19</td><td>23.04</td><td>68.78</td></tr><tr><td colspan="6">Castrados</td></tr><tr><td>13</td><td>73.79</td><td>2.01</td><td>3.32</td><td>29.53</td><td>58.33</td></tr><tr><td>16</td><td>68.45</td><td>1.23</td><td>4.65</td><td>25.46</td><td>56.33</td></tr><tr><td>19</td><td>71.62</td><td>1.16</td><td>2.75</td><td>24.13</td><td>41.33</td></tr><tr><td>22</td><td>71.50</td><td>1.29</td><td>3.01</td><td>23.63</td><td>81.47</td></tr></tbody></table>

El mayor contenido de humedad se presenta en los machos enteros de 13 meses y el menor en los machos castrados de 16 meses (prueba de comparación de medias, Duncan).
## Contenido de lípidos

El bajo porcentaje de grasa en la carne de llama puede ser efecto de las condiciones del medio ambiente. La curva de la Figura 11 indica, que la proporción de agua en los músculos es menor cuanto mayor es el nivel de grasa en carne de llamas. El porcentaje de grasa varía en otras especies siendo 4.84 % en vacunos, 6.53 % en ovinos, 5.13 % en alpacas y 20.06 % en porcinos.

<figure><img src="image_96.png" /><figcaption>**Figura 11:** Niveles inversamente proporcionales de agua y grasa en carne de llama en función de la edad en meses</figcaption></figure>

## Contenido de colesterol

La media del contenido de colesterol en carne de llama fue 42.16 mg/100 g en animales en edad de sacrificio. Es importante destacar que la carne de los CS tiene un menor contenido de colesterol que la de otras especies domésticas.

<table><caption>**Cuadro 6:** Niveles de colesterol a diferentes edades</caption><thead><tr><th>Edad (meses)</th><th>Colesterol (mg/100 g)</th></tr></thead><tbody><tr><td>13</td><td>56.54<sup>b</sup></td></tr><tr><td>16</td><td>57.08<sup>a</sup></td></tr><tr><td>19</td><td>42.16<sup>b</sup></td></tr><tr><td>22</td><td>74.79</td></tr><tr><td>Promedio</td><td><sup>a</sup> = 56.81 <sup>b</sup> = 49.35</td></tr></tbody></table>

El mayor contenido de colesterol en carne se encontró en animales de 22 meses y el menor contenido en animales de 19 meses (diferencias significativas mostradas por comparación de medias Duncan). El valor promedio fue de 56.81 mg/100 g, similar a lo reportado por Garnica (1993b) de 56.49 mg/100 g para alpacas. En llamas de 19 meses de edad el contenido de colesterol fue 42.16 mg/100 g, valor inferior al reporte de Garnica (1993b).

<footnote>a,b Valores con letras iguales no tienen diferencias significativas (P<0.01)</footnote>
## Ácidos grasos

Los ésteres del glicerol y los ácidos grasos conforman el 99 % de la grasa intramuscular. Sólo se encontraron tres o cuatro ácidos grasos en la carne de llama (oleico, palmítico, esteárico) y cuatro tipos de glicéridos (Cuadro 7).

<table><caption>**Cuadro 7:** Niveles de ácidos grasos en la carne de llama</caption><thead><tr><th rowspan="2">Condición</th><th colspan="5">Ácido Graso</th></tr><tr><th>Mir<br>C:14</th><th>Pand<br>C:15</th><th>Pal<br>C:16</th><th>Est<br>C:18</th><th>Ara<br>C:20</th></tr></thead><tbody><tr><td>Entero</td><td>0.061</td><td>0.036</td><td>0.334</td><td>0.721</td><td>0.353</td></tr><tr><td>Castrado</td><td>0.062</td><td>0.0</td><td>0.309</td><td>0.663</td><td>0.358</td></tr><tr><td>Promedio</td><td>0.061</td><td>0.018</td><td>0.321</td><td>0.692</td><td>0.355</td></tr></tbody></table>

En carnes de otras especies existen rangos como el caso del acido mirístico de 0.9 % en vacunos a 3.26 % en cerdo, el palmítico de 22.34 % en cerdos a 24.14 % en pollos, el esteárico de 4.28 % en cerdo a 13.18 % en pollos y el araquidónico de 0.67 % en pollos a 2.30 % en cordero.

## Contenido de proteína

El Cuadro 8 muestra que el valor promedio en la carne de llama fue 24.54 % de proteína, similar al 24.82 indicado por Pinto (1975). En otras especies el porcentaje de proteína es (Rivera et al., 1996): vacuno (21.01 %), ovino (18.91 %), porcino (19.37 %) y alpaca (21.88 %). El valor de contenido proteico de la canal varía entre el 24.3 % y 25.2 % en machos enteros y castrados respectivamente.

<table><caption>**Cuadro 8:** Porcentaje de proteína en la carne de llama</caption><thead><tr><th>Edad (meses)**</th><th>Condición **</th><th>Proteína (%)</th></tr></thead><tbody><tr><td>13</td><td>Castrado</td><td>29.53</td></tr><tr><td>13</td><td>Entero</td><td></td></tr><tr><td>16</td><td>Castrado</td><td>25.46 <sup>a</sup></td></tr><tr><td>16</td><td>Entero</td><td>24.39 <sup>a b</sup></td></tr><tr><td>19</td><td>Castrado</td><td>24.19 <sup>a b</sup></td></tr><tr><td>19</td><td>Entero</td><td>24.13 <sup>a b</sup></td></tr><tr><td>22</td><td>Castrado</td><td>23.63 <sup>b</sup></td></tr><tr><td>22</td><td>Entero</td><td>23.04 <sup>b</sup></td></tr><tr><td>Promedio</td><td></td><td>24.54 <sup>a</sup></td></tr></tbody></table>

<footnote>** Diferencias altamente significativas (P< 0.01)</footnote>

<footnote>a,b Valores con letras iguales no tienen diferencias significativas (P< 0.01)</footnote>
La Figura 12 muestra la curva donde se observa una bajada en contenido de proteína hasta los 22 meses. Eso significa que a medida que incrementa la edad del animal, la proteína en la carne tiende a disminuir. Los resultados coinciden con Garnica (1993a), quien señala que a mayor edad existe menor contenido de proteína en carne de alpaca. Se observó una mayor ganancia de peso diario a 14 meses, así como un alto contenido proteico a los 13 meses de edad en llamas. Esto fue corroborado por Di Marco (1993) quien indica que la ganancia de peso en animales jóvenes se debe a la mayor retención de proteína. En animales adultos la ganancia de peso se debe al incremento de grasa de depósito en decremento de la retención proteica.

<figure><img src="image_97.png" /><figcaption>**Figura 12:** Niveles de proteína en la canal (%) según la edad de los animales</figcaption></figure>

## Composición química de las vísceras

En los Andes, las vísceras son una alternativa nutricional importante para el consumo humano. Se ha publicado un rango del contenido de grasa de 3.44 a 8.34 %, proteínas de 19.0 a 21.84 %, colesterol de 147.3 a 328.40 mg/g, y un aporte energético de 95.29 a 365 cal/100 g (Cuadro 9).

<table><caption>**Cuadro 9:** Análisis bromatológico de órganos y vísceras de llama en fresco</caption><thead><tr><th>Componentes</th><th></th><th>Hígado</th><th>Estómago</th><th>Intestino</th><th>Pulmón</th></tr></thead><tbody><tr><td>Humedad</td><td>%</td><td>72.83</td><td>66.12</td><td>78.30</td><td>80.13</td></tr><tr><td>Grasas</td><td>%</td><td>3.65</td><td>8.34</td><td>5.27</td><td>3.44</td></tr><tr><td>Proteínas (*6.25)</td><td>%</td><td>21.84</td><td>21.20</td><td>20.72</td><td>19.50</td></tr><tr><td>Colesterol</td><td>mg/100 g</td><td>328.40</td><td>147.30</td><td>286.60</td><td>274.90</td></tr><tr><td>Valor Energético</td><td>cal/100 g</td><td>105.02</td><td>138.69</td><td>365.86</td><td>95.29</td></tr></tbody></table>
## Sistema de clasificación de canales de llama

La Figura 13 muestra las regiones de evaluación de cobertura de grasa. La Figura 14 muestra la clasificación por conformación muscular y las medidas externas e internas en canales de llama.

<figure><img src="image_98.png" /><figcaption>**Figura 13:** Canales de llama clasificadas por cobertura de grasa</figcaption></figure>
<figure><img src="image_99.png" /><figcaption>Figura No. 14: Clasificación de canales por conformación de músculos</figcaption></figure>
### Cortes comerciales en canales de llamas

En el Cuadro 10 y en la Figura 15 se presentan algunos resultados sobre cortes comerciales de canales de llamas.

<table><caption>**Cuadro 10:** Cortes comerciales en machos enteros y castrados</caption><thead><tr><th rowspan="3">Corte comercial</th><th colspan="4">Fase II (19, 22 y 25 meses)</th></tr><tr><th colspan="2">Enteros</th><th colspan="2">Castrados</th></tr><tr><th>Media (Kg)</th><th>Canal frío (%)</th><th>Media (Kg)</th><th>Canal frío (%)</th></tr></thead><tbody><tr><td>Lomo grueso</td><td>1.97</td><td>6.76</td><td>2.79</td><td>7.83</td></tr><tr><td>Lomo fino</td><td>1.83</td><td>6.28</td><td>2.22</td><td>6.23</td></tr><tr><td>Pierna</td><td>5.13</td><td>17.57</td><td>6.16</td><td>17.26</td></tr><tr><td>Brazuelo</td><td>2.66</td><td>9.11</td><td>3.55</td><td>9.95</td></tr><tr><td>Costillar</td><td>1.72</td><td>5.90</td><td>1.36</td><td>3.82</td></tr><tr><td>Cuello</td><td>2.56</td><td>8.77</td><td>3.50</td><td>9.81</td></tr></tbody></table>

<figure><img src="image_100.png" /><figcaption>**Figura 15:** Cortes comerciales en canales frías de machos de llamas</figcaption></figure>
<table><caption>**Cuadro 11:** Peso (Kg) y rendimiento (%) de los cortes mayores de llama (media y desviación estándar, DS)</caption><thead><tr><th rowspan="2">Cortes mayores</th><th colspan="2">Peso (Kg)</th><th colspan="2">Rendimiento/ carcasa (%)</th></tr><tr><th>Media</th><th>DS</th><th>Media</th><th>DS</th></tr></thead><tbody><tr><td>Cuello</td><td>2.96</td><td>0.17</td><td>9.69</td><td>0.85</td></tr><tr><td>Paleta</td><td>3.14</td><td>0.33</td><td>10.50</td><td>0.55</td></tr><tr><td>Paleta</td><td>3.11</td><td>0.22</td><td>10.43</td><td>0.71</td></tr><tr><td>Paletas</td><td>6.25</td><td>0.50</td><td>20.92</td><td>0.95</td></tr><tr><td>Medio lomo</td><td>2.94</td><td>0.38</td><td>9.83</td><td>0.86</td></tr><tr><td>Medio lomo</td><td>2.84</td><td>0.41</td><td>9.49</td><td>0.88</td></tr><tr><td>Lomo</td><td>5.78</td><td>0.61</td><td>19.32</td><td>0.53</td></tr><tr><td>Medio costillar derecho</td><td>1.97</td><td>0.41</td><td>6.53</td><td>0.81</td></tr><tr><td>Medio costillar izquierdo</td><td>1.97</td><td>0.33</td><td>6.54</td><td>0.61</td></tr><tr><td>Costillar</td><td>3.94</td><td>0.72</td><td>13.07</td><td>1.25</td></tr><tr><td>Pierna</td><td>4.98</td><td>0.49</td><td>16.66</td><td>0.60</td></tr><tr><td>Pierna</td><td>5.02</td><td>0.56</td><td>16.76</td><td>0.65</td></tr><tr><td>Piernas</td><td>10.00</td><td>1.03</td><td>33.42</td><td>1.05</td></tr><tr><td>Total cortes mayores</td><td>28.93</td><td></td><td>96.42</td><td></td></tr></tbody></table>

### Proceso tradicional de conservación de la carne de llama (charqui)

Etimológicamente la palabra “Charqui” proviene de la lengua Aimara, que significa “seco”. La técnica milenaria de los Altos Andes consiste en deshidratar la carne magra y saturada en sal, expuesta al sol y a heladas (- 2 °C) en áreas ventiladas, por un periodo de 7-15 días, permitiendo la deshidratación gradual y controlada de la superficie de los tejidos. Su durabilidad no está determinada, pero algunas experiencias indican una durabilidad de hasta 20 años en ambientes fríos y baja humedad. Comparada con las técnicas modernas de conservación de la carne, se trata de un proceso muy parecido a la liofilización, pero a costos bajos en comparación a éste y a otros métodos de conservación.

### Rendimiento de charqui

El proceso comienza con el descarte de animales, se adecuan las prácticas de faenamiento, proceso de oreo y maduración de la carne. El proceso requiere el desgrasado de la carne con el fin de evitar el ranciamiento y olor desagradable del producto. Se realizan filetes o cortes finos de las partes más musculosas, de aproximadamente 1 cm. Luego se procede al salado donde se utilizan dos métodos: el primero usa aproximadamente 40 a 70 g de sal por Kg de carne y el segundo es por inmersión de la carne en salmuera durante 2 o 3 días. El secado de la carne dura 5 a 15 días por acción directa del sol, pérdida de agua, que junto con los
cambios de temperatura hasta heladas de -2 °C, ayudan a inhibir el desarrollo de la actividad microbiana. El rendimiento de canal a charqui es del 34 % con un contenido de grasa de 5.96 % y de proteínas de 60.27 %, haciendo que el producto sea de alta calidad nutritiva (Cuadro 12 y 13).

<table><caption>**Cuadro 12:** Rendimiento de charqui según edad</caption><thead><tr><th>Categoría</th><th>Edad (años)</th><th>Peso vivo promedio (Kg)</th><th>Peso canal (Kg)</th><th>Rendimiento canal (%)</th><th>Rendimiento charqui (%)</th></tr></thead><tbody><tr><td>Adultos ♂</td><td>&gt; 7</td><td>75</td><td>38.0</td><td>52.0</td><td>24.5</td></tr><tr><td>Adultos ♀</td><td>&gt; 7</td><td>62</td><td>31.8</td><td>51.3</td><td>23.0</td></tr><tr><td>Jóvenes ♂</td><td>2-3</td><td>58</td><td>30.9</td><td>53.4</td><td>22.7</td></tr><tr><td>Jóvenes ♀</td><td>2-3</td><td>50</td><td>26.0</td><td>52.0</td><td>23.0</td></tr></tbody></table>

<table><caption>**Cuadro 13:** Composición química del charqui</caption><thead><tr><th rowspan="2">Componentes</th><th rowspan="2"></th><th colspan="3">Categoría</th></tr><tr><th>Entero</th><th>Castrado</th><th>Media</th></tr></thead><tbody><tr><td>Humedad</td><td>%</td><td>7.58</td><td>8.95</td><td>8.26</td></tr><tr><td>Grasa</td><td>%</td><td>8.77</td><td>9.32</td><td>9.04</td></tr><tr><td>Proteínas</td><td>%</td><td>73.30</td><td>70.50</td><td>71.90</td></tr><tr><td>Colesterol</td><td>mg/100 g</td><td>104.4</td><td>272.29</td><td>188.34</td></tr><tr><td>Valor energético</td><td>cal/100 g</td><td>326.86</td><td>318.41</td><td>322.63</td></tr></tbody></table>

### Nueva metodología del procesamiento de charqui

Una innovación en el proceso de la elaboración de charqui se ha realizado en túneles de polietileno, reduciendo el tiempo del secado de 15 días a menos de una semana. El uso de este secador solar permite una mejor calidad higiénico-sanitaria para la elaboración del charqui (Figura 16).

### Análisis microbiológico en la elaboración del charqui

Los análisis microbiológicos en unidades formadoras de colonia por gramo, demuestran la calidad sanitaria del producto, donde las cantidades de sal y el tiempo de secado son factores que minimizan el desarrollo de patógenos en la elaboración del charqui (Figura 17). La relación del número de patógenos en carne fresca y charqui es menor al permitido. Los mesófilos en carne fresca se reducen en el proceso de charqui hasta el punto de no observarse desarrollo de colonias. Según las normas de IBNORCA, los valores hallados en carne fresca fueron 1,00E+06 mientras que en charqui fueron 1,00E+03, en ambos casos el número de bacterias es menor al permitido.
<figure><img src="image_101.png" /><figcaption>**Figura 16:** Evolución del peso de carne por tiempo de secado y tratamiento en la elaboración del charqui</figcaption></figure>

<figure><img src="image_102.png" /><figcaption>**Figura 17:** Relación de Mesófilos en carne fresca y charqui</figcaption></figure>

Los causantes de olores y aromas extraños, así como la decoloración de la superficie se deben a la existencia de mohos y levaduras. La exposición solar "neutraliza" la proliferación de colonias de levaduras y mohos (Figura 18). La presencia de *Staphylococcus aureus* fue inapreciable en la carne fresca, mientras que en charqui tuvo una proliferación de $10^2$ UCF/g, valor que se encuentra en el rango admitido. No se encontraron coliformes totales ni *Clostridium perstringens* ni en carne
fresca ni en charqui. Se observó total ausencia de *Escherichia coli* en carne fresca y charqui, microorganismos que se utilizan como indicadores de contaminación de origen fecal. Igualmente, se observó ausencia de *Salmonella* en todos los casos. El proceso de elaboración de charqui mostró que el producto obtenido era inocuo, sin la presencia de patógenos y dentro de los niveles permitidos para productos elaborados. La técnica elimina todo tipo de patógeno, similar a una liofilización, evitando todo tipo de riesgo de contaminación.

