# Visible spectroscopy on lamb fat and muscle to authenticate the duration of pasture finishing

L. Rey-Cadilhac, Donato Andueza, S. Prache

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► To cite this version:

L. Rey-Cadilhac, Donato Andueza, S. Prache. Visible spectroscopy on lamb fat and muscle to authenticate the duration of pasture finishing. Meat Science, 2024, 208, pp.109377. 10.1016/j.meatsci.2023.109377. hal-04278478

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1 Visible spectroscopy on lamb fat and muscle to authenticate the duration of pasture

2 finishing

3

4 Rey-Cadilhac Lª, Andueza Dª, and Prache Sª

5 ªUniversité Clermont Auvergne, INRAE, VetAgro Sup, UMR12133 Herbivores, 63122 St-Genès-

6 Champanelle, France

7 Corresponding author: Sophie Prache – Email: sophie.prache@inrae.fr

8

9 Abstract

10 Pasture-based livestock systems are considered environmentally-sustainable and welfare-friendly
11 farming systems that can meet consumer demand for good-quality produce. However, trust in
12 products labelled as 'grass-fed' depends on the ability to reliably authenticate pasture origin. The two
13 objectives of this study were (i) to test the ability of visible spectroscopy combined with discriminant
14 analysis on lamb perirenal fat (PF), dorsal fat (DF) and *longissimus thoracis et lumborum* muscle to
15 discriminate different durations of pasture-finishing; and (ii) to determine the timing of appearance of
16 the pasture signature and its stabilization in these tissues. Four groups of 35 lambs were used over
17 two years, i.e. lambs fed concentrate in-stall (L0) and lambs grazing alfalfa for 21d (L21), 42d (L42)
18 and 63d (L63) before slaughter. No one tissue satisfactorily discriminated the four treatment groups,
19 with ≤75% of lambs correctly classified. However, visible spectroscopy discriminated L0 from
20 L21+L42+L63 lambs with an accuracy of 92.8%, 92.0%, and 85.3% lambs correctly classified on PF,
21 DF and muscle, respectively, and discriminated L0+L21 from L42+L63 lambs with an accuracy of
22 90.1%, 76.5% and 92.3% on PF, DF and muscle, respectively. The pasture fingerprint or signature on
23 the spectrum appeared in most lambs between 0 and 21d in PF and DF and between 0 and 42d in
24 muscle. Pasture signature gradually stabilized with increasing time on pasture but was not entirely
25 stabilized in any tissue within the range of grazing durations explored. These promising results need to
26 be confirmed on larger datasets with different breeds and grazing conditions.

27 **Keywords:** chemometrics, discriminant analysis, absorbance, reflectance, alfalfa, partial least squares
28 regression
29

# 1. Introduction

The quality of food products—and especially animal-source food products—is an increasingly important criterion in consumers' purchasing decisions (Birlouez, 2019; Prache et al., 2022a). Pasture-based livestock farming systems have a great advantage in meeting this consumer demand, as they are perceived as environmentally sustainable and animal welfare-friendly (Hocquette et al., 2012; Prache et al., 2022b). However, trust in labels that claim they provide 'grass-fed' products depends on the ability to control-check and certify the claimed production conditions, which requires methods that can authenticate the dietary history of source animals based on their products. There are differences in the chemical composition of meat from lambs fed contrasted diets, for example pasture vs a concentrate-based diet indoors (Prache et al., 2022b; Prache et al., 2023), and these differences form the basis of authentication methods to discriminate between pasture-fed and concentrate-fed lamb (Monahan et al., 2018; Prache et al., 2020). Spectral analysis of meat (fat and muscle) in visible, near-infrared or mid-infrared range has been identified as a promising method for authenticating the diet of farmed ruminants (Prache & Theriez, 1999; Monahan et al., 2018; Prache et al., 2020; Logan et al., 2021). More specifically, previous research has shown that the visible absorbance spectrum of fat tissues can effectively discriminate between lambs that have been pasture-fed and concentrate-fed (Dian et al., 2007a, 2008; Prache et al., 2018) but also between lambs fed less contrasted diets, such as concentrate-finishing after pasture-feeding (Huang et al., 2015a, 2015b). In these studies, the visible absorbance spectrum of perirenal fat (PF) and caudal fat was able to discriminate the feeding regimes with 91%–100% of lambs correctly classified. Muscle tissue is the saleable part of the carcass that ends up on the consumer's plate, which therefore makes it more appropriate than fat tissue for authenticating production conditions from farm to fork. However, data on the reliability of visible spectroscopy on muscle as a method to discriminate between feeding regimes in ruminant meat remains limited, and the relevant research has only focused on beef. Nevertheless, the research has yielded encouraging results, with the proportion of correctly-classified beef samples ranging from 64% to 89% of animals when discriminating cattle fed concentrate or corn silage from pasture-fed cattle and cattle concentrate-finished indoors after pasture-feeding (Cozzolino et al., 2002; Moloney et al., 2022). These studies identified the absorption range of carotenoids and haem pigments as important parts of the spectrum of fat and muscle tissues for the discrimination of the feeding regimes (Huang et al., 2015b; Moloney et al., 2022).
Furthermore, research to date has not yet determined the timing of appearance of a fingerprint of pasture feeding on visible absorbance spectrum (a specific shape of the spectrum), or pasture 'signature', in ruminant meat (fat and muscle) relative to the start of pasture feeding, nor the timing of stabilization of this pasture 'signature' in the meat (Monahan et al., 2018; Prache et al., 2020). This time-course information is essential to be able to use visible spectrum analysis as a method of authenticating the grazing conditions of farmed meat animals, such as a minimum number of days on pasture before slaughter.