<figure><img src="image_103.png" /><figcaption>Figura 18: Relación de mohos y levaduras en carne fresca y charqui</figcaption></figure>

<table><caption>Cuadro 14: Análisis físico-químico de las vísceras en fresco y en charqui</caption><thead><tr><th rowspan="3">Componentes</th><th colspan="6">Vísceras</th></tr><tr><th colspan="2">Hígado</th><th colspan="2">Estómago</th><th colspan="2">Intestinos</th><th colspan="2">Pulmones</th></tr><tr><th>Charqui</th><th>Fresco</th><th>Charqui</th><th>Fresco</th><th>Charqui</th><th>Fresco</th><th>Charqui</th><th>Fresco</th></tr></thead><tbody><tr><td>Humedad %</td><td>10.20</td><td>72.83</td><td>11.32</td><td>66.12</td><td>12.67</td><td>78.30</td><td>14.67</td><td>80.13</td></tr><tr><td>Grasa %</td><td>11.06</td><td>3.65</td><td>15.26</td><td>8.34</td><td>12.53</td><td>5.27</td><td>10.70</td><td>3.44</td></tr><tr><td>Proteína %</td><td>64.23</td><td>21.84</td><td>61.47</td><td>21.20</td><td>62.02</td><td>20.72</td><td>60.03</td><td>19.05</td></tr><tr><td>Colesterol mg/100 g</td><td>135.50</td><td>328.02</td><td>201.90</td><td>147.30</td><td>342.50</td><td>286.60</td><td>325.70</td><td>274.90</td></tr><tr><td>Valor energético cal/100 g</td><td>364.67</td><td>105.02</td><td>218.60</td><td>138.69</td><td>405.70</td><td>365.86</td><td>165.60</td><td>95.29</td></tr></tbody></table>

El charqui de vísceras es asimismo muy común en los Andes. Su análisis muestra los siguientes valores: grasas del 10.2 % a 14.67 %, proteínas del 60.03 % a 64.23 %, colesterol de 135.1 a 342.5 mg/100 g, y un aporte energético de 165.6 a 405.7 cal/100 g (Cuadro 14).
Bibliografia

ASPA (Associazione Scientifica di Produzione Animale, IT) 1991, Metodología relative alla macellazione degli animali de interesse zootecnico e alla valutazione e dissezione della loro carcasssa. Ismea- Roma. p. 40-43.

Ayala, C. 1992, Crecimiento de peso vivo y longitud de mecha en llamas de la Estación Experimental de Patacamaya. Tesis Med. Vet. Zoot. Puno, Perú. UNA 50-60

Bravo, W; Franco, E; Sumor, J. 1981. Rendimiento de canal en llamas. Res. IV In Convención Internacional sobre Camélidos Sudamericanos. Punta Arenas, CL. p.78

Bonavia, D. 1996, Los camélidos sudamericanos: una introducción a su estudio. IFEA-UPCH, Conservation International. p. 65-68, 496-499.

Bustinza, V; Carreon, O. 1983, Biometría. In Bustinza, V. ed. Carne de Alpaca. Puno, PE.EPG – UNA. p. 23-41.

Di Marco, O. 1993, Crecimiento y respuesta animal. 1 ed. Buenos Aires, AR. AAPA.

Foraquita, S.; Bustinza, V. 1993, Cortes de Carne. In Bustinza, V. ed. Carne de Alpaca. Puno, PE. EPG – UNA. p. 73-82.

Garnica, P. J. 1993a, Composición Química de la Carne. In Bustinza, V. ed. Carne de Alpaca. Puno, PE. EPG – UNA. p. 105-120.

Gerken, M. 1998, Metodología de estudio y análisis de la calidad de carne de camélidos y análisis sensorial. Seminario Proyecto SUPREME (1). Resúmenes. Córdoba, AR. UCCOR, PLANCAD, ENEA, CCE. p. 7-9.

Leon, J.B; Smith, B.B; Tim, K.L. 1989, Growth characteristics of the llama (Lama glama) from birth to 12 month old. In The Veterinary Record. Oregon. p. 644-645.

Lieven, C. 1985, Aprovechamiento de la carne de llamas, alpacas y capibaras en regiones tropicales. Tesis de Ph. D. Alemania. Universidad Ludwing-Maximilian de Munich Facultad de Veterinaria. p. 34-38.

Pinto, V. M. 1975, Estudio de algunos caracteres de la producción de carne en llamas. Tesis. Lic. Agr. Cochabamba, BO. Universidad Mayor de San Simon.

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Torrez, S. D. 1998., Análisis de la potencialidad de producción y caracterización cualitativa de la carne de camélidos, Seminario Proyecto SUPREME. (1): resúmenes. Córdoba, AR. UCCOR, PLANCAD, ENEA, CCE. p. 12-13.

Visier, A. 1980, Industria de la carne. Barcelona ES. Editorial AEDOS. p. 23-36
# Wool Scouring in Europe: Urgent and Ecological Solutions

## M.T. Chaupin

Association ATELIER-Laines d'Europe, c/o Filature de Chantemerle, F-0330

Saint Chaffrey, France

E-Mail: atelier5@orange.fr

**Abstract.** Wool scouring is the essential intervening step between agriculture, which provides the fleeces, and the craft and textile industries, which make them into finished products. However, there are many future concerns regarding the problematic situation and recent disappearance of many scouring plants across Europe. If this stage, already fragile in Europe, would break down, the whole value chain may also disappear.

**Resumen.** El lavado de la lana es el paso intermedio esencial entre la agricultura, que proporciona los vellones y las industrias artesanales y textiles que los convierten en productos terminados. Sin embargo, actualmente existe preocupación de cara al futuro por la desaparición en los últimos años de muchas plantas de lavado en Europa, y las dificultades que experimentan otras. Si se interrumpe esta etapa intermedia de lavado, ya debilitada en Europa, toda la cadena de valor podría también desaparecer.

**Keywords:** wool scouring, European wool industry, sheep breeding, wastewater and energy, ecological treatment

## Introduction

For several years already, new initiatives for adding value to wool have been developed by breeders and craft workers. Such initiatives are strongly linked to environmental concerns, especially preservation of threatened breeds. They have worked on creating direct links between breeders and processors, aiming to bring the benefit of value added closer to the wool producer.

In any case, whether it concerns sheep, alpacas, angora or cashmere goats, the first steps of processing are more or less the same: shearing, grading the fleeces, storage and transport to the scouring plant.
## A weak link

Wool scouring is the essential intervening step between agricultural processes resulting in the provision of the fleeces and the craft and textiles industries, developing them into finished products. However, there are many future concerns regarding the problematic situation and recent disappearance of many scouring plants across Europe. If this stage, already fragile in Europe, would break down, the whole value chain may also disappear.

## Wool scouring: a question of scale

There are numerous techniques for scouring wool, for example:

* wool scouring in hot springs, traditionally used in some regions (Pyrénées, France)

* a trailer with a degreasing bowl heated by solar panel, a washing machine, travelling from one farm to another

* a discontinuous scouring plant set up in Czech Republic by a Romney sheep breeders' association

* a rinsing bowl, using river water in Ariège (France)

* small sized leviathans in regional scouring plants (Saugues and Souvigny, France)

* larger scouring plants (e.g., in Tavares (Portugal) or in Traitex (Belgium))

Bigger plants can be found in the UK (e.g., Haworth), in Italy (e.g., Pettinatura di Verrone) or in Czech Republic (Modiano Nedjeck).

## The operation of a scouring plant

The process is always the same: opening the fleeces, scouring with water, heat, sodium carbonate and movements, rinsing, removal of water, and drying.

## Water, energy and wastewater: an ecological challenge

Water consumption in industrial scouring plants is generally around 8-20 litres per kg of greasy wool, but sometimes much more in smaller and older plants. The main energy requirement for scouring emerges from heating the water for bowls.

## 50 % impurities

Depending on the sheep breed and husbandry system used, the wool fibre only represents around a third to two thirds of the total weight of the fleece. The other constituents are wool grease and suint, sands and dust.
## Wastewater treatments

Treating wool scour effluent is highly difficult, as wool grease has a high pollution factor. For example, a wool scour processing 1 t of greasy wool a day requires effluent treatment equivalent to the domestic sewage requirement of a town of between 1,250 to 4,000 inhabitants. However, ecological solutions already exist for example by means of spreading to soil, a pre-purification plant for the effluent or methane generation.

## European meeting in November 2015

On the initiative of associations ATELIER-Laines d'Europe, Pôle Laine du Pays de Saugues and Lainamac, 150 participants from 15 European countries, representing all stages of the wool processing industry met in Saugues, Haute-Loire, from 4-6 November, 2015 to share ideas and look for solutions.

The proceedings of the meeting include the oral presentations, descriptions of various projects, report of debates, local visits, with an annex including maps, useful addresses and a glossary.

## Conclusion

The small scouring plant in Saugues, the town where the meeting took place, was an old one, neither very efficient nor sustainable. The local authorities are now aware of this enterprise playing an important role for about 100 French sheep breeders who bring their fleeces here every year and depend on it. The authorities now support a 3-year plan for improving the whole installation and treatment of wastewater. On the Island of Gotland (Sweden), a new scouring plant is now running since summer 2016. We hope that the dissemination of the book at all levels, farming, crafts and industry, local authorities and EU bodies, will help to maintain the existing installations and even create new ones. It will allow everyone to participate in the development of the European wool industry and consider its future with optimism.

## References

* Association ATELIER-Laines d'Europe, 2016, Laver la laine, Le lavage des laines en Europe : urgence et avenir écologique. Scouring wool. Wool scouring in Europe : urgent and ecological solutions. A bilingual book.
<figure><img src="image_104.png" /></figure>
# Proteomic Method for Determination of Animal Hair Fibres

C. Tonetti¹, S. Paolella¹, D.O. Sanchez Ramirez¹, R.A. Carletto¹, C. Vineis¹, A. Varesano¹ and S. Sforza²

¹CNR-ISMAC, Institute for Macromolecular Studies, Corso G. Pella 16, Biella, Italy

²Department of Food Science, University of Parma, Via Università 12, Parma, Italy
E-Mail: c.tonetti@bi.ismac.cnr.it

**Abstract.** The market of high quality textiles requires suitable analytical methods for the determination of their fiber composition to guarantee that no falsification occurs. The proteomic method, developed in recent years and based on the ultra-performance liquid chromatography coupled with electrospray mass spectrometry (LC/ESI-MS), was successfully used for the identification and quantification of the most commercial Bovidae fibres (wool, cashmere and yak). This is possible because keratin from sheep, cashmere goat and yak are similar but not identical. Indeed, in some specific parts of the protein there are amino acidic variants that can be used as specific peptide-marker to distinguish each animal fibers. In this paper, the proteomic method was applied to other animal hair fibers, such as Camel, Lama, Alpaca, Vicuna and Guanaco, in order to identify new molecular markers to discriminate Camelidae from Bovidae. Preliminary results showed that there are specific molecular markers for Camelidae and for Bovidae, suitable both for qualitative and quantitative analysis.

**Resumen.** El mercado de textiles de alta calidad requiere métodos analíticos adecuados para determinar la composición de la fibra y poder así evitar falsificaciones. El método proteómico, desarrollado en los últimos años y basado en la cromatografía líquida de ultra-rendimiento en acoplamiento con espectrometría de masas por electrospray (LC/ESI-MS), se utilizó con éxito para la identificación y cuantificación de fibras comerciales de la familia Bovidae (lana, cashmire y yak). Esto fue factible porque las queratinas de oveja, cabra cashmire y yak son similares pero no idénticas. De hecho, en algunas partes específicas de la proteína existen variantes aminoacídicas que pueden ser utilizadas como marca-dores peptídicos específicos de la fibra de cada especie. En este trabajo, el método proteómico se aplicó a otras fibras animales, como el camello, llama, alpaca, vicuña y guanaco, con el fin de identificar nuevos marcadores moleculares para discriminar la familia Camelidae de la Bovidae. Los resultados preliminares mostraron la existencia de marca-dores moleculares específicos para Camelidae y para Bovidae que serían adecuados tanto para el análisis cualitativo como cuantitativo.

**Keywords:** LC/ESI-MS, animal fibers, bovidae, camelidae
**Introduction**

Special animal hair fibres, in particular cashmere, yak, mohair, camel and alpaca, are obtained from domestic mammals of the genera Capra, Bos, Camelus and Llama. These fibres are valuable natural raw materials used by the fashion industry for manufacturing high quality luxury textiles, and as such are distinct from fibres derived from sheep's wool.

International producers of textiles in cashmere and other specialty fibres require suitable analytical methods for the determination of their fiber composition to guarantee that no falsification occurs, especially when cheaper fibers, like wool and yak, are blended with expensive fibers, like cashmere.

The traditional and most used methods for identifying animal fibres for the textile sector involve microscopy. Light microscopy (LM) allows to observe the internal and external structure of the fibres such as pigmentation, medullation, shape and cuticle morphology (Appleyard, 1978); scanning electron microscopy (SEM) shows the surface morphology and the fine structure of the cuticle at high resolution (Langley et al., 1981).

The traditional microscopic techniques are subjective depending on the expertise of the operator and often are affected by chemical treatments to which the fibers have been submitted during textile processing. Several methods have been studied to improve the objectivity and accuracy of the results of the animal fiber blend identification, like methods based on the extraction and analysis of DNA (Tang et al., 2014) or based on specie-specific monoclonal antibodies (Tonetti et al., 2012). Nevertheless, the results obtained are often affected by chemical treatment such as bleaching, dyeing and depigmentation.

The proteomic method (Paolella et al., 2013; Vineis et al., 2014), developed in recent years and based on the ultra-performance liquid chromatography coupled with electrospray mass spectrometry (LC/ESI-MS), was successfully used for the identification and quantification of the most commercial Bovidae fibres (wool, cashmere and yak). This is possible because keratin from sheep, cashmere goat and yak are similar but not identical. Indeed, in some specific parts of the protein there are amino acidic variants that can be used as specific peptide-marker to distinguish each animal fiber.

This method has been validated analyzing several samples in different shapes and with different treatments (fibres, slivers, yarns, fabrics, raw materials, dyed, depigmented, bleached, finished), in order to verify the accuracy of the LC/ESI-MS method and the laboratory repeatability (Vineis et al., 2017). Results proved that LC/ESI-MS technique is an objective and accurate method for animal hair fibers analysis, unaffected by chemical treatment and applicable to sample from various stages of textile processing.

The aim of this paper is to apply the proteomic method to other animal hair fibers, such as Camel, Llama, Alpaca, Vicuna and Guanaco, in order to identify new molecular markers to discriminate Camelidae from Bovidae.
# Materials and Methods

## *Samples*

Authentic samples of wool, cashmere, yak, camel and South American camelids (alpaca, llama, vicuna and guanaco) and their blend in different shapes and with different treatments (fibres, slivers, yarns, fabrics, raw materials, dyed, depigmented, bleached, finished) were kindly supplied by the Cashmere and Camel Hair Manufacturers' Institute (CCMI), Boston, MA, USA and by trusted companies that supported the research.

## *Protein-extraction*

Samples were scoured, dehaired, cleaned with petroleum-ether for 2 h in a Soxhlet extractor, rinsed for 1 h in water at room temperature and finally for 1 h in water at 50 °C. The fibres were dried in an oven at 50 °C and then conditioned in standard atmosphere at 20 °C, 65 % RH, for 24 h. The fibres (150 mg) were placed in a test tube and 9.5 ml of extraction buffer (25 mM Tris-HCl, pH 8.5, 2.4 M thiourea, 5 M urea, 5 % dithiothreitol (DTT)) were added. The buffer was left in contact with the fibres for two days at 50 °C under slow stirring. The solution was then filtered on 0.45 µm filter in a centrifuge 5,000 g for 15 min at room temperature.

## *Trypic digestion*

To 67 µl of the protein solution an equal volume of 100 mM NH4HCO3 was added, mixing by vortex. A 5 µl portion of a 200 mM DTT solution in 100 mM NH4HCO3 was added, followed again by vortex mixing. The solution was incubated for 1 h at room temperature and 4 µl of iodoacetamide 1 M in 100 mM NH4HCO3 was added, followed again by vortex treatment. The solution was further incubated for 1 h at room temperature and the excess iodoacetamide eliminated by adding 20 µl of a 200 mM DTT solution, followed again by treatment with vortex and incubation for 1 h at room temperature. Finally, 818 ml of deionized water and 20 µl of trypsin solution (100 ng/ml in 1 % CH3COOH) were added, followed again by vortex treatment. The solution was allowed to stand for 4 hours at 37 °C. The reaction was stopped with 2 µl of HCl (at 37 % or 12N) and the volume was reduced under nitrogen flux.

## *LC/ESI-MS analysis*

The dried samples were dissolved in 100 µl of eluent A, treated with vortex and transferred to vials for UPLC-MS analysis. The analysis was performed using an Acquity UPLC BEH300 C18 1.7 µm column (Waters). Gradient elution was conducted using two eluents: A (H2O + 0.2 % CH3CN + 0.1 % HCOOH) and B
(CH3CN + 0.1 % HCOOH). The instrumental conditions and the acquisition parameters are reported in our previous works (Paolella et al., 2013; Vineis et al., 2014).

## Results and Discussion

The principles of the proteomic method is that keratin sequences, extracted from Bovidae or Camalidae, might be slightly different in the different species, because in some specific parts there are aminoacidic variants. Peptides containing these variants have different molecolar weight and different sequences among the species, thus they might be differentially detected by mass spectrometry, acting as species-specific molecular markers. For example the peptide-marker already identified in previous papers for Bovidae like cashmere goat, yak and sheep wool), as reported in Table 1, are specific for the corresponding animal fibres implying that they are absent in the others. Only sheep-goat markers, as the name suggest, can be found in both cashmere and sheep wool, but they are absent in yak.

<table><caption>**Table 1:** Marker peptides identified for Bovidae (wool, cashmere and yak fibres)</caption><thead><tr><th>Molecular mass (Da)</th><th>Retention time (min)</th><th>Characteristic ions (m/z)</th><th>ID<sup>a</sup></th></tr></thead><tbody><tr><td>2634</td><td>41.6</td><td>879.0</td><td>Cashmere 1 (C1)</td></tr><tr><td>2691</td><td>41.0</td><td>898.1</td><td>Cashmere 2 (C2)</td></tr><tr><td>2607</td><td>42.0</td><td>870.1</td><td>Wool 1 (W1)</td></tr><tr><td>2664</td><td>41.3</td><td>889.0</td><td>Wool 2 (W2)</td></tr><tr><td>2234</td><td>39.0</td><td>745.7</td><td>Wool-cashmere 1 (WC1)</td></tr><tr><td>4738</td><td>43.4</td><td>948.5 + 1185.6</td><td>Wool-cashmere 2 (WC2)</td></tr><tr><td>2504</td><td>38.9</td><td>835.5</td><td>Yak 1 (Y1)</td></tr><tr><td>2520</td><td>39.1</td><td>1260.2 + 840.9</td><td>Yak 2 (Y2)</td></tr></tbody></table>

Following the same principle, the proteomic method was also applied to other animal hair fibers, such as Camel, Llama, Alpaca, Vicuna and Guanaco, in order to identify new molecular markers to discriminate Camelidae from Bovidae. The pure fiber of Camelidae and Bovidae were analyzed. Comparing the peptides obtained from the analysis in LC/ESI-MS of camel fibers, it was possible to identify several peptides present or only in Camelidae and absent in Bovidae or absent in Camelidae and present in one or more Bovidae. Among these peptides, 5 are present only in Camelidae and 7 only in Bovidae.

The markers have been evaluated for their specificity both qualitatively and quantitatively. All markers were determined in mixed samples by single ion recording (SIR) detection, specifically monitoring only the characteristic ions. Chromatographic areas associated to the markers were integrated in order to estimate the percentage in mixed samples.
In order to verify the correspondence between the calculated and the actual percentages, different calibration curves were produced by preparing two-fiber mixed samples (one Camalidae vs one Bovidae) with different percentage composition: only 3 peptides among those identified can be used as specific and quantitative markers for a generic Camelidae. The limit of detection for Camelidae is 3 %.

In order to confirm UPLC/ESI-MS is an accurate and entirely acceptable method for distinguishing and quantifying the composition of Camalidae from Bovidae, a validation with blind samples in different shapes and with different treatments is necessary. The results already obtained in previous work for wool, cashmere and yak fiber mixtures (the results are reported in Table 2) proved that LC/ESI-MS method is unaffected by chemical treatment and applicable to sample from various stages of textile processing.

<table><caption>**Table 2:** Bovidae samples analysed by UPLC/ESI-MS compared to the actual percentage composition*</caption><thead><tr><th rowspan="2">Blind samples</th><th colspan="3">UPLC/ESI-MS</th><th colspan="3">Actual</th><th rowspan="2">Averaged trueness (%)</th></tr><tr><th>C (%)</th><th>W (%)</th><th>Y (%)</th><th>C (%)</th><th>W (%)</th><th>Y (%)</th></tr></thead><tbody><tr><td>A</td><td>23</td><td>77</td><td>0</td><td>20</td><td>80</td><td>0</td><td>2,4</td></tr><tr><td>B</td><td>56</td><td>44</td><td>0</td><td>50</td><td>50</td><td>0</td><td>4,9</td></tr><tr><td>C</td><td>85</td><td>15</td><td>0</td><td>80</td><td>20</td><td>0</td><td>4,1</td></tr><tr><td>D</td><td>26</td><td>36</td><td>38</td><td>20</td><td>30</td><td>50</td><td>8,5</td></tr><tr><td>E</td><td>33</td><td>32</td><td>35</td><td>30</td><td>40</td><td>30</td><td>5,7</td></tr><tr><td>F</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td></tr><tr><td>G</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td></tr><tr><td>H</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>I</td><td>70</td><td>0</td><td>30</td><td>75</td><td>0</td><td>25</td><td>4,1</td></tr><tr><td>J</td><td>20</td><td>0</td><td>80</td><td>15</td><td>0</td><td>85</td><td>4,1</td></tr><tr><td>K</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>L</td><td>90</td><td>0</td><td>10</td><td>90</td><td>0</td><td>10</td><td>0</td></tr><tr><td>M</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>N</td><td>43</td><td>57</td><td>0</td><td>50</td><td>50</td><td>0</td><td>5,7</td></tr><tr><td>O</td><td>0</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td></tr><tr><td>P</td><td>22</td><td>10</td><td>68</td><td>20</td><td>10</td><td>70</td><td>1,6</td></tr><tr><td>Q</td><td>40</td><td>16</td><td>44</td><td>40</td><td>20</td><td>40</td><td>3,3</td></tr><tr><td>R</td><td>60</td><td>0</td><td>40</td><td>60</td><td>0</td><td>40</td><td>0</td></tr><tr><td>S</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>T</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td></tr><tr><td>U</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>V</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>W</td><td>72</td><td>0</td><td>28</td><td>80</td><td>0</td><td>20</td><td>6,5</td></tr><tr><td>X</td><td>25</td><td>45</td><td>30</td><td>25</td><td>50</td><td>25</td><td>4,1</td></tr><tr><td>Y</td><td>60</td><td>0</td><td>40</td><td>60</td><td>0</td><td>40</td><td>0</td></tr><tr><td>Z</td><td>90</td><td>0</td><td>10</td><td>90</td><td>0</td><td>10</td><td>0</td></tr><tr><td>a</td><td>43</td><td>0</td><td>57</td><td>50</td><td>0</td><td>50</td><td>5,7</td></tr><tr><td>b</td><td>51</td><td>0</td><td>49</td><td>50</td><td>0</td><td>50</td><td>0,8</td></tr><tr><td>c</td><td>43</td><td>57</td><td>0</td><td>40</td><td>60</td><td>0</td><td>2,4</td></tr><tr><td>d</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>0</td></tr><tr><td>e</td><td>0</td><td>0</td><td>100</td><td>0</td><td>0</td><td>100</td><td>0</td></tr></tbody></table>

<footnote>*The trueness of the analysis method was calculated as the difference of the mean of the measured value to the actual value. The trueness obtained for the samples was between 0 % (in pure samples) and 8.5 %.</footnote>
More investigation are necessary but preliminary results of treated samples of
mixture Camalidae-Bovidae show that the specific new marker are good candidates
to be use in determination of animal hair fibers in all stage of textile processing
(data not shown).

Finally, the some approach has been applied in order to distinguish Camel
from South American camelids fibres (alpaca, llama, vicuna and guanaco). Between
all the peptides identified as potential specific-peptide marker, 8 peptides seem to
be specific markers for qualitative analysis (data not shown). The validation as
qualitative and quantitative analysis is work in progress.

Conclusion

The proteomic method based on the use of liquid chromatography coupled with electrospray mass spectrometry was applied to Camalidae animal hair fibers, such as Camel, Llama, Alpaca, Vicuna and Guanaco, in order to identify new molecular markers to discriminate Camelidae from Bovidae. Several peptides were identified and they were evaluated for their specificity both qualitatively and quantitatively. The identification and validation of specific markers suitable to distinguish Camel from South American camelids fibres is in progress. The proteomic method continues to be successful applied to the identification of animal hair fibres (such as Bovidae and Camalidae) in sample of different shapes and with different treatments.

This method showed good repeatability, reproducibility and accuracy, and it
was not influenced by different treatments to which the fibers have been subjected
or by the presence of other fibers different from animal hairs. The LC/ESI-MS
method was tested for qualitative and quantitative analysis and it was already
validated for wool, cashmere and yak. The detection limit was of 3 %. According
to these results, the UPLC/ESI-MS method is under review for publication as ISO
standard method for qualitative and quantitative analysis of wool, cashmere and
yak fibres.

References

Appleyard, H.M. 1978, Guide to the identification of animal fibres. Leeds: WIRA, 1–5.

Langley, K.D., Kennedy, T.A. 1981, The identification of speciality fibres. Textile Research Journal, 51: 703–709.

Tang, W.M., Zhang, W., Zhou, H., Fei, J., Yang, J., Lu, W., Zhang, S., Ye, S., Xiaoping 2014, A real-time PCR method for quantifying mixed cashmere and wool based on hair mitochondrial DNA. Textile Research Journal, 84(15):1612-1621.

Tonetti, C., Vineis, C., Aluigi, A., Tonin, C. 2012, Immunological method for the identification of animal hair fibres. Textile Research Journal, 82(8):766–772.

Paolella, S., Bencivenni, M., Lambertini, F., Prandi, B., Faccini, A., Vineis, C., Tonetti, C., Sforza, S. 2013, Identification and quantification of different species in animal fibres
by LC/ESI-MS analysis of keratin-derived proteolytic peptides. Journal of Mass Spectrometry, 48 (8): 919-926.

Vineis, C., Tonetti, C., Paolella, S., Pozzo, P.D., Sforza, S. 2014, A UPLC/ESI-MS method for identifying wool, cashmere and yak fibres. Textile Research Journal, 84(9):953-958.

Vineis, C., Tonetti, C., Sanchez Ramirez, D.O., Carletto, R.A., Varesano, A. 2017, Validation of UPLC/ESI-MS method used for the identification and quantification of wool, cashmere and yak fibres. The Journal of The Textile Institute, DOI:10.1080/00405000.2017.1317225
<figure><img src="image_105.png" /></figure>
# The Use of Near-Infrared (NIR) Reflectance Spectroscopy to Predict Mohair Quality in Greasy Fleece Samples of Angora Goats

D. Allain<fnref n="1" />, S Brenot<fnref n="2" />, G Auvinet<fnref n="2" />, B Pena-Arnaud<fnref n="1" /> and P. Martin<fnref n="3" />

E-Mail: pierre.martin@capgenes.com

**Abstract.** One experiment was conducted in order to test the utility of near-infrared spectroscopy (NIRS) to predict mohair quality, i.e. i) clean mohair content and ii) mean fibre diameter (MFD) in Angora goat fleece. A total of 397 mohair fleece samples were collected in 2016 within the framework of the French selection scheme including performance recording, fleece assessment and fibre measurements. Fleece samples were laboratory measured for clean mohair content and MFD by OFDA methodology, then scanned in a Petri dish using a NIRS portable instrument (LabSpec ® 5000; ASD Inc, Boulder, USA) by reflectance in the VIS and NIR regions (350 to 2,500 nm). Partial least square (PLS) regression was used to develop a number of calibration models between the spectral and reference measurements. Different mathematical treatments were used during model development. The methods studied were partial least squares regression (PLS) and first-derivative pretreatment + PLS. Cross validation was used to assess the performance and avoid overfitting of the models. NIR prediction of MFD gave a low R<fnref n="2" /> (<0.70) whatever the calibration models. By using the first derivative of the raw spectra in the NIR region (800 to 2,500 nm), the calibration models gave a coefficient of determination in calibration (R<fnref n="2" />) of 0.81 for clean mohair content with a low relative error (3.5 %). It is concluded that NIR reflectance spectroscopy can be used to predict clean mohair content with a good precision but not for determining mean fibre diameter. However the use of OFDA 2000 MFD measurement along the greasy staple can be used as an alternative. Thus NIR spectroscopy to predict clean mohair content and OFDA2000 to measure fibre diameter along greasy staple would be widely used to assist the French Angora goat breeding program and allowing a large reduced cost of fibre measurements.

**Resumen.** Se realizó un experimento para probar la utilidad de la espectroscopía del infrarrojo cercano (NIRS) para predecir la calidad del mohair, es decir 1) limpiar contenido de mohair y 2) diámetro de la fibra media (MFD) en lana de cabra de Angora. Se recolectaron un total de 397 muestras de lana de mohair en 2016 en el marco del esquema

<footnote n="1">¹INRA UMR GenPhySE, Toulouse, CS 52627, 31326 Castanet Tolosan, France, E-Mail:daniel.allain@inra.fr</footnote>

<footnote n="2">²INRA UE GENESI, Le Magneraud BP 52, 17700 Surgères, France, E-Mail:sylvie.brenot@inra.fr</footnote>

<footnote n="3">³Capgenes Section Angora Agropole – 2135 Route de Chauvigny 86550-MIGNALOUX BEAUVOIR, France</footnote>
de selección francés incluyendo el registro del rendimiento, evaluación del vellón y mediciones de fibra. Las muestras de lana se analizaron en el laboratorio midiendo el contenido limpio mohair y MFD por metodología OFDA, analizándose luego en una placa Petri con un dispositivo portátil de NIRS (LabSpec® 5000; ASD Inc., Boulder, E.E.U.U.) por reflexión en las regiones VIS y NIR (350 a 2.500 nm). Para desarrollar modelos de calibración entre las mediciones espectrales y las de referencia, se utilizó la regresión de mínimos cuadrados parciales (PLS). Se utilizaron diferentes ajustes matemáticos durante el desarrollo del modelo. Los métodos estudiados fueron la regresión de mínimos cuadrados parciales (PLS) y el pretratamiento de la derivada primera + PLS. Para evaluar la capacidad predictive de los modelos y evitar sobreajustes, se emplearon tácnicas de validación cruzada. La predicción NIR del MFD presentó un R² bajo (< 0.70) independientemente del modelo de calibración. Usando la primera derivada de los espectros brutos de la región NIR (800 a 2.500 nm), los modelos de calibración dieron un coeficiente de determinación (R²) de 0.81 para contenido mohair limpio con un bajo error relativo (3,5 %). Se concluyó que la espectroscopía de reflectancia NIR puede utilizarse para predecir contenido de mohair limpio con una buena precisión, pero no para determinar el diámetro medio de fibra. Sin embargo, el uso de la medición de la OFDA 2000 MFD sobre la mecha grasa puede utilizarse como alternativa. Por tanto, se podría utilizar ampliamante la espectroscopía NIR para predecir el contenido limpio mohair y el OFDA2000 para medir el diámetro de la fibra sobre la mecha grasa como ayuda en el programa francés de mejora genetic de la cabra de Angora, programa de cría y permitiendo una gran reducción del coste de las mediciones de fibra.

**Keywords:** mohair, NIR spectroscopy, clean mohair content, mean fibre diameter

## Introduction

Clean yield of mohair and mean fibre diameter are economically important traits for French producers. The French mohair industry is vertically integrated, where producers are processing the whole production within the textile industry and then sell directly to consumers final products. As clean mohair content ranges from 50 to 90 %, accurate evaluation is required. Standard methods for determining yield are lengthy and time-consuming. Current methods involve scouring or washing in aqueous solution to remove grease, suint and dirt and then drying and weighing the samples prior to analysis by conventional analytical techniques (Connell & Brown, 1978; Connell, 1983; Coleman et al., 1999; Church & O'Neill, 1999). Furthermore, standard methods for determining fibre diameter are based on measurements on clean fibre. However, OFDA2000 methodology allows measurements of fibre diameter along the greasy staple using an automatic correction for greasy factor, but this method has not been tested for mohair.

Near-infrared spectroscopy (NIRS) is an analytical technique based on the absorption of infrared light by organic matter. Since absorption is linked to the chemical composition of samples, it can be predicted after a calibration phase. Near infrared (NIR) reflectance spectroscopy is used for the quality evaluation of
foods and forages from the early 1970s (Murray, 1993; Osborne et al., 1993; Batten
1998). This technique is based on the vibrations of molecular bonds in the NIR
electromagnetic region containing H attached to atoms such as N, O and C, which
are constituents of the organic matrix (Murray, 1993; Osborne et al., 1993; Batten,
1998). In NIR spectroscopy, calibration is a mathematical process, which generally
uses multivariate regression techniques (e.g. partial least squares) to relate
absorbance measurements from a NIR spectrophotometer at different wavelengths
(e.g. 800 to 2,500 nm) to reference values measured by conventional chemical or
physical methods (Osborne et al., 1993; Deaville & Flinn, 2000). The advantages of
NIR spectroscopy include the speed of the analysis, simplicity of sample
preparation, multiplicity of analysis, and lack of chemicals required (Murray, 1993;
Deaville & Flinn, 2000). The NIR technique has been used for both at- and on-line
applications in the textile industry for quality control of, for example, moisture,
residual grease and contamination of wool (Slack-Smith et al., 1979; Church &
O'Neill, 1999; Hammersley & Townsend, 2004). Previous studies have shown that
near-infrared spectroscopy has potential for rapid analysis of raw mohair fleeces to
predict clean mohair content (Coleman et al., 1999).

The objective of this study was to explore the potential use of visible (VIS) and NIR spectroscopy coupled with multivariate statistical tools (partial least squares), to predict clean mohair content and fibre diameter of greasy mohair samples and to test fibre diameter measurement along the greasy staple in order to assist the French Angora goat breeding program.

**Material and methods**

A total of 397 fleece samples from 132 males and 265 females of 18 months to 3
years of age and issued from 38 different herds were collected in 2016 within the
framework of the national selection scheme of French Angora goat including
performance recording, fleece assessment and fibre measurements (Allain &
Roguet, 2003).

Laboratory measurements of clean mohair content and fibre diameter

All fleece samples were determined for clean mohair content at INRA (GenESI
laboratory) using a simplified washing method using sonification for aqueous
scoring. Fleece samples remained for at least 24 hours under a controlled ambient
environment (20 °C, 60 % relative humidity). Then about 10 g of each fleece
samples were weighed, introduced within a fine mesh net and then deposit into an
ultrasonic tank filled with a warm soapy-aqueous solution (at 45 °C) for
sonification during half an hour. Thereafter fine mesh nets were dried at 85 °C in a
drying oven, then put under a controlled ambiant environment (20 °C; 60 %
relative humidity) for 24 hours and were finally weighed. Clean mohair content was
determined as the part of clean mohair to greasy mohair within each fleece sample.
Mean fibre diameter (MFD) measurements were made at INRA (GenESI laboratory) using OFDA 2000 benchtop version on both clean mohair samples on 2 mm fibre snippets cut using a guillotine and greasy samples along the length of greasy mohair staples using the OFDA2000 automatic correction for greasy factor.

## NIR measurements

Fleece samples were scanned using a NIRS portable instrument (LabSpec® 5000; ASD Inc, Boulder, USA) with a reflectance probe (spot size=10 mm). Fleece samples were remained for at least one week under a controlled ambient environment (20 °C, 60 % relative humidity) before scanning. About 10 g of fleece samples were introduced within a Petri dish. Then 4 spectra were collected from each sample with the reflectance probe in the visible (VIS) and near infrared (NIR) region (350-2,500 nm) at 1-nm intervals, to produce a total of 2,151 data points. A standard reference made of Teflon was scanned after each 20-sample interval to correct for changing conditions such as instrument drift.

## Statistical analysis

Spectral data were transformed into an ASCII text format and exported into SAS (Version 9.2) software for multivariate analysis. The mean spectrum of each sample was estimated by averaging the 4 successive scans and stored as the logarithm of the reciprocal of reflectance (log 1/R) and the first derivative of the spectrum.

Principal component analysis (PCA) was firstly performed before partial least squares (PLS) regression models were developed. PCA was used to derive the first 10 principal components from the spectral data, to examine the possible grouping of samples and secondly to detect possible spectral outliers prior to the development of PLS regression models (Cowe & McNicol, 1985). No mathematical treatments or spectral transformation were applied when PCA was performed.

In order to avoid bias, wavelengths below 400 nm in the VIS regions were discarded from the analysis. Two wavelength regions were analyzed: visible plus near infrared (Vis/NIR, 400 to 2,500 nm), and near infrared (NIR, 800 to 2,500 nm). Calibrating equations were determined either by using the reflectance (log1/R) raw spectra or by using the first derivative spectra in order to eliminate the uncontrolled variations of the spectra.

Partial least square regression (PLS) calibration models were determined by cross validation according to the root mean square error of cross-validation in order to determine the optimum number of latent variables. Cross validation were performed by splitting at random the calibration samples into 150 subsets of 100 samples where all samples except 100 were used for calibration while the
remaining ones were used for validation test and the process was repeated until all subset samples were used as validation test once.