Here we investigated the change in fat and muscle visible absorbance spectrum in lambs switched from indoor concentrate-feeding to outdoor alfalfa grazing for different durations of time prior to slaughter. The objectives of the study were (i) to determine whether it is possible to distinguish different durations of alfalfa pasture-finishing based on the visible spectrum of fat and muscle, and (ii) to determine when the pasture signature appears and stabilizes in the visible spectrum of these tissues.

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## 2. Material and Methods

All experimental procedures employed in this study were approved by French Ministry of Higher Education, Research and Innovation (committee approval 14289-2017042411419479V4).

### 2.1. Experimental design, animal diets and slaughter procedures

The experiment was conducted at the Herbipôle experimental station (INRAE, UE1414, France; https://doi.org/10.15454/1.5572318050509348E12) and was replicated two times, in 2018 and 2019, with a total of 147 male Romane lambs. It compared four treatment groups with different durations of finishing on alfalfa pasture, i.e. the 'L0' group of concentrate-fed lambs kept indoors (no grazing), and L21, L42, L63 groups: lambs grazing alfalfa for 21 days (L21), 42 days (L42) and 63 days (L63) before slaughter (Figure 1). All the lambs were born within the same four-week interval in April. Mean live weight (LW) at birth was 4.1 kg ± 0.98 kg (SD). The dates of turn-out to pasture were planned to accommodate the slaughter-date schedule (all lambs slaughtered during the four weeks of September), so that lambs would be slaughtered at approximately 5 months of age (Figure 1). Each year, lambs born during this 4-week interval were randomly selected from the experimental unit's existing flock and randomized to the four treatment groups based on birth LW and growth rate between birth and the beginning of the experiment (n=18 or 19 lambs in each treatment each year).
89 Lamb age/LW at turnout to pasture was 117 ± 14 days/35.7 ± 5.2 kg, 98 ± 13 days/28.7 ± 7.0 kg, and
90 71 ± 11 days/24.1 ± 7.1 kg for L21, L42 and L63 lambs, respectively.

91 Before assignment to one of the four treatment groups, all lambs were kept indoors in a single group
92 and fed a concentrate-based diet and *ad libitum* straw. Then, during the stall-feeding period for L0,
93 L21 and L42 lambs, straw was distributed *ad libitum* but concentrate level was adjusted in quantity to
94 achieve a similar growth rate between concentrate-fed and alfalfa pasture-finished lambs. The
95 objective was to avoid potential confounding effects between lamb age/LW at slaughter and treatment.
96
97 The composition of the concentrate is given in Supplementary Table 1. Except during the 5-d dietary
98 transition from concentrate-feeding to alfalfa-grazing, the L21, L42 and L63 lambs co-grazed in a
99 added to this group of pasture-finished lambs to train them in pasture use. Rotations between grazing
100 plots were managed to give the lambs *ad libitum* access to good-quality alfalfa. Refusals were cut with
101 a gyro-crusher and removed from the plots after each grazing session. Lambs received drenches
102 against digestive nematodes and *Moniezia* if necessary, based on faecal egg counts performed at
103 monthly intervals during the grazing period. All lambs had *ad libitum* access to water and salt licks,
104 and the in-stall troughs and racks were long enough to let all stall-fed lambs feed at the same time.
105 Over both years combined, one lamb had to be removed from the experiment due to disease, and five
106 died.
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108 Lambs were slaughtered by stunning followed by exsanguination at the INRAE's experimental
109 slaughter facility. Evisceration and skinning were performed as per standard commercial practice, and
110 the carcasses were then kept in a refrigerated chiller at 4°C until 24 h after slaughter.

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## 2.2. Measurements

### 2.2.1. Animal performances and carcass characteristics

113 Lambs were weighed at birth, weekly (at the same time each week), on the day of turnout to pasture,
114 and at slaughter. At 24 h post-mortem, the carcass was weighed and graded with a fatness score
115 ranging from 1 (very low) to 15 (very high). The perirenal fat (PF) was then removed and weighed, a
116 piece of *longissimus thoracis et lumborum* (LTL) muscle was collected and the thickness of the
117 subcutaneous dorsal fat (DF) was measured.

### 2.2.2. Visible reflectance spectrum (400-700 nm) of fat and muscle
119 The reflectance spectrum of PF, DF and LTL muscle was measured on all lambs at 24 h post-mortem
120 at 10 nm intervals across the range of wavelengths from 400 nm to 700 nm, using a MINOLTA CM-
121 700d spectrophotometer (Minolta France S.A., Carrières-sur-Seine, France) with D65 illuminant and
122 an observer angle of 10°. For each tissue, the reflectance spectrum was averaged from 5 replicates,
123 transformed into absorbance values [log(1/reflectance values)], and exported into WinISI III software
124 version 1.63 (Infrasoft International, Port Matilda, PA, USA) for analysis.

125

126 **2.3. Statistical analysis**

127 All statistical analysis were performed using R software (version 4.2.2; R Fondation for Statistical
128 Computing, Vienna, Austria), except when it was explicitly stated that another software was used.

129 **2.3.1. Animal performances and carcass characteristics**

130 Data on animal performances and carcass characteristics were analyzed by ANOVA followed by a
131 Tukey test for pairwise comparisons with treatment as a fixed factor and the year as a random factor, if
132 applicable. If the distribution of the variables lacked normality and/or homoscedasticity, variables were
133 log-transformed. These statistical analysis were performed using R software version 4.2.2 (R
134 Foundation for Statistical Computing, Vienna, Austria).

135 **2.3.2. Partial least squares-discriminant analysis**

136 Partial least squares-discriminant analysis (PLS-DA) was run on the absorbance spectrum of each
137 tissue to classify the lambs into the four treatment groups, via a 4-fold cross-validation with 10
138 iterations procedure as described in Huang et al. (2015b). The PLS-DA was performed on raw spectra
139 and on spectra subjected to standard normal variate transformation followed by detrend correction
140 (SNV-D; Barnes et al., 1989) and the first derivative (1stD). The preprocessing of the spectra was
141 made with the WinISI III software version 1.63 (Infrasoft International, Port Matilda, PA, USA).
142 Beforehand, a principal component analysis was performed to study, for each tissue and treatment
143 group, the Mahalanobis distance (H) between each spectrum and the mean spectrum, in order to
144 identify outliers (H>3, Garrido-Varo et al., 2019). No outliers were identified in the raw spectra while
145 one pre-processed CF and LTL spectra and two pre-processed PF spectra were identified as outliers
146 and removed. PLS-DA models were optimized using cross-validation on the dataset: the process was
147 repeated until the addition of latent variables (LV) to the model produce no increase in cross-validation
148 accuracy.
These statistical procedures were also applied to discriminate between two treatment groups, i.e. L0 vs L21 lambs, L0 vs L42 lambs, L0 vs 63 lambs, L21 vs L42 lambs, L21 vs L63 lambs, and L42 vs L63 lambs. Pairwise discriminations showed that L0 and L21 lambs were not well discriminated using LTL spectra, unlike PF and DF. These first results prompted us to test i) discrimination between L0+L21 lambs and L42+L63 lambs, and ii) discrimination between L0 lambs vs L21+L42+L63 lambs to get advantage of this difference between fat and muscle tissue. To deal with the class imbalance in the discrimination between stall-fed (L0 lambs) and alfalfa pasture finished lambs (L21+L42+L63 lambs), the down sampling method of caret R package was used prior to PLS-DA. It randomly samples the alfalfa pasture finished lambs group to be the same size as the stall-fed lambs group.