The coefficient of determination (R²) in cross-validation, root mean square of the standard error of cross validation (RMSECV), the relative error expressed as the ratio of the residual predictive standard deviation to the reference mean and the ratio performance deviation (RPD) calculated as the ratio of standard error of the laboratory result to the standard error of prediction (RPD=SD/SEP) were selected to evaluate the PLS calibration equations between the chemical analyses and the NIRS estimates. The higher is the coefficient of determination and the lower is the RMSECV, the better is the prediction performance.

Estimations were considered sufficiently accurate and robust to be applied routinely when the relative error was under 5% and the coefficient of determination was greater than 0.91 (Coppa et al., 2010). When the relative error ranges from 5 to 10% and coefficient of determination is greater than 0.82, we advise to use these equations only for analytical purposes. Otherwise equations should be restrained for research and interpreted with caution. An RPD value above 2 indicates good to excellent prediction ability (Moron & Cozzolino, 2004; Nicolai et al., 2007; Pissard et al., 2013).

## Results and discussion

The descriptive statistics for both clean mohair content and fibre diameter of fleece samples are given in Table 1. A wide range of both clean mohair content (range: 52 to 92 %) and fibre diameter (range: 17.83 to 34.89 µm) was observed.

Mean fibre diameter (MFD) was measured using OFDA methodology on both clean fibre snippets according standard method and along the length of greasy mohair staples using the OFDA2000 automatic correction for greasy factor. Descriptive statistics of MFD measurements reported on table 1 show close similar results between both methods.

<table><caption>**Table 1:** Descriptive statistics (number of samples (No), mean, standard deviation (SD, coefficient of variation (CV), minimum and maximum) for clean mohair content and mean fibre diameter (MFD) determined using OFDA2000 on clean snippets and along greasy staple of mohair fleece samples</caption><thead><tr><th>Mohair samples</th><th>No</th><th>mean</th><th>SD</th><th>CV<br>(%)</th><th>Min</th><th>Max</th></tr></thead><tbody><tr><td>Clean content<br>(%)</td><td>397</td><td>74.67</td><td>5.78</td><td>7.74</td><td>52.42</td><td>91.49</td></tr><tr><td>MFD on clean snippet<br>(µm)</td><td>397</td><td>24.16</td><td>2.91</td><td>12.06</td><td>17.42</td><td>34.53</td></tr><tr><td>MFD along greasy staple<br>(µm)</td><td>397</td><td>24.09</td><td>2.90</td><td>12.02</td><td>16.93</td><td>34.89</td></tr></tbody></table>
Figure 1 shows scatter plot of OFDA2000 MFD measurements on clean fibre snippets and along greasy staples using the OFDA2000 automatic correction of the greasy factor using the formula established by the manufacturer after exhaustive analysis of Australian and New Zealand flocks. The relationship between the 2 MFD measurements determined through a simple linear regression had a high coefficient of determination (R²=0.91) and a low relative error (3.6 %). This result agreed previous studies on wool (Baxter, 2001) and could be extend to mohair. MFD measurement along the greasy staple would be advised to determine fibre diameter without any pre-washing and might have a great interest for screening of potential animals in the breeding programme of the French Angora goat.

<figure><img src="image_106.png" /><figcaption>**Figure 1:** Relationship between mean fibre diameter (MFD) measured on clean fibre snippet and along greasy staple</figcaption></figure>

<figure><img src="image_107.png" /><figcaption>**Figure 2:** VIS and NIR mean spectrum of reflectance (Log1/R) of greasy mohair samples (n=397)</figcaption></figure>

Figure 2 shows the mean spectrum expressed as the logarithm of the reciprocal of reflectance (log 1/R) in the VIS and NIR region (400 to 2,500 nm) of the greasy
samples. Reflectance values (log1/R) decreased gradually from 0.7 to 0.45 from the VIS region (400 nm) up to 1,100 nm in the closed NIR region. Thereafter, larger variations were observed up to 2,500 nm with a deep edge in the 1,800-1,900 nm region.

<figure><img src="image_108.png" /><figcaption>**Figure 3:** First derivative of the VIS and NIR spectrum of reflectance (Log1/R) of greasy mohair samples (n=397)</figcaption></figure>

Figure 3 shows the mean first-derivative of the spectrum expressed as the logarithm of the reciprocal of reflectance (log 1/R) in the VIS and NIR region (400 to 2,500 nm) of the greasy samples. The use of the first derivative has eliminated the uncontrolled variations of the spectra. The more interested bands of the NIR region were observed from 1,200 to 1,500 nm, at 1,600-1,700 nm, and thereafter from 1,800 to 2,500 nm. The use of the first derivative of log 1/Reflectance is useful to eliminate the uncontrolled variations of the spectra and to resolve overlapping bands (Mika et al., 2003).

In the present study PLS regression analysis were done through cross-validation procedure and not by separating a pool of samples into independent calibration and validation data sets. It could be discussed but several studies showed that the calibration/validation and cross-validation procedures are equally valid (Shenk & Westerhaus 1993; Coûteaux et al. 2003; Moron & Cozzolino 2004; Ludwig et al. 2008). Thus we decided to use cross-validation because it was difficult to well split samples into homogenous and representative separate calibration and validation sets. The data set used in the present study was representative of both the French Angora goat population and the sampling made each year within the national breeding program as a fleece sampling collection was made once a year on all candidate animals of farms registered to the national selection scheme. But there were a large variability between samples as they were collected on animals of 1 to 3 years of age, of both sexes and issued from 38 different farms (1-43 samples/farm). It is well known that sex, animal age and herd/farm are important factor influencing clean mohair content and mean fibre diameter (Gifford et al., 1990; Lupton et al., 1996; Allain & Roguet, 2003). Another reason for using cross-validation was the number of samples (n=397) selected for our study, which is sufficient for a cross-validation. The cross-validation procedure used in the present
study was done by splitting samples at random into 150 subsets of 100 samples (a quarter of all samples) which were all used as validation test once while other samples were used for calibration.

The statistics of calibration equations for clean mohair content and mean fibre diameter using Vis/NIR and NIR regions are reported in tables 2 and 3 using the raw (log 1/R) and the first derivative of log 1/Reflectance spectra respectively. Low coefficient of determination (R²), high RMSECV and low RPD were observed on both predicted clean mohair content and mean fibre diameter by using the raw Vis/NIR or NIR spectra. The R², RMSECV, and RPD were 0.73, 3.18 % and 1.82, and 0.74, 1.6 µm and 1.83 on clean mohair content and mean fibre diameter respectively using raw Vis/NIR spectra (400 to 2,500 nm) and 0.73, 3.21 % and 1.80 and 0.71, 1.66 µm and 1.75 on clean mohair content and mean fibre diameter respectively using raw NIR (800 to 2,500 nm) spectra (Table 2). Relative error of clean mohair content was below 5 % whatever the wavelength regions: 4.07 and 4.11 % in the Vis/NIR and NIR regions respectively while it was above 5 % for mean fiber diameter: 6.30 and 6.60 % respectively in the Vis/NIR and NIR regions. These results observed on greasy mohair samples were not acceptable to predict clean mohair content and mean fibre diameter using the raw (log 1/R) spectra in both Vis/NIR and NIR regions.

<table><caption>**Table 2:** Calibration statistics for clean fleece content and mean fibre diameter in greasy fleece samples (n=397) using raw (log 1/Reflectance) Vis/NIR (400 to 2,500 nm) and NIR (800-2,500 nm) spectra</caption><thead><tr><th>Trait</th><th>Wavelength regions<sup>a</sup></th><th>CD (R<sup>2</sup>)<sup>b</sup></th><th>RMSEV<sup>c</sup></th><th>Relative error (%)<sup>d</sup></th><th>RPD<sup>e</sup></th><th>T<sup>f</sup></th></tr></thead><tbody><tr><td rowspan="2">Clean content (%)</td><td>Vis/NIR</td><td>0.73</td><td>3.18</td><td>4.07</td><td>1.82</td><td>15</td></tr><tr><td>NIR</td><td>0.73</td><td>3.21</td><td>4.11</td><td>1.80</td><td>15</td></tr><tr><td rowspan="2">Mean fibre diameter (μ)</td><td>Vis/NIR</td><td>0.74</td><td>1.59</td><td>6.30</td><td>1.83</td><td>15</td></tr><tr><td>NIR</td><td>0.71</td><td>1.66</td><td>6.60</td><td>1.75</td><td>14</td></tr></tbody></table>

Higher R², lower RMSECV, higher RDP and lower relative error were observed on clean mohair content in both Vis/NIR and NIR regions by using the first derivative of log (1/Reflectance) spectra. The R², RMSECV, and RPD were 0.80, 2.59 % and 2.14 and 0.81, 2.51 % and 2.21 in the Vis/NIR and NIR regions respectively. Relative error of clean mohair content was 3.52 % and 3.40 % in the Vis/NIR and

<footnote><sup>a</sup> Wavelength regions: Vis/NIR (400-2,500 nm) or NIR (800-2,500 nm);</footnote>

<footnote><sup>b</sup> Coefficient of determination (R²)</footnote>

<footnote><sup>c</sup> Root means square of residual predictive value;</footnote>

<footnote><sup>d</sup> Relative error as ratio of the residual predictive standard deviation to the reference mean;</footnote>

<footnote><sup>e</sup> Ratio performance deviation: ratio of Standard error of laboratory result to the standard error of prediction</footnote>

<footnote><sup>f</sup> Number of partial least square terms (or latent variables) to develop PLS Cross-validation models;</footnote>
NIR regions respectively. On the contrary, the R², REMSECV, RPD and relative error were not improved and remained low for mean fibre diameter by using the first derivative spectra (Table 3).

<caption>**Table 3:** Calibration statistics for clean fleece content and mean fibre diameter in greasy fleece samples (n=397) using the first derivative of the raw (log 1/Reflectance) Vis/NIR (400 to 2,500 nm) and NIR (800-2,500 nm) spectra</caption>

abcdef See footnotes on Table 2

<table><thead><tr><th>Trait</th><th>Wavelength regions<sup>a</sup></th><th>CD (R<sup>2</sup>)<sup>b</sup></th><th>RMSECV<sup>c</sup></th><th>Relative error<sup>d</sup> (%)</th><th>RPD<sup>e</sup></th><th>T<sup>f</sup></th></tr></thead><tbody><tr><td rowspan="2">Clean content (%)</td><td>Vis/NIR</td><td>0.80</td><td>2.59</td><td>3.52</td><td>2.14</td><td>10</td></tr><tr><td>NIR</td><td>0.81</td><td>2.51</td><td>3.40</td><td>2.21</td><td>10</td></tr><tr><td rowspan="2">Mean fibre diameter (μ)</td><td>Vis/NIR</td><td>0.76</td><td>1.48</td><td>5.95</td><td>1.97</td><td>10</td></tr><tr><td>NIR</td><td>0.65</td><td>1.77</td><td>7.18</td><td>1.64</td><td>8</td></tr></tbody></table>

By using the first derivative of log (1/R) spectra, the results obtained in this study shows that calibration models would be considered acceptable to predict clean mohair content but not mean fibre diameter in the French Angora goat. Our results agree with those reported earlier about yield of clean mohair (Larsen & Kininson, 1982; Coleman et al., 1999). Contradictory results were reported about the use of NIRS methodology to predict mean fibre diameter. It was reported that NIRS have potential for rapid analysis of fibre diameter in raw mohair fleeces (Coleman et al., 1999) but not in greasy wool (Hammersley, 1992; Hammersley & Towsend, 2004; Cozzolino et al., 2005). However, NIR spectroscopy seems to have good potential for determining fibre diameter in clean wool samples (Cozzolino et al., 2005).

Near-infrared spectroscopy has potential for rapid analysis of raw mohair fleeces in order to determine clean mohair content. As coefficient of determination between NIR spectra and laboratory values were 0.81 in NIR region with an RPD value higher than 2 and a low relative error (3.4 % in NIR). Figure 4 shows scatter plot of clean mohair content measured according laboratory analysis and NIRS predicted using PLS regression. The relationship between the laboratory and NIRS predicted values had a minor bias with a slope close to 1. NIR spectroscopy would be advised to be used for analytical purposes of clean mohair content (Copa et al., 2010) and might have a great interest for screening of potential animals in the breeding programme of the French Angora goat.
<figure><img src="image_109.png" /><figcaption>**Figure 4:** Relationship of clean mohair content (%) measured in laboratory and near-infrared spectroscopy (NIRS)-predicted clean mohair content</figcaption></figure>

On the contrary, NIR spectroscopy would be unacceptable for measuring mean fiber diameter and should be restrained for research and interpreted with caution. However, according our results MFD measurement along the greasy staple using OFDA2000 methodology allows determination of fibre diameter with a good precision without any pre-washing procedure of fleece samples (Table 1; Figure 1). The use of automatic correction for grease factor using the formula established after exhaustive analysis of Australian and New Zealand flocks could be extended to French Angora goat flocks.

## Conclusion

The objective of this study was to explore the potential use of visible (VIS) and NIR spectroscopy coupled with multivariate statistical tools (partial least squares), to predict mohair quality, i.e. clean mohair content and mean fibre diameter on greasy mohair samples and to test fibre diameter measurement along the greasy staple.

NIR spectroscopy on raw fleece samples is acceptable to predict clean mohair content but not for mean fibre diameter. However OFDA2000 methodology allows determination of fibre diameter along the greasy staple, with a good precision.

It can be concluded that NIR spectroscopy on greasy fleece samples and OFDA mean fibre diameter measurement along the greasy staple, without any pre-washing/cleaning procedure can be widely used to predict mohair quality and to assist the French Angora goat breeding program allowing a large reduced cost of fibre measurements.
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# Variability of Fiber Quality of Chinese Alashan Left Banner White Cashmere Goat

S. Pallotti<fnref n="1" />, J. Wang<fnref n="2" />, P. Tang<fnref n="3" />, M. Antonini<fnref n="4" />, Y. Lou<fnref n="2" />, C. Pieramati<fnref n="5" />, A. Valbonesi<fnref n="1" /> and C. Renieri<fnref n="6" />

**Abstract.** The heritability and the phenotypic and genetic correlations of down weight (DW), down fiber diameter (DFD), and coefficient of variation of the down fiber diameter (CVDFD) of Chinese Alashan Left Banner White Cashmere goat were estimated on 1,375 one year old animals, born in 2009, 2011 and 2013 and bred at the Station for Livestock Improvement of Alashan (Left Banner, Inner Mongolia, P.R. China). For all traits, significant effects were for sex, cohort and sex-cohort interaction (P<0.001). The heritability for DFD and CVDFD was high, 0.41 ± 0.08 and 0.52 ± 0.06 respectively. Heritability for the DW was low (0.12 ± 0.03). Phenotypic correlation calculated by Pearson's coefficient showed that DFD is positively correlated with both CVDFD (0.29 ± 0.07) and DW (0.20 ± 0.05). The phenotypic correlation between CVDFD and DW was negative (- 0.11 ± 0.06). The genetic correlations between DW and CVDFD and between DFD and CVDFD were both high and positive (0.63 ± 0.16 and 0.39 ± 0.1, respectively) while the DW showed a negative genetic correlation with DFD (-0.27 ± 0.2). Our results suggest that the selection for reducing DFD and its CVDFD is possible and a genetic progress can be achieved quickly in the Chinese Alashan Left Banner White Cashmere goat.

**Resumen.** Se estimó la heredabilidad y las correlaciones fenotípicas y genéticas del peso inferior (DW), el diámetro de fibra inferior (DFD) y el coeficiente de variación del diámetro de fibra inferior (CVDFD) en 1.375 cabras Cashmere Alashan Left Banner White de China de un año de edad nacidas en 2009, 2011 y 2013 en la Estación para el Mejoramiento Ganadero de Alashan (Left Banner, Inner Mongolia, R.P.China). Los efectos significativos fueron el sexo, la cohorte y la interacción sexo-cohorte (P <0,001) para todos los carac-

<footnote n="1">¹University of Camerino, School of Bioscence and Veterinary Medicine, Via Gentile III da Varano s/n, 62032 Camerino, Italy
E-Mail: stefano.pallotti@unicam.it</footnote>

<footnote n="2">²Jilin Agricultural University, Xin Cheng 2888, 130118 Chang Chun, P.R. China</footnote>

<footnote n="3">³Station for Livestock Improvement of Alashan, Alashan Zoogi, 75030 Inner Mongolia Autonomous Region, P.R. China</footnote>

<footnote n="4">⁴ENEA UTAGRI, Via Anguillarese, Roma, Italy</footnote>

<footnote n="5">⁵University of Perugia, Veterinary Medicine Department, Piazza San Costanzo 4, 06100 Perugia, Italy</footnote>

<footnote n="6">⁶University of Camerino, School of Pharmacy, Via Gentile III da Varano s/n, 62032 Camerino, Italy</footnote>
teres. La heredabilidad de DFD y CVDFD fue alta, 0,41 ± 0,08 y 0,52 ± 0,06 respectivamente. La heredabilidad de DW fue baja (0.12 ± 0.03). El coeficiente de correlación fenotípica de Pearson mostró que DFD está correlacionado positivamente con CVDFD (0,29 ± 0,07) y DW (0,20 ± 0,05). La correlación fenotípica entre CVDFD y DW fue negativa (- 0,11 ± 0,06). Las correlaciones genéticas entre DW y CVDFD y entre DFD y CVDFD fueron altas y positivas (0,63 ± 0,16 y 0,39 ± 0.10, respectivamente), mientras que DW mostró correlación genética negativa con DFD (-0,27 ± 0,20). Nuestros resultados que es posible seleccionar simultáneamente para reducir DFD y CVDFD, y que se puede lograr un progreso genético rápidamente en la cabra Cashmere Alashan Left Banner White de China.

**Keywords:** Cashmere, Alashan, goat, heritability, genetic correlation

**Introduction**

This paper contains the results of the research on the variability of fiber quality on Chinese Alashan Left Banner White Cashmere goat carried out at the Italian University of Camerino in collaboration with the Jilin Agricultural University, the station for Livestock Improvement of Alashan and the Italian University of Perugia. The results are published in Pallotti et al. (2018).

Cashmere is the fine downy-soft winter undercoat found on many goats. Cashmere has a fine texture, and is light yet strong. When it is made into garments, cashmere is extremely warm, much warmer than the equivalent weight in sheep wool.

The U.S. Wool Products Labeling Act of 1939, as amended (U.S.C. 15 Section 68b (a) defines cashmere as the fine (dehaired) undercoat fibers produced by cashmere goat (Capra hircus l.). The average diameter of the fibers must not exceed 19 microns and contain no more than 3% (by weight) of cashmere fibers with average diameters exceeding 30 microns (Cashmere and Camel Hair Manufactures Institute, 2008).