For all discriminant analyses, the performance of the classification was expressed in terms of accuracy, i.e. the proportion of correctly-classified lambs in the total population. When the classification considered all the four treatment groups, the results were also expressed as proportion of misclassified lambs in each treatment group. When the classification considered only two groups of lambs (e.g. L0 vs L21+L42+L63 lambs, or L0+L21 vs L42+L63 lambs), we calculated four other outcomes, i.e. sensitivity, specificity, false negative rate, and false positive rate, from the confusion matrix of the discriminant models (van Stralen et al., 2009), as described in Table 1. For example, in the discrimination between L0 lambs and L21+L42+L63 lambs, with the pasture-finished lambs (L21+L42+L63 lambs) considered as the target group (Table 1), sensitivity is the ability to correctly classify the pasture-finished lambs, specificity is the ability to correctly classify the concentrate-fed lambs, false negative rate is the proportion of pasture-finished lambs wrongly assigned as concentrate-fed lambs, and false positive rate is the proportion of concentrate-fed lambs wrongly assigned as pasture-finished lambs. In addition, permutation tests were performed on each PLS-DA model (Westerhuis et al., 2008). Class labels were randomly assigned to lambs and a PLS-DA model was calculated. This procedure was repeated 100 times and distributions of the area under the receiving operating characteristic curve (AUC), accuracy and class error rate were obtained. Then, a statistical test was applied to check that the result obtained with the initial set was not part of the distribution of results from the permuted sets (example in Figure S1). In addition, the important regions of the spectra that contributed most to discriminations between the groups were assessed by a variable importance in projection (VIP) score equal to or greater than 1.0.
For each tissue, the number of lambs correctly and incorrectly classified in each pairwise discriminations (L0 vs L21 lambs, L21 vs L42 lambs, L42 vs L63 lambs) were obtained. These numbers were subjected to a Fisher's exact test followed by a *post hoc* test with Benjamini-Hochberg correction to test whether they were different between pairwise discriminations which would indicate a change in pasture signature in the visible spectrum: more correctly classified lambs and fewer misclassified lambs indicated a pasture signature established over a greater number of lambs. These tests therefore make it possible to analyze the kinetics of the pasture signature in the visible spectrum of fat and muscle tissues. The number of lambs correctly and incorrectly classified in pairwise discriminations was also subjected to a Chi-square goodness of fit test to test whether it was different from a random draw (i.e. 50% of lambs correctly classified and 50% of lambs incorrectly classified) to determine if the stabilization of the pasture signature in the visible spectrum of fat and muscle tissues was achieved.

## 3. Results and Discussion

### 3.1. Animal performances and carcass characteristics

Results on animal performances and carcass characteristics are presented in Table 2. The adjustment of the level of concentrate fed to L0, L21 and L42 lambs during the stall-feeding period led to no significant differences between treatment groups in terms of daily LWG between birth and slaughter, LW at slaughter, carcass weight, and DF thickness. There was a treatment effect on PF weight (*P*=0.050) but the between treatment groups differences were not significant. However, there was a treatment effect on carcass fatness (*P*=0.002), which was lower in L21 lambs than in L0 lambs (*P*=0.001), but none of the other pairwise comparisons found significant differences. Indeed, mean LWG at pasture was almost null for L21 lambs, which strongly suggests that the abrupt shift from a concentrate-based diet to an alfalfa-pasture diet without any concentrate supplementation stressed the lambs to some extent at turnout to pasture. Most lambs lost weight at the beginning of alfalfa pasture-grazing, but L21 lambs did not have enough time to get used to the new regime and regain weight, which explains why L21 lambs had the lowest carcass fatness. The LWG at pasture raised with the duration of alfalfa grazing (*P*<0.001), with L21 < L42 < L63 (Table 2).
## 3.2. Classification of lambs using visible spectroscopy on fat and muscle tissues combined with discriminant analysis

Figure 2 plots the mean absorbance spectra of PF, DF and LTL muscle for the four treatment groups. For each discriminant analysis, only the mathematical pre-processing method (i.e. none or SNV-D and 1stD spectrum) providing the best accuracy for classification is presented in the text and in Table 3, Table 5 and Table 6.