China is the world's main source of cashmere goats, and has recently become the leading purchaser and processor of cashmere produced in other Asian countries.

In the Domestic Animal Diversity Information System hosted by FAO (http://dad.fao.org/) four Chinese cashmere goat breeds are described (Inner Mongolian Cashmere, Liaoning Cashmere, Hexi Cashmere and Shanbei White Cashmere) reared in Liaoning, Inner Mongolia, Xinjiang and Tibet provinces. For the Inner Mongolia cashmere breed many subpopulations are described (Di et al. 2011), which differ in color (pure white or colored) and quality of cashmere (Li et al. 2004). Generally these types are bred without genetic relationship between them in isolated areas.
In the past years, the genetic admixture with breeds like Liaoning and Inner Mongolia Arbas cashmere selected for increased body weight and low weight of the animals, have led to the loss of fineness and homogeneity of fiber.

Nowadays, one of the more genetically preserved populations is the Left Banner Alashan White, which produced very fine cashmere (Bai et al. 2006). Nevertheless, the influence of Liaoning and Arbas goats is now in progress also in Banner, leading to a reduction in fiber quality. In fact, fiber diameter is becoming coarser.

A genetic project coordinated by the Station for Livestock Improvement and supported by the Chinese Agricultural University of Jilin and some Italian public and private institutions (University of Camerino, ENEA and the Loro Piana S.p.A. textile industry) started in 2009 in Alashan Left Banner. The purpose of this project was to estimate the genetic parameters for the production traits of the Left Banner Alashan White Cashmere goat. The traits included are: down weight (DW), down fiber diameter (DFD) and coefficient of variation of down fiber diameter (CVDFD).

## Material and methods

From 2009 to 2013 data were collected from 1,375 one year old goats, born in 2009 (1st cohort), 2011 (2nd cohort) and 2013 (3rd cohort). The structure of the sample is given in table 1.

<table><caption>**Table 1:** Sample structure</caption><thead><tr><th>Sex</th><th>Year</th><th>Cohort</th><th>Number of animals</th></tr></thead><tbody><tr><td rowspan="3">Bucks</td><td>2009</td><td>1</td><td>270</td></tr><tr><td>2011</td><td>2</td><td>185</td></tr><tr><td>2013</td><td>3</td><td>79</td></tr><tr><td rowspan="3">Does</td><td>2009</td><td>1</td><td>341</td></tr><tr><td>2011</td><td>2</td><td>312</td></tr><tr><td>2013</td><td>3</td><td>188</td></tr></tbody></table>

The herd was located in the Station for Livestock Improvement of Alashan (latitude 38°24' N and longitude 104°42' E), Left Banner, a semi-desert steppe area of the Inner Mongolia (P.R. China). Fleece samples from the mid side of each animal were collected during the first combing. The samples were dehaired, washed and analyzed in the Loro Piana Metrology Laboratory in Beijing, certified according to the international requirements of the WTO. Analysis of the DFD and the CVDFD were carried out using an OFDA 100, measuring thousands of fiber for each sample. The DW was recorded directly by the laboratory assistants.

Software package SPSS 12.0 was used to determine the effect of sex, cohort and their interaction on the traits. The same software was also used for the computation of phenotypic correlations calculated by Pearson's correlation coefficient.
Heritability and genetic correlation were estimated using the MTDFREML program (Boldman et al. 1995) with a criterion for convergence set at $10^{-6}$ and sex and age included as fixed effect for each trait. Standard errors of heritability were estimated using the VCE6 package (Neumaier and Groeneveld, 1998).

## Results and Discussion

As showed in the table 2, the average DW values for bucks of the 1st, 2nd and 3rd cohorts was 501.72 g, 514.49 g and 424.11 g respectively. Lower DW values were recorded for does with a value of 436.69 g, 487.74 g and 404.47 g for the 1st, 2nd and 3rd cohort respectively.

The average DFD values for the 1st, 2nd and 3rd cohorts ranged from 14.63 µm to 14.27 µm for the bucks. The does showed slightly thicker fiber with DFD values ranging from 14.49 µm to 15.75 µm. The average CVDFD values for the 1st, 2nd and 3rd cohorts for the bucks ranged from 27.09 % to 29.39 % showing less variation compared to does were CVDFD ranged from 27.64 % to 41.39 %.

The basic statistical analysis results indicating the potential of the Left Banner Alashan White Cashmere goat showed higher results for bucks in terms of yield, fineness and homogeneity of fleece. The ANOVA showed a significant effect (P<0.001) of sex, cohort and the interaction between sex and cohort on the three traits studied (Table 3).

<table><caption>**Table 2:** Average values for the down weight, the down fiber diameter and the coefficient of variation of down fiber diameter</caption><thead><tr><th>Trait</th><th>Cohort</th><th>Bucks<br>Mean</th><th>SD</th><th>Cohort</th><th>Does<br>Mean</th><th>SD</th></tr></thead><tbody><tr><td rowspan="3">Down weight (g)</td><td>1</td><td>501.72</td><td>120.50</td><td>1</td><td>436.69</td><td>120.41</td></tr><tr><td>2</td><td>514.49</td><td>132.62</td><td>2</td><td>487.74</td><td>138.04</td></tr><tr><td>3</td><td>424.11</td><td>73.02</td><td>3</td><td>404.47</td><td>61.74</td></tr><tr><td rowspan="3">Down fiber<br>diameter (µm)</td><td>1</td><td>14.63</td><td>0.93</td><td>1</td><td>14.49</td><td>1.09</td></tr><tr><td>2</td><td>14.27</td><td>0.75</td><td>2</td><td>15.01</td><td>0.77</td></tr><tr><td>3</td><td>14.59</td><td>0.67</td><td>3</td><td>15.75</td><td>0.95</td></tr><tr><td rowspan="3">Coefficient of<br>variation of<br>down fiber<br>diameter (%)</td><td>1</td><td>27.09</td><td>3.78</td><td>1</td><td>27.64</td><td>5.84</td></tr><tr><td>2</td><td>29.39</td><td>4.39</td><td>2</td><td>41.39</td><td>8.51</td></tr><tr><td>3</td><td>28.52</td><td>5.02</td><td>3</td><td>36.50</td><td>9.28</td></tr></tbody></table>
<table><caption>**Table 3:** Anova for the down weight, the down fiber diameter and the coefficient of variation of down fiber diameter</caption><thead><tr><th>Trait</th><th>Source of variation</th><th>df</th><th>Mean Square</th><th>F</th><th>P-value</th></tr></thead><tbody><tr><td rowspan="3">Down weight (g)</td><td>Sex</td><td>1</td><td>373,731.02</td><td>26.74</td><td>&lt;0.001</td></tr><tr><td>Cohort</td><td>2</td><td>569,320.45</td><td>40.74</td><td>&lt;0.001</td></tr><tr><td>Sex x Cohort</td><td>2</td><td>67,062.43</td><td>4.80</td><td>&lt;0.001</td></tr><tr><td rowspan="3">Down fiber diameter (µm)</td><td>Sex</td><td>1</td><td>104.26</td><td>126.08</td><td>&lt;0.001</td></tr><tr><td>Cohort</td><td>2</td><td>37.35</td><td>45.16</td><td>&lt;0.001</td></tr><tr><td>Sex x Cohort</td><td>2</td><td>48.17</td><td>58.24</td><td>&lt;0.001</td></tr></tbody></table>

As reported by the basic statistical analysis results, bucks showed highest performance in terms of fiber quality. These differences between the two genders may reflect the physiological mechanisms that affect fleece production performance as proposed by Wang et al. (2013).

The differences in weather condition, rainfall and grazing during the five years of the study may explain the effect of cohort in the traits studied. This non genetic factor affected fiber production in other goat breeds as reported for the Inner Mongolia cashmere goat (Zhou et al. 2003) and for the Angora goats (Allain et Roguet, 2003).

As showed in the Table 4 the heritability was low for the DW and high for the DFD with values of 0.12 and 0.41 respectively. Of the three traits studied in this paper the CVDFD had the highest heritability with a value of 0.59. In our study, the low heritability value for DW differs from those reported for the Inner Mongolia cashmere goat (Zhou et al. 2002) and for the Arbas strain (Bai et al. 2006) where the heritability was found to be moderate with values of 0.28 and 0.30 respectively. A moderate heritability of DW (0.35) was also found for the Liaoning cashmere goat in a study by Ning et al. (2005). For the DFD we found an heritability value similar to those reported from previous studies on Arbas strain and Liaoning breed (Zhou et al. 2002; Bai et al. 2006; Ning et al. 2005, Wang et al., 2013 and 2015) in which the value was moderate ranging from 0.28 to 0.42.

The DW showed negative genetic correlation with DFD (-0.27) while was highly genetically correlated with CVDFD with a correlation coefficients of 0.63. The genetic correlation between DFD and CVDFD was moderate with a value of 0.39.

The phenotypic correlation of DW was positive for DFD (0.20) and negative and not statistically significant for CVDFD (-0.11) while DFD showed moderate phenotypic correlation with CVDFD with values of 0.29.
The negative genetic and positive phenotypic correlation between DW and DFD from our study are in disagreement with the correlations estimated by Bai et al. (2006) and Wang et al., (2013; 2015), which are both positive.

<table><caption>**Table 4:** Heritability (bold), genetic correlations (above diagonal) and phenotypic correlations (below diagonal) for the fiber traits</caption><thead><tr><th>Trait</th><th>Down weight</th><th>Down fiber diameter</th><th>CVDFD</th></tr></thead><tbody><tr><td>Down weight</td><td><strong>0.12 ± 0.03</strong></td><td>-0.27 ± 0.20</td><td>0.63 ± 0.16</td></tr><tr><td>Down fiber diameter</td><td>0.20 ± 0.05</td><td><strong>0.41 ± 0.08</strong></td><td>0.39 ± 0.10</td></tr><tr><td>CVDFD</td><td>-0.11 ± 0.06</td><td>0.29 ± 0.07</td><td><strong>0.52 ± 0.06</strong></td></tr></tbody></table>

However, the largest differences between our estimates of genetic parameters and those found in other works may be due to the differences in genetic structure between the breeds. Differences in the sample size, the definitions of the traits, the models used for analysis, and the environments to which the populations are subjected may also contribute to these differences (Zhou et al. 2003).

According to our results, in the Chinese Alashan Left Banner White Cashmere goat the selection for reducing DFD and its CVDFD is possible and the genetic progress can be achieved quickly. Both traits have high heritability and high positive genetic and phenotypic correlations, therefore selection based on phenotypic values will lead to a genetic improvement of these two traits. Otherwise, the direct involvement of DW on selection appears not useful due to his low heritability.

## Conclusion

In Alashan Left Banner White Cashmere goat the genetic parameters are favorable for selection of homogeneous and fine fleece while the selection for yield in cashmere would lead to a slow genetic improvement of the trait.

Our data make an addition to understanding the genetics of cashmere fiber production in Alashan Left Banner White Cashmere goat and provide a basis for the development of the efficient genetic selection plan.

**Acknowledgments.** The authors would like to thank the Loro Piana S.r.l. for their financial support.

## References

Allain, D. and Roguet, J. M. 2003, Genetic and nongenetic factors influencing mohair production traits within the national selection scheme of Angora goats in France. Livestock Production Science, 82.2, 129-137.
Bai, J. Y., Li, J. Q., Jia, X. P., Zhang, Q., & Dao, E. J. 2006, Influence of maternal genetic effect on genetic parameter estimates of production traits of cashmere goat. Yi chuan. 28, 1083-1086.

Bai, J., Zhang, Q., Li, J., Dao, E., & Jia, X. 2006, Estimates of genetic parameters and genetic trends for production traits of Inner Mongolian White Cashmere goat. Asian-australasian journal of animal sciences, 19, 13.

Boldman, K., Kriese, L. A., Van Vleck, L. D., Van Tassell, C. P., & Kachman, S. D. 1995, A manual for use of MTDFREML. A set of programs to obtain estimates of variance and covariances (Draft). USDA, ARS, Lincoln, NE.

Di, R., Farhad Vahidi, S. M., Ma, Y. H., He, X. H., Zhao, Q. J., Han, J. L., ... & Pu, Y. P. 2011, Microsatellite analysis revealed genetic diversity and population structure among Chinese cashmere goats. Animal Genetics, 42.4, 428-431.

Li, M. H., Li, K., and Zhao, S. H. 2004, Diversity of Chinese indigenous goat breeds: a conservation perspective-A review. Asian-australasian journal of animal sciences, 17, 726-32.

Ning, M. A., Li, Y. J., Song, Y. Q., Lou, Y. J., Son, X. C. 2005, Estimates of Genetic Parameters of Main Economic Traits in Liaoning Cashmere Goat. Journal of Jilin Agricultural University, 27: 446-448.

Neumaier, A., & Groeneveld, E. 1998, Restricted maximum likelihood estimation of covariances in sparse linear models. Genetics Selection Evolution. 30(1), 3-26.

Pallotti, S., Wang, J., Tang, P., Antonini, M., Lou, Y., Pieramati, C., Valbonesi, A. & Renieri, C. 2018, Variability of fibre quality on Chinese Alashan Left Banner White Cashmere goat. Italian Journal of Animal Science, 17(1), 53-56.

Wang, Z., Wang, R., Zhang, W., Wang, Z., Wang, P., Liu, H., ... & Zhang, Y. 2013, Estimation of genetic parameters for fleece traits in yearling Inner Mongolia Cashmere goats. Small Ruminant Research 109(1), 15-21.

Wang, Z., Wang, Z., Liu, Y., Wang, R., Zhang, Y., Su, R., & Li, J. 2015, Genetic evaluation of fiber length and fiber diameter from Inner Mongolia White Cashmere goats at different ages. Small Ruminant Research. 123(1), 22-26.

Zhou, H. M., Allain, D., Li, J. Q., Zhang, W. G., & Yu, X. C. 2003, Effects of non-genetic factors on production traits of Inner Mongolia cashmere goats in China. Small Ruminant Research. 47, 85-89.

Zhou, H. M., Allain, D., Li, J. Q., Zhang, W. G., & Yu, X. C. 2002, Genetic parameters of production traits of Inner Mongolia cashmere goats in China. Journal of Animal Breeding and Genetics, 119, 385-390.
<figure><img src="image_110.png" /></figure>
# Effects of Year and Sampling Site on Mean Fibre Diameter of Alashan Cashmere Goat

Antonini M.<fnref n="1" />, Wang J.<fnref n="2" />, Lou Y.<fnref n="2" />, Tang P.<fnref n="3" />, Renieri C.<fnref n="4" />, Pazzaglia I.<fnref n="4" />, Valbonesi A.<fnref n="4" />

*Corresponding author:* Irene Pazzaglia. Email: irene.pazzaglia@unicam.it

**Abstract.** Fourteen female Alashan white cashmere goats were investigated for fibre fineness (diameter) and coefficient of variation of fineness (CV). The investigation focused on the same animals combed at 1, 3 and 4 years of age. Fibre of the animals was collected from 10 different body areas. A statistically significant effect was observed for both, year of collection, and body areas. The present paper suggests that the fibre of one-year old animals should be kept separately from older ones and likewise, fibre from upper parts of the body should be separated from the others.

**Resumen.** Se estudiaron catorce cabras Cashmere Alashan de capa blanca para determinar la finura de su fibra (diámetro) y su coeficiente de variación (CV). Todas las muestras procedían de los mismos animales tomadas a los 1, 3 y 4 años de edad, obteniendo fibras de 10 diferentes áreas corporales. Tanto el año de recolección como el área corporal mostraron efecto estadísticamente significativo. Este trabajo sugiere que deberían tratarse por separado las fibras de los animales de un año de las de animales adultos, así como las fibras obtenidas de la región superior del cuerpo de las del resto.

**Keywords:** Cashmere goat, Alashan, age, body areas

<footnote n="1">¹Italian National Agency for new Technology, Energy and Sustainable Economic Development, ENEA UTAGRI Inn CR Casaccia, Roma, Italy</footnote>

<footnote n="2">²College of Animal Science and Technology, Jilin Agricultural University, Changchun, 130118, China</footnote>

<footnote n="3">³Livestock Improvement Station of Alashan, Inner Mongolia Autonomous District, Alashan Left Banner, 750300, China</footnote>

<footnote n="4">⁴School of Bioscience and Veterinary Medicine, University of Camerino, Italy</footnote>
**Introduction**

China is the largest producer of cashmere by far, and Alashan white cashmere goats are famous for the quality of their fibre (http://www.naturalfantasy.it). Together with homogeneity and length of cashmere fibres (Schneider, 2010), fineness is one of the most important characteristics for spinnability and value of textile products (Allain and Renieri, 2010; McGregor, 2006). In animal fibre producers, the diameter seems to be affected by both, body areas and age (Antonini et al., 2004; Aylan-Parker and McGregor, 2002; McGregor et al., 2011; Tabbaa et al., 2001; Taddeo et al., 2000). Yet, breeders comb cashmere on the whole body of goats, and cashmere from animals of different ages is collected in the same bag, thus reducing the value of cashmere fibre. The aim of this paper is therefore, to promote a new method for fleece collection which may lead to obtaining more fineness and homogeneous cashmere lots.

**Materials and methods**

Fourteen female Alashan cashmere goats, born in 2008 at the Animal Improvement Station of Alashan Left Banner, were randomly selected. The farm is located in the territory of Jilantai, in Alashan Left Banner, a semi-desert steppe environment. Selected goats were sampled and weighed at 1, 3 and 4 years of age since May 2009. The cashmere fibre was collected from 10 areas of the goats right body side (Fig. 1) and analysed only for the undercoat. An average of 8,850 fibres for each sample, were analysed by OFDA 100. Investigations were conducted on fibres' diameter and CV. Pearson's correlation coefficients between body weight, diameter and CV, were calculated at different ages. As a significant correlation between the body weight and the other two variables was not observed throughout the whole period of investigation, we disregarded this variable in the "analysis of repeated measures procedure" (Landau and Everitt, 2004), which was aimed at detecting the effects of age and body parts on the fibre parameters investigated. Once it was determined that differences in age and body areas do exist among the means of parameters investigated, pairwise multiple comparisons were used to determine which means differed, as per Hochberg's GT2 significant difference test. Statistical analyses were carried out with SPSS12.0 software.
<figure><img src="image_111.png" /><figcaption>**Figure 1:** Sampling areas of the goat body</figcaption></figure>

## Results

There were significant differences between fibre diameters of 15.6 µm (sd = 0.64), 17 µm (sd = 0.99) and 16.4 µm (sd = 0.89) for 2009, 2011 and 2012, respectively (F = 16.84; P<0.001). Also differences in body weight were found with 20.21 kg (sd = 0.72), 25.68 kg (sd = 0.65) and 27.0 kg (sd = 0.99) for 2009, 2011 and 2012, respectively. Here, body weight did not show homogeneous correlations with the other two characters as presented in table 1.