### 3.2.1. Discrimination of all four treatment groups (L0 vs L21 vs L42 vs L63) and pairwise discriminations

In terms of ability to discriminate the four treatment groups, visible spectroscopy on PF, DF or LTL muscle combined with PLS-DA showed low accuracy, at ≤ 75% of lambs correctly classified for all three tissues (74.1%, 64.3% and 69.5% for PF, DF and LTL muscle, respectively) (Table 3).

Permutation tests validated the significance of the discriminations (*P*<0.01; Table 3). This accuracy was below that reported by Huang et al. (2015a, 2015b) who correctly classified 91.9%–95.9% of lambs using PF or caudal fat visible spectroscopy to discriminate pasture-fed lambs vs concentrate-fed lambs vs lambs concentrate-finished indoors for 28 days after pasture-feeding (Table 4). This difference of accuracy with our study can be at least partly explained by: i) the greater contrast in the feeding regimes in the studies by Huang et al. compared to here; ii) the lower number of treatment groups in the studies by Huang et al. compared to here (3 vs 4 treatment groups, respectively); iii) the lower number of lambs used here, i.e. 141 vs 189 in Huang et al. (2015a) and 224 in Huang et al. (2015b).

Very few studies have investigated the reliability of PLS-DA on the visible spectrum of LTL muscle to authenticate dietary history in ruminants (Cozzolino et al., 2002; Moloney et al., 2022), and both were performed on beef. The accuracy of the discrimination between the four treatment groups based on LTL-muscle visible spectroscopy was slightly higher here (69.5% of lambs correctly classified) than in Moloney et al. (2022) who compared pasture-fed beef vs concentrate and grass silage-fed beef vs pasture-fed beef finished with a concentrate and grass silage diet (64% of beef correctly classified) (Table 4). Beyond differences due to animal species (lamb vs. beef), it may be due to the fact that the concentrate-fed cattle in Moloney et al. (2022) had *ad libitum* access to grass silage with the
concentrate, decreasing the dietary contrast between pasture-fed and concentrate-fed cattle. Moloney et al. (2022) also used a lower number of animals (n=45) than here.

238

In the pairwise discrimination between L0 and L21 treatment groups, the misclassification rate by PLS-DA reached 5.1% of lambs for PF, 3.1% of lambs for DF, and 24.3% of lambs for LTL muscle (Table 5, Figure 3). In the discrimination between L21 and L42 treatment groups, the proportion of lambs that were misclassified was 14.9% for PF, 27.1% for DF and 8.5% for LTL muscle. In the discrimination between L42 and L63 treatment groups, the proportion of lambs misclassified reached 24.0% for PF, 26.4% for DF and 24.6% for LTL muscle (Table 5, Figure 3). These results showed that L0 lambs were correctly discriminated from L21 lambs by visible spectroscopy on PF and DF but not by visible spectroscopy on LTL muscle. However, LTL-muscle visible spectroscopy correctly discriminated L21 lambs from L42 lambs (8.5% lambs misclassified) while PF and DF visible spectroscopy did not (14.9% and 27.1% misclassified lambs, respectively, Table 5). These results encouraged us to test the reliability of i) the discrimination between concentrate-fed lambs (L0 lambs) and alfalfa pasture-finished lambs (L21+L42+L63 lambs) using visible spectroscopy on animal tissues (chiefly PF and DF), and ii) the discrimination between lambs that did not graze or that grazed alfalfa for only 21 days before slaughter (L0+L21 lambs) and lambs that grazed alfalfa for 42 days or longer before slaughter (L42+L63 lambs) using visible spectroscopy (chiefly LTL muscle).