<table><caption>**Table 1:** Pearson correlation coefficients for body weight (BD), fibre diameter (FD) and the related CV. Coefficients were calculated at 1 (2009), 2 (2011) and 4 (2012) years of age</caption><thead><tr><th rowspan="2">Year</th><th colspan="2">2009</th><th colspan="2">2011</th><th colspan="2">2012</th></tr><tr><th>FD</th><th>CV</th><th>FD</th><th>CV</th><th>FD</th><th>CV</th></tr></thead><tbody><tr><td>BD</td><td>0.351*</td><td>-0.123</td><td>0.532*</td><td>0.687*</td><td>-0.003</td><td>0.382*</td></tr></tbody></table>

<footnote>* Correlation significant at p = 0.01</footnote>
Significant differences were also observed among the 10 different body areas (F=27.01; P<0.001) for fiber diameter and CV. The pairwise multiple comparisons method identified three homogeneous groups: the first included the areas 3, 5, 1, 2, 6, 10 and 7, with lower finesses ranging from 15.7 µm up to 16.3 µm; the second included the areas 6, 10, 7, 4 and 9, with intermediate fineness from 16.2 µm up to 16.9 µm and the third included the areas 4, 9 and 8 with coarser fibres from 16.5 µm up to 17.1 µm.

Correspondingly, the CV with an average of 26.22 % (sd=4.03), 31.16 % (sd=10.79) and 30.71 % (sd=8.26), for 2009, 2011 and 2012 respectively, proved to be significantly different (F=18.53; P<0.001). Besides, differences were observed also among the 10 different body areas (F=5.75; P<0.001). The pairwise multiple comparison method identified two homogeneous groups: the first group included the areas 1, 2, 3, 7, 5, 4, 6, 8 and 10 with lower CV ranging from 25.38 % up to 31.76 %, and the second group included the areas 6, 8, 10, and 9, with higher CV, from 30.41 % up to 35.77 %.

## Discussion

The results of this investigation indicated a strong and significant effect of both, the animals' age and its body areas on the diameter of cashmere fibres, thereby partially confirming the results of a previous study (McGregor et al., 2011). Animals combed at one year old showed a better diameter (on average < 1.11 µm) and a major homogeneity (on average CV<4.71 %) when compared to the animals combed at 3 and 4 years of age. The ten different body areas, according to the fibre diameter, can be categorized into three different groups. The first includes areas from the upper part of croup and the thorax (areas: 3, 1, 2, and 5); the second includes neck, shoulder, thigh and anterior legs (areas: 7, 10, 6, and 4) and the third includes hind leg and belly (areas: 8 and 9). The areas of the first group are considered best, as they show on average: i) a diameter of 15.89 µm (sd=0.14) vs 16.32 µm (sd=0.14) and 16.98 µm (sd=0.18) of second and third group, respectively, ii) a CV of 25.58 % (sd=0.29) vs. 28.67 % (sd=2.46) and 32.93 % (sd=4.01) of second and third group, respectively.

## Conclusion

The present results suggest collecting cashmere in a rational way: i) for age, combing first the younger goats and then the older ones and ii) for body areas, keeping the fibre of the upper body parts separately from those of the other parts of the body. Moreover, utilizing this method, the farmers will obtain batches with lower contamination because the first combed areas are generally cleaner and finer than areas that are more contaminated by both vegetable matter and excrements.
References

Allain, D., Renieri, C., 2010. Genetics of fibre production and fleece characteristics in small ruminants, Angora rabbit and South American camelids. Animal 4, 1472-1481.

Antonini, M., Gonzales & M., Valbonesi, A., 2004. Relationship between age and postnatal skin follicular development in three types of South American domestic camelids. Livestock Production Science 90, 241-246.

Aylan-Parker, J. & McGregor, B. A., 2002. Optimising sampling techniques and estimating sampling variance of fleece quality attributes in alpacas. Small Ruminant Research 44, 53-64.

Characteristics and qualities of the Cashmere fibre originating from the People's Republic of Mongolia from http://www.naturalfantasy.it/.

Landau, S. & Everitt, B.S., 2004. A handbook of statistical analyses using SPSS, 1-354. Chapman & Hall/CRC, New York Washington, D.C.

McGregor, B. A., 2006. Production, attributes and relative value of alpaca fleeces in southern Australia and implications for industry development. Small Ruminant Research 61, 93-111.

McGregor, B. A., Kerven, C. & Toigonbaev, S., 2011. Sources of variation affecting cashmere grown in the Pamir mountain districts of Tajikistan and implications for industry development. Small Ruminant Research 99, 7-15.

Schneider, G. S., 2010. Market Indicators. Retrieved on 24.08.10 from http://www.gschneider.com/.

Tabbaa, M.J., Al-Azzawi & W.A., Campbell, D., 2001. Variation in fleece characteristics of Awassi sheep at different ages. Small Ruminant Research 41, 95-100.

Taddeo, H.R., Duga, L., Almeida, D., Willem, P. & Somlo, R., 2000. Variation of mohair quality over the body in Angora goats. Small Ruminant Research 36, 285-291.
<figure><img src="image_112.png" /></figure>
Abstracts

<figure><img src="image_113.png" /></figure>
<figure><img src="image_114.png" /></figure>
# Sustainable Cashmere, Pastoralism, and
Coexistence with Predators in Europe

N. Kravis

The creation of a European model of SUSTAINABLE CASHMERE produced by
cashmere goats born and raised in Italy. Economic, environmental, energetic,
occupational and socio-political sustainability are examined, as well as the fiber
characteristics that define the process of genetic selection practiced since 1995.
Land management, biodiversity, and animal welfare in the European community
are dependent on pastoralism: the essential link between intensive farming and
abandonment of marginal agricultural land. The effect of wolf protection and
consequent increase of the density of predators in many European countries has
had major repercussions on pastoralism and extensive livestock management. The
practice of non-lethal predator control (“PREDATOR FRIENDLY FARMING”)
is essential to create and maintain a sound ecological equilibrium. But still, much
needs to be done at a political level in order to assist the shepherds and to make it
viable on a larger scale.
# Efecto de la precipitación pluvial en la seja de selva y la zona alto andina de la región Puno sobre la producción ganadera de altura

Pineda B., Zeballos J., Mamani R. and Huanca T.

Instituto Nacional de Innovación Agraria (INIA) – Perú

El cambio climático se define como una modificación identificable y persistente del estado del clima por variabilidad natural o por efecto de la actividad humana. La zona altoandina se encuentra por encima de los 4,000 msnm (piso puna) abarca el mayor porcentaje de la superficie y se caracteriza por su alta vulnerabilidad a fenómenos climáticos adversos. La precipitación pluvial en la ceja de selva tomando como referencia al mes de agosto en promedio es de 76.3 mm incrementándose en los meses de lluvia y la zona altoandina en promedio es de 18.5 mm y de forma irregular. El año 2016 se caracterizó por una severa sequía que no superó los 350 mm de precipitación pluvial, el seguimiento de 15 unidades productivas de comunidades campesinas nos permitió determinar que el número de afecciones dentro del hato (animales enfermos y muertos) llego hasta 11.34 % en los adultos y 35.12 % en las crías en comparación con año un normal (2012) y esta se debió a la escases de pastos y agua que afectó a las madres lactantes y en gestación. El porcentaje de abortos en alpacas llegó hasta 33.5 % y en llamas hasta 18.21 % en comparación al promedio general en adultos que no supera el 2 % en un año normal. La aparición de enfermedades infecciosas en alpacas crías llegó hasta un 27.70 % en diarreas y en los adultos hasta un 24.50 % como la fiebre de las alpacas. Se concluye que una baja precipitación pluvial tiene un efecto negativo sobre la producción y productividad de las alpacas y llamas en la zona alto andina, no siendo manifiesto en la zona de ceja de selva.
# Evaluation of Population and Social Composition of Vicunas (*Vicugna vicugna*) in Different Environment Sites of the Laguna Blanca Biosphere Reserve (Catamarca, Argentina)

Riva de Neyra, L. A.<fnref n="1" />,<fnref n="2" />, Hick, M.V.H.<fnref n="1" />,<fnref n="3" /> and Frank, E. N.<fnref n="1" />,<fnref n="3" />

The wild vicuna is an important resource for the Laguna Blanca Reserve, where capture and shearing for the sustainable use of its fiber is practiced. The objective of this study was to evaluate population variables of vicunas in eight different vegetation communities of the reserve. Vicuna counts were conducted by direct observation in communities of shrub steppes (2), herbaceous steppes (2), and waterfowl meadows (marshes) (4) during April 2013. Relative abundance (I) (observations/time), percentages of family group (% FG), single males (% SM) and number of offspring (No. Off.) were determined. Regarding FG, we determined Family Group Size (FGS) and Male:Female offspring ratio. The % FG and FGS were assessed on the basis of statistical evidence (Student's T-test) of non-compliance with the FG standard ≥60 and FGS≥6. MFOr was assessed on the basis of statistical evidence (χ2 goodness test) of non-compliance with MFOr standard ≠ 1: 4: 2. The largest number of vicunas was recorded in the steppes (shrubs and herbaceous) (113) as well as the No. Off. (19). In the environments of herbaceous steppes, greater % FG was observed, and in the bushes steppes greater % SM. Good values of I in herbaceous and shrub steppes were obtained, but in marsh environments no vicunas were reported. It is concluded that environments shaped by shrubs and herbaceous steppes meet at least two of the three population attributes. In marshes, despite being the best communities, they did not meet any attributes. The absence of vicunas may be due to the presence of domestic livestock on these sites.

<footnote n="1">¹Universidad Nacional de La Rioja – Sede Chamical</footnote>

<footnote n="2">²EEA Chilecito (INTA)</footnote>

<footnote n="3">³IRNASUS-CONICET, Universidad Católica de Córdoba</footnote>
# Animal Welfare Problems in South American Camelids Kept in Europe

Gauly, M.

Department of Livestock Sciences, Free University of Bolzano, 31000 Bolzano, Italy

Since the beginning of the 1980s, lamas and alpacas have been increasingly used as pets, companion and recreational animals in various European countries. They are often kept in smaller herds (2 to 8 animals), which underlines the hobby character. A few breeders are aiming at an agricultural use of the animals. The legal basis for keeping domesticated camelids (llamas and alpacas) is in most countries the Animal Protection Law and in addition, in the case of farming, specific regulations for farm animals. Only in some countries, specific regulations are available for South American Cameilds (SACs). SACs are herd animals. Therefore group housing with at least two animals is required. Exceptions are sexually mature males. However even they, if kept alone, must have at least visual contact with the herd. The majority of SACs kept in Europe are on pasture from April to November, which is good from an animal welfare point of view if minimal requirements are fulfilled. SACs older than 6 months, need at least 1000 m² area for the first two animals. Each additional animal needs about 100 m² more. SACs are “distance animals”. If possible, they avoid direct contact to each other. This must be taken into account, in particular, in the design of stables and shelters. Because of the small herd size and their use as pets, they are in close contact with humans. This may lead to miss behaviour (Berserk-Male syndrome), especially if this is practiced during the early life of the cria. Several typical welfare problems are discussed in the presentation.
# Breeding Objectives for Alpacas of the Highlands Central of Peru

Candio, J.R.¹ and Gutiérrez, G.A.²

¹Sheep and camelids program (POCA). Universidad Nacional Agraria La Molina. VLIR-UNALM PARTNER PROGRAMME. Av. La Molina S/N. La Molina, Lima 12, Peru.

E-Mail: jcandio@lamolina.edu.pe

²Animal Breeding Program (PMA). Universidad Nacional Agraria La Molina – UNALM. Av. La Molina S/N. La Molina, Lima 12, Peru.

E-Mail: gustavogr@lamolina.edu.pe

The aim of this study was to determine the breeding objectives for alpacas. The study was carried out in the communal cooperative San Pedro de Racco located in the region of Pasco-Peru and the records of 2933 alpacas were evaluated during the period 2006-2012. The determination of the breeding objectives, profit equation and economic values was made based on Ponzoni (1986), Tolone et al. (2011), Alfonso et al. (2012) and Borg et al. (2007). The breeding objective was determined assuming the following economic scenario: Sale of white alpaca fiber with flat price, sale of alpacas for meat and sale breeding animals. The profit equation formulated was:

$$EC2 = NM \times TN \times SV (PVL1 \times pf + P1E \times pcb \times 0.43 + (DF1E + DS + RZ + BG) \times pp \times 0.2 - ct) + (NM + NP) (PVL \times pf + PV \times pcb \times 0.2) + NP ((DF + DS + RZ + BG) \times pp \times 0.1) - NM \times cm - NP \times cp$$

Where the characters were survival at the 1st shear (SV), diameter of fiber at the 1st shear (DF1E), weight of fleece at the 1st shear (PVL1), weight at the 1st shear (P1E), diameter fiber (DF), fleece weight (PVL), live weight (PV). The visual evaluation characters of fiber were general balance (BG), density (DS) and curls (RZ). The economic value of SV, DF1E and P1E was S/. 411.18, S/. 3.86 and S/. 1.10 soles per alpaca mother respectively. The economic value for DS, RZ and BG was S/. 0.24 soles per alpaca mother, being minimal in comparison to the other characters evaluated. The breeding objective determined was:

$$H2 = 411.18 \times GSV + 3.86 \times GDF1E + 4.92 \times GPVL1 + 1.10 \times GP1E + 0.24 \times GDF + 8.26 \times GPVL + 0.86 \times GPV + 0.24 \times GDS + 0.24 \times GRZ + 0.24 \times GBG$$

Where: GSV, GDF1E, GPVL1, GP1E, GDF, GPVL, GPV, GDS, GRZ, GBG, are the genetic additive values of the characters studied. It is concluded, that the production traits SV, PVL, PV, DF, DF1E, P1E y PVL1 are of greater economic importance than the visual evaluation characters BG, DS and RZ. Therefore the production traits must be included in the breeding objectives for the breeding of alpacas.
# Vicugna Pacos As1-Casein: Identification of New Polymorphisms at the Csn1s1 Gene

Erhardt, G.<fnref n="1" />, Gu, M.<fnref n="2" />, Wagner, H.<fnref n="3" />, Di Stasio, L.<fnref n="2" /> and Pauciullo, A.<fnref n="1" />,<fnref n="2" />

E-Mail: georg.erhardt@agrar.uni-giessen.de

E-Mail: alfredo.pauciullo@unito.it

E-Mail: henrik.w.wagner@vetmed.uni-giessen.de

Genetic polymorphism in milk proteins is due to gene mutation resulting in either substitution or deletion of amino acids sequence along the peptide chain. South American camelids were genetically poorly investigated so far and little information is available in alpacas (*Vicugna pacos*) regarding the diversity of the caseins. The aim of this study was to investigate the presence of polymorphisms at the CSN1S1 gene in alpacas at protein and DNA level. The analysis of whole alpaca milk by IEF from 20 samples evidenced polymorphic protein patterns corresponding to αs1-CN migration area. According to the nomenclature in Llamas, the variants were 2 and 3 with 2 being the anodic one. Three variants (2/2, 2/3, 3/3) could be observed. Estimation of frequencies resulted in 0.475 and 0.525 for the variants 2 and 3, respectively. Blood and hair samples were collected from 130 alpacas belonging to different flocks in Germany and Italy. They were used for DNA isolation. The SNP c.366A>G at the exon 12 was successfully genotyped by PCR-RFLP. Two (AA, AG) of the three possible genotypes could be demonstrated resulting in estimated allele frequencies c.366 A 0.91 and c.366G 0.09. Milk samples from IEF showed different genotypes at DNA level for the SNP (c.366Alle>GVal) as the mutation at the exon 12 does not lead to a relevant change in terms of pI of protein and therefore it was not possible to establish a link with IEF results. The polymorphisms found in alpaca have not been described before. The presence of the adenine (c.366A) at the exon 12 of the alpaca CSN1S1 might represent the ancestral condition of the gene because it has been found also in the other camelids. This data adds knowledge to the genetic variability of a species little investigated and opens the opportunity for further investigation in the field of milk protein for South American camelids.

<footnote n="1">¹Institute for Animal Breeding and Genetics, Justus Liebig University, Gießen, Germany</footnote>

<footnote n="2">²Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco (TO), Italy</footnote>

<footnote n="3">³Department of Obstetrics, Gynaecology and Andrology of Large and Small Animals with ambulance, Justus Liebig University, Gießen, Germany</footnote>
# Estimación de la heredabilidad de seis caracteres de calidad de fibra de alpacas huacaya del INIA Puno

Mamani-Cato, R.H.<fnref n="1" />, Huanca, T.<fnref n="1" />, Pineda, M.<fnref n="1" />, Naveros, M.<fnref n="1" /> and Gallegos, R.<fnref n="2" />

El objetivo fue estimar las heredabilidades de seis caracteres de calidad de fibra de alpacas Huacaya a la primera esquila del banco de germoplasma del Instituto Nacional de Innovación Agraria, ubicado en el departamento de puno a una altitud de 4,200 metros en la zona agroecológica de puna seca. La base de datos constó de 9,114 registros de fibra y fueron analizados con el analizador óptico del diámetro de fibra (OFDA, IWTO-47-95) en el laboratorio de fibras del IVITA Maranganí. Para estimar los componentes de varianza del diámetro de fibra, desviación estándar del diámetro de fibra, factor de confort, coeficiente de variabilidad del diámetro de fibra, longitud de mecha y peso vellón se utilizó el modelo animal unicaracter y = Xb + Zu + e, donde y es el vector de observaciones, b es el vector de efectos fijos (sexo, color y mes-año de esquila) la edad en días se consideró como covariable lineal, u es el vector que representa el efecto genético aditivo, e es el vector de residuales; X y Z son las matrices de incidencia de efectos fijos y aleatorios respectivamente. Los componentes de varianza fueron estimados por el método de Máxima Verosimilitud Restringida (REML) utilizando el programa VCE versión 6.0.2. La heredabilidad estimada para el Diámetro de fibra fue de alta magnitud 0.540±0.087; para el resto de caracteres fue de media magnitud siendo para la Desviación estándar 0.311±0.089, Factor de confort 0.278±0.077, Coeficiente de variabilidad 0.291±0.089, Peso vellón 0.158±0.027 y Longitud de mecha 0.268±0.081. Se concluye que es posible obtener una buena respuesta a la selección para los seis caracteres de calidad de fibra en alpacas Huacaya.