254

### 3.2.2. Discrimination of concentrate-fed lambs (L0 lambs) from alfalfa pasture-finished lambs (L21+L42+L63 lambs)

The discrimination between concentrate-fed lambs and lambs finished on alfalfa pasture using visible spectroscopy on animal tissues combined with PLS-DA showed good accuracy with 92.8%, 92.0% and 85.3% of lambs correctly classified when using PF, DF and LTL muscle, respectively (Table 6). Permutation tests validated the significance of the discriminations (*P*<0.01; Table 6 and Figure S1). The proportion of concentrate-fed lambs misclassified as lambs finished on alfalfa pasture was only 0.4% for PF (Table 6). Conversely, the proportions of alfalfa pasture-finished lambs misclassified as concentrate-fed lambs was 9.4% for PF. False negative and false positive rates were quite similar for DF and LTL (7.9% and 8.4% for DF and 14.2% and 16.4% for LTL, respectively).

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Previous studies have already shown that visible spectroscopy on fat tissues combined with PLS-DA can discriminate between concentrate-fed lambs and lambs grazing for at least 44 days (Dian et al., 2007a, 2008; Huang et al., 2015a, 2015b; Prache et al., 2018), but here we brought the demonstration that the method can discriminate between concentrate-fed lambs and lambs pasture-finished from as early as 21 days of grazing on alfalfa. Our findings are consistent with previous studies that have demonstrated that PF visible spectroscopy reliably discriminated pasture-fed from concentrated-fed lambs, with 93.9% to 100% of lambs correctly classified (Dian et al., 2007a, 2008; Huang et al., 2015a; Prache et al., 2018; Table 4). To our knowledge, there is no equivalent study on subcutaneous DF, but previous studies using visible spectroscopy on subcutaneous caudal fat showed similar discriminant accuracy between concentrate- and pasture-fed lambs, with 91%-92% lambs correctly classified (Dian et al., 2007a; Huang et al., 2015b). The visible reflectance spectrum of DF is easy to collect as it can be measured directly on the carcass. However, as DF is sometimes relatively thin, which hinders measurement, previous studies have generally used measurements on caudal fat (Dian et al., 2007a; Huang et al., 2015b). Here, the discrimination between concentrate-fed and alfalfa pasture-finished lambs based on the visible spectrum of DF was at least as reliable as the discrimination based on PF, whereas previous studies have found that visible spectroscopy generally gave better results on PF than on subcutaneous fat (Dian et al., 2007a; Huang et al., 2015b) (Table 4).

Examination of the VIP scores of the PLS-DA revealed the wavelengths responsible for the discrimination between concentrate-fed lambs and alfalfa pasture-finished lambs using the visible spectra of PF (Figure 4a) and DF (Figure 4b). For PF, the VIP scores equal to or greater than 1.0 were located in the following regions: 400-410 nm, 420-430 nm, 460-500 nm, 570-590 nm, 600-620 nm, 630-640 nm, and 690-700(Figure 4a). For DF, the VIP scores equal to or greater than 1.0 were located in the following regions: 400-430 nm, 460-500 nm, 570-610 nm and 690-700 nm f (Figure 4b).

The VIP scores for the discrimination using visible spectroscopy on LTL muscle showed the same range of wavelengths as important for the discrimination analysis (data not shown). The VIP scores in the range 450-510 nm and in the ranges 400-430 nm and 620-650 nm correspond to the region where carotenoid and haem pigments, respectively, absorb light.

In this study, we did not measure the carotenoid content of pasture herbage or animal fat. However, previous studies showed that green pasture herbage was much richer in carotenoid pigments than the concentrates used to feed stall-fed lambs (Prache et al., 2003a) and that pasture-fed lambs had a
295 higher plasma carotenoid content than concentrate-fed lambs (Prache & Thériez, 1999; Prache et al., 296 2003a; Huang et al., 2015b; Prache et al., 2018). Furthermore, Prache et al. (2003b) identified the 297 carotenoid pigments present in the PF of lambs and quantified their concentration. They showed that 298 only lutein was present in lamb PF and that pasture-fed lambs accumulated 2 to 4 times more lutein 299 than concentrate-fed or concentrate-finished lambs. Moreover, they showed that the shape of the PF 300 visible reflectance spectrum in the absorption region of carotenoid pigments (450-510 nm) can be 301 used to calculate an indicator of fat carotenoid concentration. Numerous studies have subsequently 302 used this indicator to discriminate between pasture-fed and concentrate-fed ruminants (Dian et al., 303 2007a; Blanco et al., 2011; Röhrle et al., 2011; Huang et al., 2015b; Ripoll et al., 2015; Prache et al., 304 2018; Blanco et al., 2019). Such a body of work is lacking in the scientific literature for haem pigments, 305 and further research is needed to better understand their involvement in the authentication of pasture- 306 feeding, which requires extracting, identifying and quantifying them in animal tissues. However, a large 307 body of data consistently observed that the region where haem pigments absorb light is involved in the 308 discrimination between pasture-fed and concentrate-fed lambs based on fat visible spectroscopy (Dian 309 et al., 2007a; Huang et al., 2015b; Prache et al., 2018).

310 The accuracy of the discrimination between concentrate-fed lambs (L0 lambs) and alfalfa pasture-
311 finished lambs (L21+L42+L63 lambs) based on LTL muscle visible spectroscopy was of the same
312 order of magnitude (85.3% of lambs correctly classified) as in previous studies attempting to
313 discriminate concentrate and grass silage- or corn silage-fed cattle from pasture-fed cattle (81%-89%
314 beef samples correctly classified; Cozzolino et al., 2002; Moloney et al., 2022; Table 4).
315

3.2.3. Discrimination of lambs with shorter or no alfalfa pasture finishing period (L0+L21 lambs) vs lambs with longer alfalfa pasture finishing periods (L42+L63 lambs)

316 The discrimination between lambs with shorter or no alfalfa pasture finishing period (lambs grazing for 317 0 to 21 days, i.e. L0+L21 lambs) and lambs with longer alfalfa pasture finishing periods (lambs finished 318 on alfalfa pasture for at least 42 days, i.e. L42+L63 lambs) using visible spectroscopy on LTL muscle 319 combined with PLS-DA showed 92.3% accuracy with 96.0% sensitivity and 88.3% specificity (Table 320 6). Therefore, only 4.0% of the lambs with a longer alfalfa pasture finishing period were misclassified 321 as lambs with shorter or no pasture finishing period, whereas 11.7% of the lambs with shorter or no 322 pasture finishing period were misclassified as lambs with longer pasture finishing period (Table 6)... 323
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The VIP scores equal to or greater than 1.0 were located in the regions 400-470 nm, 580-600 nm, 610-620 nm and around 700 nm (Figure 5). The main region was in the range 400-450 nm, which corresponds to the area where haem pigments absorb light (Figure 5). One possible explanation for this role of haem pigments as an important factor in the discrimination could be the difference in concentration in haem pigments in the muscle of grazing lambs vs concentrate-fed lambs. Dunne et al. (2006) have indeed shown that haem pigment concentrations were higher in the LTL muscle of heifers that grazed for 96 d compared to stall concentrate-fed heifers, concomitantly with higher values for a* colour coordinate of the muscle of grazing animals. The increased haem pigment concentration in the LTL muscle of grazing animals may be due to more intensive physical activity in grazing animals associated with an increase in myoglobin content (Prache et al., 2022b). Redox state can also explain the difference in muscle colour, as grazing drives increased oxidative metabolism (Moloney et al., 2022; Prache et al., 2022b).

Classification based on PF visible spectrum showed 90.1% accuracy with 83.6% sensitivity and 93.4% specificity, which led to 13.1% of longer pasture-finished lambs misclassified as shorter or non-pasture-finished lambs, and 6.6% of shorter or non-pasture-finished lambs misclassified as longer pasture-finished lambs (Table 6). Finally, the classification based on DF visible spectrum was less accurate than classifications based on PF and LTL, with only 76.5% of lambs correctly classified, and the lower sensitivity and specificity (73.0% and 79.8%, respectively). Permutation tests validated the significance of the discriminations (*P*<0.01; Table 6)

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### 3.3. Kinetics of appearance and stabilization of the alfalfa pasture signature in the visible spectrum of lamb fat and muscle