<footnote n="1">¹Instituto Nacional de Innovación Agraria (INIA) Puno – Perú</footnote>

<footnote n="2">²Universidad Nacional del Altiplano, Facultad de Medicina Veterinaria y Zootecnia</footnote>
Effect of the Brown Coat-Coding Gene (Tyrp-1) on
Wool and Skin Color of Żelaźnieńska and
Wrzosówka Sheep

Niżnikowski, R., Świątek, M. and Zymańska, Z.

Division of Sheep and Goat Breeding, Faculty of Animal Sciences, Warsaw
University of Life Sciences, Ciszewskiego 8 Street, PL 02-786 Warszawa

The aim of the study was to assess the relationship between frequency of alleles and genotypes of the brown coat-coding gene (TYPR-1) and the color of wool and skin measured objectively. In order to better illustrate the color differences, two breeds were examined: white colored Żelaźnieńska sheep and colorful (mostly grey) Wrzosówka sheep. The study was conducted on randomly chosen ewes (Żelaźnieńska sheep – 93; Wrzosówka sheep – 133) during shearing. Color of wool and skin was examined using a Chroma Mater CR-400 device. Color was measured using the system CIE L*a*b*. L* expresses clarity and varies from 0 (black) to 100 (white). a* varies from -60 to +60, where it ranges from -a* (green) to +a* (red). b* varies from -60 to +60, where it ranges from -b* (blue) to +b* (yellow). Color of wool and skin measurements were taken on the right side of sheep at the point of the last rib. DNA was isolated from blood leukocytes. Sample genotyping was performed with the KASPar® system (www.kbioscience.co.uk), which uses a single nucleotide polymorphism (SNP) and found three genotypes: CC, CT and TT. Significant and highly significant differences in all color measurements of wool (Żelaźnieńska vs. Wrzosówka: L*: 75,64 vs. 46,09 P ≤ 0.01; a*: 0,67 vs. 2,33 P ≤ 0.01; b*: 5,84 vs. 2,75 P ≤ 0.01) and skin (Żelaźnieńska vs. Wrzosówka: L*: 70,03 vs. 54,26 P ≤ 0.01; a*: 4,53 vs. 3,98 P ≤ 0.05; b*: 6,18 vs. 3,17 P ≤ 0.01) between tested breeds were found, which should be connected to the different wool color in each breed. Differences in color values of wool depending on TYRP-1 gene genotypes were observed only for Wrzosówka sheep. The measurement of the L* color parameter made on wool was significantly higher in the case of CC and CT genotypes compared to TT genotype (respectively 47,25 vs 48,27 vs 38,10; P ≤ 0.01). However, in the measurement of the a* color parameter, the situation was reversed and homozygote TT had higher values compared to CC and CT genotypes (3,58 vs 2,17 vs 1,92; P ≤ 0.01, respectively). No differences between all skin color parameters for both breeds were found. The results of studies on wool color, depending on genotype of the TYRP-1 gene in Wrzosówka sheep, opens possibilities to conduct breeding work in order to develop standards for coat color in this breed.
# Relationship between Classes Assigned by Visual Appraisal and a Selection Index in Function of Live Weight, Fleece Weight and Fiber Diameter in Huacaya Alpacas from Pasco

Corredor F.A.<fnref n="1" /> and Gutiérrez G.<fnref n="2" />

Visual appraisal evaluation is a common practice in highland livestock production of alpacas in Peru. An alternative is using selection indexes based on performance tests. The aim of this study was to evaluate the relationship between the classes assigned by visual appraisal with a selection index based on live weight, fleece weight and fineness in white Huacaya alpaca fiber. 1823 alpacas were evaluated, in which females and males were 1083 and 740 respectively. Index coefficients were estimated for the productive characteristics of live weight (10.41), fleece weight (0.60) and fiber diameter (-11.65), using market prices for alpaca fiber at the producer level of 2014 (MINAGRI 2016). This selection index has an estimated genetic progress for live weight of 1,047 kg, for fleece weight 0.050 kg and fiber diameter -0.71 microns. A linear additive model was used for the comparison of this index with the selective classes, where live weight is included as a covariable. Statistical differences (p-value <0.05) were found between selective class, shear number and source. Selective classes S, A and B show statistically equal means and selective class C shows statistical differences with the other averages for the selection index. When applying a selection index, the weighting to each of these characteristics is governed by the economic value obtained, so it is shown that the selective classes S, A and B have no difference between their averages of the index score.

<footnote n="1">¹Animal Breeding Program (PMA). Universidad Nacional Agraria La Molina – UNALM. Av. La Molina S/N. La Molina, Lima 12, Peru.
E-Mail: acorredor117@gmail.com</footnote>

<footnote n="2">²Animal Breeding Program (PMA). Universidad Nacional Agraria La Molina – UNALM. Av. La Molina S/N. La Molina, Lima 12, Peru.
E-Mail: gustavogr@lamolina.edu.pe</footnote>
# Preliminary Comparative Analysis and Localization of *Bos Taurus* SNPS on *Vicugna Pacos* Chromosome 10 (Vpa10)

Farfán K.A.<fnref n="1" />, Gutierrez G.A.<fnref n="2" /> and Ponce de León F.A.<fnref n="3" />

Current genomic information on alpaca (*Vicugna pacos*) is incipient. To increase the number of SNPs, we used the Illumina (Bovine Hd Genotyping – 777kSNP) DNA chip to genotype 40 female Huacaya alpacas and identified a total of 10314 potentially similar SNPs between cattle and alpaca. To determine if our strategy has validity and confirm similarity and chromosomal location of SNPs in alpaca, we used the genome database of the Vicugna_pacos-2.0.1 alpaca (ABRR00000000.2; NCBI) and the chromosomal location of 230 molecular markers as well as ZooFISH, generated by Avila et al. (2014) and Balmus et al. (2007), respectively. Positive SNPs in alpaca were compared to sequences from the 4195 scaffolds (KB632434: KB635807; NCBI) with the Megablast software. For preliminary validation of our strategy, we selected all the SNPs located on BTA29 that were positive in the alpaca and compared the sequences of those SNPs with the alpaca scaffolds sequences associated with markers found on chromosomes 10 (VPA10) and 33 (VPA33) (Avila et al., 2014). The latter, supported by ZooFISH analysis, indicated that BTA29 is equivalent to VPA10 and PVA33 according to Balmus et al. (2007). These comparisons identified 42 bovine PNSs co-localized in VPA10 and zero PNSs in VPA33. These preliminary studies indicate that it will be possible to identify an adequate number of conserved SNPs between bovine and alpaca that will allow enriching the genomic information of the alpaca. This strategy demonstrates an alternative to be applied to species with little or no genomic information.

Avila F., Baily M., Perelman P., Das P., Pontius J., Chowdhary R., Owens E., Jhonson W., Merriwether D., Raudsepp T., 2014. A Comprehensive Whole-Genome Integrated Cytogenetic Map for the Alpaca (Lama pacos). *Cytogenet Genome Res* 2014;144:193–204 D OI: 10.1159/000370329

Balmus G., Trifonov V., Biltueva L., O’Brien E., Fu B., Skidmore J., Allen T., Graphodatsky A., Yang F., Ferguson-Smith M., 2007. Cross-species chromosome painting among camel, cattle, pig and human: further insights into the putative *Cetartiodactyla* ancestral karyotype. *Chromosome Research* (2007) 15:499–514 DOI: 10.1007/s10577-007-1154-x

<footnote n="1">¹Department of Animal Production, Universidad Nacional Agraria La Molina, Lima, Peru, E-Mail: 20111015@lamolina.edu.pe</footnote>

<footnote n="2">²Department of Animal Production, Universidad Nacional Agraria La Molina, Lima, Peru, E-Mail: gustavogr@lamolina.edu.pe</footnote>

<footnote n="3">³Department of Animal Science, University of Minnesota, St. Paul, MN, USA E-Mail: apl@umn.edu</footnote>
# Innovative Andrological Evaluation to Optimize the Selection of Fiber Animal

Stelletta, C.<fnref n="1" />,<fnref n="2" />

Breeding soundness evaluation (BSE) is an overall assessment of the ability of a male to mate and to initiate reproduction. It is estimated that sub-fertile males represent the 20% in an unselected population. Classical BSE includes: libido assessment, physical examination, examination of the reproductive organs and semen evaluation. The development of new diagnostic techniques has introduced new tools to integrate the classical BSE. Trans-scrotal ultrasonography is a non-invasive technique that is ideal in on-farm condition. The echo-doppler approach can increase the accuracy on the testis vascularity evaluation. Ultrasonography applied on the accessory glands can optimize the precision of the BSE in camelids, ram and buck. Testicular fine-needle aspiration cytology reports are available in many species and it has been described to enhance BSE accuracy. The exogenous administration of GnRH has the effect to increase serum levels of LH and testosterone. GnRH challenge test has been associated with the scrotal thermography evaluation. Some studies showed the relation among seminal plasma components with sperm function, stress resistance and cryopreservation success. The *sperm zone pellucida binding test* is based on the concept that spermatozoa need to be able to pass the zone pellucida in order to fertilize an oocyte. The *sperm oviductal cell adhesion test* is based on the evidence, that in-vivo adhesion of spermatozoa to isthmic cells is necessary to develop the ability of fertilization. *In-vitro taxis factors test*, with microfluidics technologies, and *in-vivo sperm test*, based on the use of fibered confocal microscopes, can be able to identify the place reached by sperm after time unit from the insemination. All these new available approaches can increase precision and accuracy of a classical BSE during the selection process of males.

<footnote n="1">¹Department of Animal Medicine, Production and Health. University of Padova, Italy</footnote>

<footnote n="2">²Department of Reproduction and Artificial Insemination, Faculty of Veterinary Medicine. Ankara University, Turkey</footnote>
# Use of Seminal Plasma on Interval to Ovulation, Susceptibility of Corpus Luteum to Prostaglandin and Improving of Reproductive Performance in Alpacas (*Vicugna Pacos*) under Peruvian Highland Conditions

Huanca, W.<fnref n="1" />, Turin, J.<fnref n="1" />, Huanca, W.F.<fnref n="1" />, Mamani, C.<fnref n="1" />, Sanchez, S.<fnref n="1" /> and Cordero, A.<fnref n="2" />

Alpacas, like all camelids, are induced ovulators which means, mating is required to induce ovulation (San Martin et al., 1968). The reproductive efficiency of alpacas under Peruvian highland conditions is low due high embryo mortality, short breeding season and long gestation period and it is one of the main factors that affect the development of breeding programs to produce genetically superior animals with natural mating. The presence of an ovulating inducting factor (OIF) in the seminal plasma of alpacas has been reported by Rios (1989) and later confirmed by Adams et al. (2005). Seminal plasma can, therefore, also be used as an alternative for inducing ovulation with subsequent development of a corpus luteum (CL) capable of maintaining pregnancy and improving the reproductive performance in alpacas. Experiments were performed with the objective to evaluate the effect of seminal plasma (SP) application on: the interval at ovulation (Exp. 1); susceptibility of the corpus luteum to the prostaglandin (PG) induced to ovulation with seminal plasma (Exp. 2); improvement of the pregnancy rate in alpacas under natural mating (Exp. 3); or to evaluate the effect of seminal plasma in females with different times of mating (Exp. 4). Adult, non-pregnant alpacas were used for the different experiments. The animals were evaluated by ultrasound to determine the presence of a dominant follicle (≥ 7 mm) and then assigned to the treatments. Exp. 1: Alpacas were assigned to T1 (n=12) application of 1.0 mL of SP or T2 (n=12) application of 0.04 mg of GnRH (Acetate of busereline) and evaluated by transrectal ultrasonography with a transducer 7.5 MHz (Aloka SSD500) every two hours from 20 to 40 hours or disappearance of dominant follicle previously observed. Exp.2: alpacas were assigned to the following treatments: T1 (n=8): SP + PG D4; T2 (n=8): GnRH+PG D4; T3 (n=8): SP+PG D5; T4 (n=8): GnRH+PG D5; T5 (n=8): SP+PG D6; T6 (n=8): GnRH+PG D6; T7 (n=8): SP+PG D7; T8 (n=9): GnRH+PG D7; T9 (n=8): SP+PG D8;

<footnote n="1">¹Laboratory of Animal Reproduction, Faculty of Veterinary Medicine, Universidad Nacional Mayor de San Marcos
E-Mail: whuancal@unmsm.edu.pe</footnote>

<footnote n="2">²Department of Nutrition, Faculty of Zootechny, Universidad Nacional Agraria, La Molina</footnote>
T10 (n=8): GnRH+PG D8; T11 (n=6): Control: 1mL Saline solution. Animals were evaluated by ultrasonography every twelve hours after application PG (196 µg. Tiaprost). Exp. 3: Non-pregnant alpacas with a follicle ≥ 7 mmm were bred by natural mating and then assigned to T1 (n=40): Mating + 1 mL SP; T2 (n=39): Mating + 0.042 mg GnRH and T3 (n=38): Control. Animals were evaluated by ultrasound to pregnancy rate on Day 25 and 62; Exp. 4: Alpacas evaluated by ultrasound were assigned randomly to the following treatments: T1 (n=28): natural mating 5 min; T2 (n=28): natural mating 5 min. + 1.0 mL SP; T3 (n=27): natural mating 10 min.; T4 (n=27): natural mating 10 min + 1.0 mL SP; T5 (n= 26): natural mating ≥ 15 min; T6 (n=26): natural mating ≥ 15 min + 1.0 mL SP. Results were: EXP.1: Interval to ovulation was 27.1 ±1.9 and 26.6 ± 1.6 h to SP and GnRH, respectively. EXP. 2: luteolysis was 0.0 %, 0.0 %, 25.0 %, 0.0 %, 100.0 %, 100.0 %, 100.0 %, 100.0 %, 100.0 %, 100.0 %, and 0.0 % for the treatments T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, and T11 respectively. EXP. 3: Pregnancy rate was 67.5 %, 51.3 % and 55.3 % to D25 and 92.6 %, 80.0 % and 85.7 % of embryo survival to D62 to T1, T2 and T3 respectively. EXP. 4: Pregnancy rate was 50.0 %, 64.3 %, 62.9 %, 70.3 %, 76.9 % and 80.0 % to D25. The results suggest that SP does not induce differences with GnRH on interval to ovulation and susceptibility to corpus luteum but would be an important alternative to improve the reproductive performance in alpacas with an increase of embryo survival and the use of males to mating a major number of females with similar pregnancy rate.
# Induction of Superovulation in Alpacas According to the Number of Follicles Recruited to the Emergence of Follicular Wave

Pozo A.<fnref n="1" />, Vásquez A.<fnref n="1" />, Zevallos J.<fnref n="2" />, Olivera L.<fnref n="2" />, Cordero A.<fnref n="3" /> and Huanca W.<fnref n="1" />

E-Mail: whuancal@unmsm.edu.pe

Two experiments were designed to evaluate the response to induction of superovulation with equine Chorionic gonadotropin (eCG). EXP. 1: 34 Alpacas were evaluated by ultrasonography to determine the presence of a dominant follicle (≥ 7 mm) and then induced to ovulation with 0.04 mg of GnRH (Acetate of busereline). They were then evaluated on D2 to determine ovulation on the disappearance of the dominant follicle previously observed and further evaluated by transrectal ultrasonography with a transducer 7.5 MHz (Aloka SSD500) every two days to determine the number of follicles recruited in successive follicular waves. EXP 2: According to the number of follicles emergent ≥ 3 mm at Day 4 post induction of ovulation, the alpacas were assigned to T1 (n=13) with 2.4 ± 0.5 follicles and T2 (n=12) with 6.0 ± 2.27 follicles. Alpacas with presence of a dominant follicle ≥ 7 mm were induced to ovulation with 0.04 mg of GnRH (Acetate of busereline). They were then evaluated on D2 to determine ovulation on the disappearance of the dominant follicle previously observed and then induced to superovulation with 700 IU of eCG IM according to the protocol described by Huanca et al. 2009. The alpacas were mounted with fertile males and seven days later were flushed to recover the embryo. The average number of emergent follicles ≥3 mm at Day 4 was 3.6 ± 2.6 follicles. The repeatability of the number of recruited follicles in successive follicular waves was 0.46. The superovulatory ovarian response in T1 and T2 was 10.0 ± 6.9 and 10.0 ± 8.1 follicles (P = 0.68) and 8.5 ± 4.3 and 7.5 ± 4.3 (p=0.77) corpus luteum. Embryo recovery rate was 2.6 and 2.2 embryos to T1 and T2, respectively (p=0.47), with embryos of good quality. The results suggest that the alpacas resent a small number of emerging follicles by follicular wave during their recruitment and that this affects the selection of donors with irregular and low response to superovulatory protocols. This would be linked to intrinsic factors associated with ovarian reserve and genotype.

<footnote n="1">¹Laboratory of Animal Reproduction, Faculty of Veterinary Medicine –
Universidad Nacional Mayor de San Marcos, Lima, PERU</footnote>

<footnote n="2">²Faculty of Veterinary Medicine and Zootechny – Universidad Nacional del
Altiplano, Puno, PERU</footnote>

<footnote n="3">³Department of Nutrition, Faculty of Zootechny – Universidad Nacional Agraria,
La Molina, La Molina, Lima, PERU</footnote>
# Farmers Wool and Traceability

Thompson, N.

Consortium Biella, The Wool Company

Globalisation has been of great benefit for many, but in many cases it has caused unrepairable damage to minor supply lines of agricultural by-products, such as wool. Cheap freight costs to Asia have heavily diminished wools value, especially where the wool is not destined for quality products, but mainly towards the upholstery and furnishings sector. However, new opportunities for the small sheep-breeder are presenting themselves, thanks to a more knowledgeable consumer, who may not be totally in favour of biological labelling (often not quite as transparent as one would hope) but believe in transparency. Wool is natural, renewable and sustainable, and therefore has the prefect characteristics for ethical processing here in Europe, to satisfy this growing demand.
# Feed Intake and Animal Behaviour of Alpaca and Llamas Co-Grazing on Andean Highlands in Peru

Hoehn D.<fnref n="1" />, Castro-Montoya J.<fnref n="1" />, Gomez C.<fnref n="2" /> and Dickhoefer U.<fnref n="1" />

Despite huge interest in raising South American Camelids (SACs) – either as a hobby or for livelihood – and a vast number of scientific publications addressing SACs, relatively few efforts have been made to study feed intake and animal behaviour under grazing conditions. Data on voluntary feed consumption and nutrient requirements are mainly from animals kept in barns or derived from studies involving sheep, goats and cattle (National Research Council, 2007). Therefore, limited information on grazing behaviour of SACs is available (Gauly, 2011). Hence, a comparative study with alpacas and llamas co-grazing on Andean pasture in Peru was conducted with the aim at (i) Exploring group specific differences (i.e. alpaca/llama, male/female) on activity patterns, feed intake, and digestibility; (ii) Relating individual and group behaviour, intake and digestibility parameters with performance indicators and vegetation characteristics. Out of 634 alpacas and 74 llamas co-grazing on an area of 340.6 ha, twelve eight-month-old alpacas (huacaya) and llamas (q'ara) (six females and six males, respectively) were randomly selected for the study. Data was collected during the transition from dry to rainy season between October and December 2016 in the Pasco region (4,350 m.a.s.l.) of Peru. Animal movement was monitored by fitting the animals with global positioning system devices for twelve consecutive days. Simultaneously, visual observation at a 30 seconds interval was performed, with one and a half hours observation per animal. Animal activities monitored were grazing, traveling, resting, drinking, and others. Feed intake and organic matter digestibility were estimated by the combination of internal (Titanium dioxide, 2.5 g/d) and external markers (acid insoluble ash). Faecal grab samples were collected during five days. Diet simulation sampling was performed for four alpacas and four llamas. Vegetation samples for biomass production and botanical composition were taken at two different moments from 14 transects across the grazing area. Live weight of animals was recorded every four weeks. Finally, fibre of alpacas was cut (mid side sampling) at the beginning and at the end of the experiment to estimate clean fibre weight, mean fibre diameter, and fibre length. Differences in grazing behaviour and vegetation utilization between both species and between sexes within a species will be evaluated. Similarly, the relationship between grazing parameters and performance between species and sexes will be assessed. Finally, the existence of a

<footnote n="1">¹University Hohenheim, Institute of Agricultural Sciences in the Tropics, Animal Nutrition and Rangeland Management in the Tropics and Subtropics, Germany</footnote>

<footnote n="2">²Universidad Agraria La Molina, Faculty of Zootecnia, Animal Science Department, Peru</footnote>
preferential grazing, or not, by different species as affected by biomass availability, quality and botanical composition will also be tested.

Gauly, M., Vaughan, J., Cebra, C., 2011, Neuweltkameliden – Haltung, Zucht, Erkrankungen. 3rd edition, Stuttgart: Enke Verlag (p 62).

National Research Council, 2007, Nutrient requirements of small ruminants: sheep, goats, cervids, and New World camelids. Washington, D.C.: National Academies Press (p 238).
# Daily and Seasonal Changes in Body Temperature and Activity Patterns of Llamas in the High Andes of Peru

Riek, A.<fnref n="1" />, Stölzl, A.<fnref n="1" />, Marquina Bernedo, R.<fnref n="2" /> and Gerken, M.<fnref n="1" />

Endothermic animals have to invest a substantial amount of energy to keep their body temperature (Tb) within a narrow limit. Recent studies on wild ungulates, however, revealed that they are able to adjust their Tb and locomotor activity (LA) according to season and time of the day and thus save energy during adverse environmental conditions. Therefore, the aim of the study was to determine whether the llama, one of the most extensively kept domestic livestock breeds, also exhibits seasonal adjustment mechanisms in terms of Tb and LA under High Andean conditions. For the present study, 7 female adult non-pregnant llamas were kept within a herd of approx. 300 female llamas under a traditional herding system in the High Andes of Peru. The study site was a semi-arid habitat and located 80 km to the North of the city of Arequipa in Southern Peru at an altitude of 4,400 m. The LA and Tb (measured in the rumen) were recorded continuously for each animal every 3 min and the location every 30 min for 10 months using a telemetry system. Relative humidity and ambient temperature (Ta) were recorded every 60 min using miniature data loggers. Daily Tb varied considerably with daily maximum (mean max. ± SD: 39.47 ± 0.32 °C, max. range: 40.55 - 38.97 °C) and minimum (mean min. ± SD: 37.49 ± 0.36 °C, min. range: 36.58 - 38.12 °C) Tb's occurring around midday and early morning, respectively throughout the study period. The daily Tb amplitude differed significantly (P < 0.001) between seasons and was highest in June-Sep, when Ta was low (average daily mean ± SD: 1.94 ± 1.43 °C, average daily amplitude: 34.54 ± 4.79 °C) and lowest in Dec-March when Ta was high (average daily mean ± SD: 6.93 ± 1.22 °C, average daily amplitude: 22.34 ± 3.68 °C). Average daily Tb followed the Ta pattern, i.e. Tb was correlated with Ta (r = 0.43, P < 0.001). Daily distances covered averaged 5.3 ± 1.2 km and ranged from 3.4 - 11.2 km per day. Mean daily LA varied considerably over the study and followed a similar pattern as Ta with the lowest daily average LA recorded in June (19.58 ± 16.34 %) and the highest in Jan (36.35 ± 32.9 %).

The results indicate that llamas in the high Andes adjust their Tb and LA according to season and time of the day in accordance to Ta. Throughout the study we found a distinct daily Tb and LA rhythm. Therefore, despite of the domestica-

<footnote n="1">¹Department of Animal Sciences, University of Göttingen, Albrecht-Thaer-Weg 3, 37075 Göttingen, Germany</footnote>

<footnote n="2">²Centro de Estudios y Promoción del Desarrollo, Calle Malaga Grenet 678 – Umacollo, Arequipa, Peru</footnote>
tion process, llamas seem to have maintained the ability to adjust their Tb under adverse environmental conditions as has been reported for some wild ungulates.
# Blood Levels of Phosphorus in Pubescent Alpaca (*Vicugna Pacos*) and the Effect of Dietary Phosphorus on Growth of Female Alpacas Post Weaning in Peruvian Andes

Quispe, C.E.<fnref n="1" />, Ancco, E.<fnref n="1" />, Van Saun, R.<fnref n="2" /> and Gomez, C.<fnref n="3" />

E-Mail: equispe.vet@gmail.com

E-Mail: rjv10@psu.edu

E-Mail: cagomez@lamolina.edu.pe

Phosphorus deficiencies have been reported for alpacas in the Peruvian Andes. This is of special relevance because their hidden effects may be affecting some reproductive variables and the growth in one-year-old pubescent alpacas forcing the farmers to start mating at two years with the economic consequences of feeding without producing and delaying genetic progress. This study is performed in an effort to know the status of phosphorus and the effects of this mineral on feed consumption and live weight variables in young female alpacas in two important stages of production such as breeding season (January - February) and weaning (August - September). In the first stage of the study, blood levels of phosphorus were determined in 180 female alpacas of approximately 11-13 months of age located in four regions of greater importance for alpacas breeding in Perú. Levels of 8.25 ± 1.63, 5.25 ± 1.46, 6.42 ± 1.84, 4.8 ± 1.61 mg / dl were found for Cerro de Pasco, Junín, Cuzco and Puno regions, respectively. Significant differences (P <0.05) were found among the four regions, and these data were compared with the expected range for alpacas (Van Saun and Herdt, 2014: 5-11.5 mg/dl). Two regions (one below the mentioned limit and another at the limit) can be considered deficient in phosphorus. This may be related to the deficiencies of this mineral in the high Andean grasslands reported by some authors and may be affecting some reproductive, consumption and growth parameters associated with this mineral. In a second part of the study, a controlled experiment with different concentrations of phosphorus in the diet was performed: 0.16 % (T1), 0.25 % (T2), and 0.34 % (T3). Forty-five female alpacas post weaning (25.25 ± 1.62 kg) were used, with ad libitum feeding, with 15 animals per treatment housed in individual pens for a period of 4 months. Ages range from six to eight months. Dry matter intake, phosphorus intake and live weight were

<footnote n="1">¹PhD Program in Animal Science, National Agrarian University La Molina, Av. La Molina s/n, La Molina, Lima, Perú</footnote>

<footnote n="2">²Department of Veterinary and Biomedical Sciences, Pennsylvania State University, USA</footnote>

<footnote n="3">³Faculty of Animal Science, Nutrition Department, National Agrarian University La Molina, Av. La Molina s/n, La Molina, Lima, Perú</footnote>
evaluated. The average dry matter intake expressed per kg/d was 0.458, 0.562 and 0.652 for T1, T2 and T3 respectively, while the average consumption of alpacas expressed per kilogram of live weight was 1.52 %, 1.73 % and 1.97 % respectively. In both cases there were significant differences between treatments (P <0.05). There was an appreciable reduction in feed consumption when the diet had 0.16 % of phosphorus, while for the diets of 0.25 % and 0.34 % of phosphorus consumption values are expected in camelids for this stage. Finally, the live weight was 30.58 ± 1.42, 32.4 ± 0.92 and 33.3 ± 2.43 kg for T1, T2 and T3 respectively, with significant differences (P <0.05) between T1 vs T2 and T3. The effect of lower consumption on T1 may have influenced in weight gain. Effects of phosphorus on reproductive variables to which it is associated are still being evaluated.

Jeffs, S; Parraguez, V; Urquieta, B; Reyes, M. 1996, Endocrine study of puberty in female alpacas of the coastal dryland of central Chile. University of Chile. Department of Animal Biological Sciences.

NRC (National Research Council). 2007, Nutrient Requirements of Small Ruminants: Sheep, Goats, Cervids, and New World Camelids.

Van Saun, R Y Herdt, T. 2014, Llama y Alpaca Care Book. Nutritional assessment. Chapter 12. p 115.
# Digestibility of Bean Pulp Granulated in Rabbits

Arce, O.<fnref n="1" />, Alagón, G.<fnref n="2" />, Ródenas, L.<fnref n="3" />, Martínez-Paredes, E.<fnref n="3" />, Moya, V.J.<fnref n="3" />, Pascual, J.<fnref n="3" /> and Cervera, C.<fnref n="3" />

Granulated beet pulp is a by-product of the sugar industry and it is used for feeding rabbits. The objective of this work was to determine the digestibility and energy value of granulated beet pulp from different sources in Spain by the method of substitution by total fecal collection in weaned rabbits. Therefore, 87 rabbits were distributed in 6 groups for 6 animal feeds (1 control feed and 5 feeds with 20 % inclusion of the beet pulp), with individualized feeding and consumption ad libitum. The results indicate, that the digestibility of the granulated beet pulp in rabbits was similar (p> 0.05) in dry matter (76.0 ± 6.3 %) and organic matter (76.7 ± 5.8 %), with a higher tendency for Olmedo pulp. In contrast, the digestibility of the fiber fractions (FDN and FDA) showed difference (p <0.0001), with the best response for the same pulp. Protein digestibility and digestible protein content were similar as well (p> 0.05), with 62.3 ± 6.3 % and 5.2 ± 0.6 %, respectively. The digestible energy content, with an average of 12.8 ± 0.8 KJ / g of dry matter and an efficiency of use of 0.72 ± 0.05 in relation to the gross energy was similar. These results confirm that the granulated beet pulp has good digestibility and is an important source of digestible energy for rabbits.

<footnote n="1">¹Facultad de Ciencias Agrarias y Veterinarias, Universidad Técnica de Oruro, Avda. 6 de Octubre 5715, Cas Postal 49, Oruro, Bolivia</footnote>

<footnote n="2">²Facultad de Agronomía y Zootecnia, Universidad Nacional de San Antonio Abad del Cusco, Avda. de la Cultura 733, Ap. Postal 921, Cusco, Perú</footnote>

<footnote n="3">³Instituto de Ciencia y Tecnología Animal, Universidad Politécnica de Valencia, Camino de Vera, 14, Valencia 46071, España</footnote>
# Correlation between Diameter of Fiber, Medulation and Ancestrality in Alpacas

Melo, C., Zapata, C. and Bravo, W.

Medicina Veterinaria, Universidad San Antonio Abad del Cusco, Peru

The selection in alpacas is based on the fineness of fiber, a characteristic of great importance for the textile industry. However, it has been possible to observe fine animals with the presence of marrow in the fiber. In the present work, we evaluated the correlation between fiber fineness, the percentage of marrow and the correlation with its vicuña ancestor (*Vicugna vicugna*). The complete region was evaluated of the D-loop and the Cytochrome b region in 50 alpacas. The overall average for fiber diameter was 20.26 ± 2.69 µ. Between the fiber diameter and the percentage of medulation, the correlation was 0.8322. This positive correlation indicates, that as the percentage of medulation increases, the fiber diameter will also increase. This would reflect the degree of improvement of the herd of alpacas in some way. The median-joining network topology of the D-loop and the Cytochrome b showed two haplogroups to determine ancestry. Regarding the correlation between the percentage of medulation and the vicuña ancestor, we found a negative correlation, whereas there was a positive correlation between the percentage of medulation and the guanaco ancestor. These results allow us to indicate the ancestry of alpacas by evaluating the percentage of medulation and corroborating with molecular genetics in the laboratory.
# Apelin, a New Adipokine Acting on Hair Follicle: an Immunohistochemical Study on Ovine Skin

Mercati, F.<fnref n="1" />, Dall'Aglio, C.<fnref n="1" />, Guelfi, G.<fnref n="1" />, Scocco, P.<fnref n="2" /> and Ceccarelli, P.<fnref n="1" />

Apelin (AP) is a novel peptide belonging to the family of adipokines (Pitkin et al., 2010). Adipose tissue is a source of plasma AP and the secretion by this tissue is regulated by several factors including fasting and refeeding. Apelin specific receptor (APJ) shows a widespread tissue distribution and accordingly many physiological roles were described for AP. In this work, the expression of AP and APJ were investigated in the ovine skin by an immunohistochemical technique in order to point out the presence of structures that might be locally responsive to the action of AP. The analyses performed evidenced a clear and intense immunostaining for APJ in the ovine skin, while AP expression could not be observed. The receptor was localized in the hair follicles (HFs), while other structures of the skin appeared to be negative. APJ expression involved the outer root sheath and extended throughout follicular wall, from the infundibulum to the bulb. AP is a recently discovered molecule and, at present, there are not surveys describing it in the skin of any animal species including humans. The strong expression of APJ in the HF, suggests an important role of AP that probably acts on this organ through an endocrine mechanism. The identification of APJ in ovine skin is a preliminary study that introduces the study of AP in the skin and represents the beginning of a comparative survey that could contribute to the improvement of fiber quality.

<footnote n="1">¹Department of Veterinary Medicine, University of Perugia, Perugia, Italy</footnote>

<footnote n="2">²School of Biosciences and Veterinary Medicine-University of Camerino, Camerino, Italy</footnote>
# ICAR – Guideline for the Animal Fibre Production in Alpaca and Cashmere and New Rules for the Organization of the Fibre and Fleece Collection Centers

Antonini, M.<fnref n="1" />, Pazzaglia, I.<fnref n="2" />, Nocelli, C.<fnref n="2" />, Lou, Y.<fnref n="3" /> and Thompson, N.<fnref n="4" />

ICAR opened a working group on animal fibre in 2007. The working group first established standards and guidelines on alpaca fibre production and afterwards on cashmere goat production. Further, methods on alpaca and cashmere goat identification as well as guidelines for alpaca and cashmere shearing/combing, management, fibre harvesting and grading were established. The next step of the ICAR animal fibre working group will be, to define guidelines on the identification of the objective and the development of selection criteria in alpaca breeding. Further, the working group will be opening new guidelines for the definition of the animal fibre collection centers. The collection centers will firstly work on plans for the European wool production and subsequently for alpaca production in Latin - America and cashmere production in China.

<footnote n="1">¹Italian National Agency for New Technology, Energy and Sustainable Economic Development, ENEA CR Casaccia SSPT BIOAG PROBIO, Via Anguillarese 301, 00123 S.M. di Galeria – Roma, Italy and ICAR (International Committee of Animal Recording) Chairman Animal Fibre WG, Via Savoia 78, 00198 – Rome, Italy</footnote>

<footnote n="2">²School of Pharmacy, University of Camerino, Piazza dei Costanti, 4, 62032 – Camerino MC, Italy</footnote>

<footnote n="3">³College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China</footnote>

<footnote n="4">⁴Consortium Biella, The Wool Company – Via Vittorio Veneto, 2, 13816 Miagliano BI, Italy</footnote>
# Technological Characteristics of White and Coloroured Huacaya Alpaca Fibre in Apurimac, Perú

Corredor, F.A.<fnref n="1" />, Bustinza, V.<fnref n="2" />, Machaca, V.<fnref n="2" />, Paucara, V.<fnref n="2" />, Paúcar, R.<fnref n="3" /> and Quispe, E.C.<fnref n="4" />

The objective of this study was to characterize the different technological traits of alpaca fiber produced in the Apurimac region to document its present profile and to provide information for future improvements. Therefore, 145 fiber samples from white and colored alpacas from five communities were analyzed. The effect of sex, age, color and locality on fiber diameter (FD), standard deviation fiber diameter (SDFD), comfort factor (CF) and curvature index (CI) and the relationship between them were analyzed to determine the factors that should be considered when designing a breeding program for Huacaya alpaca in Apurímac, Peru. Statistical difference was found by sex, age, color and locality to the technological characteristics of FD, CF and CI. For SDDF, age was not significant. The FD increases with age (p<0.05) and females are finer than males, with 22.79 and 23.79 µm respectively (p<0.05). There were statistical differences (p<0.05) between dark color fiber (26.69 µm), the light color (23.81 µm) and white (22.30 µm). The CF was 87.41 % in males and 91.23 % in females (p<0.05), decreasing with age (p<0.05). The CF was different among colors (p<0.05), less CF (75.94 %) with dark color. For CI, females were 38.23 % and males 33.76 % (p<0.05), decreasing with age (p<0.05). There were statistical differences (p<0.05) between dark color fiber (29.26 %), light color fiber (34.98 %) and white (38.29 %). There were statistical differences among the five localities (p<0.05) for all the technological traits. We concluded that the quality of white and colored Huacaya alpaca fiber produced in the region of Apurimac has good potential to be improved.

<footnote n="1">¹Animal Breeding Program (PMA). Universidad Nacional Agraria La Molina – UNALM. Av. La Molina S/N. La Molina, Lima 12, Peru
E-Mail:acorredor117@gmail.com</footnote>

<footnote n="2">²Veterinary and Animal Science Faculty. Universidad Nacional Micaela Bastidas de Apurímac, Patibamba Baja s/n, Abancay, Perú</footnote>

<footnote n="3">³Animal Science Faculty. Universidad Nacional de Huancavelica, Ciudad Universitaria Paturpampa s/n. Huancavelica, Perú</footnote>

<footnote n="4">⁴Vicerectory of Research. Universidad Nacional Autónoma de Chota, Cajamarca, Perú</footnote>