Our study analyzing the pairwise discriminations between treatment groups (Figure 3) demonstrated that the signature of pasture feeding appeared in the visible spectrum of fat tissues of most of the lambs from as early as 21 days of alfalfa grazing, as L0 and L21 lambs were well discriminated (≤ 5.1% lambs misclassified) by visible spectroscopy on PF and DF. When using visible spectroscopy on LTL muscle to discriminate between L0 and L21 treatment groups, the proportion of misclassified lambs reached 24.3%, showing that the pasture signature was not acquired after 21 days alfalfa grazing in a certain proportion of lambs. However, the pasture signature was more clearly detectable on LTL muscle spectrum for most lambs from 42 days of alfalfa grazing onwards, as L0 and L42 lambs
355 were better discriminated (8.5% lambs misclassified; Table 5). The appearance of the pasture
356 signature in the PF or DF visible spectrum after 21 days of alfalfa grazing could be attributed to the
357 change in fat carotenoid concentration. De Oliveira et al. (2012a, 2012b) switched lambs from a low-
358 carotenoid diet to a high-carotenoid diet for various durations before slaughter, and have indeed found
359 that plasma carotenoid concentrations rose significantly from 6 days on the high-carotenoid diet and
360 that carotenoid concentrations in PF and subcutaneous caudal fat rose significantly from 15 days on
361 the high-carotenoid diet. The difference in the timing of appearance of the pasture signature in the
362 visible spectrum of LTL muscle compared to fat tissues may be related to i) the fact that the
363 compounds serving for the discrimination are primarily located in adipose tissues, and to ii) differences
364 in the precocity of fat deposition, which starts first with internal fat, then with subcutaneous fat, and
365 then lastly intramuscular fat (Prache et al., 2022b).

366 This study also determined the kinetics of stabilization of the pasture signature in the visible spectrum
367 of fat and muscle tissues. We can consider that stabilization of the pasture signature is acquired if half
368 of the lambs are misclassified in the pairwise discriminations between contiguous pasture-finished
369 treatment groups, which is equivalent to a random draw. On this basis, there was no stabilization of
370 the pasture signature in any of the spectrum of the three tissues at 63 days of alfalfa grazing (P<0.001
371 for PF and LTL muscle and P=0.005 for DF). However, examination of the pairwise discriminations
372 showed that the proportion of misclassified lambs increased with increasing duration of finishing on
373 alfalfa pasture, with higher misclassification rate when discriminating between L42 and L63 lambs than
374 when discriminating L0 and L21 lambs for PF and DF (P<0.001, Figure 3) and a higher
375 misclassification rate when discriminating between L42 and L63 lambs than when discriminating L21
376 and L42 lambs for PF (P<0.001, Figure 3). This result shows that the pasture signature in the visible
377 spectrum of fat tissues progressively stabilized in a growing proportion of lambs with increasing alfalfa
378 pasture-finishing duration. Similarly, visible spectroscopy on LTL muscle had a low misclassification
379 rate when discriminating between L21 and L42 lambs but a higher misclassification rate when
380 discriminating between L42 and L63 lambs (P<0.001, Figure 3), which again suggests that the pasture
381 signature in the visible spectrum progressively stabilized in a growing proportion of lambs with
382 increasing alfalfa pasture-finishing duration.

383

384

**3.4. Implications for the authentication of the duration of pasture finishing**
Given that the goal of this work is to produce a method for authenticating the pastoral origin of meat in order to exclude meat from lambs that have not grazed or have only grazed for a short duration (from 21 to 41 days), the most important factor to consider from the farmer's perspective is not the accuracy of the method but the rate of false negatives (Table 6), which would unfairly penalize them. When discriminating concentrate-fed from pasture-finished lambs, visible spectroscopy on PF gave the best accuracy and had false negative rates that reached 9.4% of alfalfa pasture-finished lambs misclassified as concentrate-fed lambs. For the discrimination between L0+L21 groups and L42+L63 groups, visible spectroscopy on the LTL muscle gave the best accuracy and also had a low false negative rate, with only 4.0% of the longer-pasture-finished lambs misclassified as shorter or non-pasture-finished lambs (Table 6). In contrast, from the consumer's perspective, the most reliable figure would be the false positive rate. From this point of view, when discriminating concentrate-fed from pasture-finished lambs, visible spectroscopy on PF had lower false positive rates, with 0.4% of concentrate-fed lambs misclassified as pasture-finished lambs (Table 6). In the discrimination of L0+L21 lambs vs L42+L63 lambs using visible spectroscopy on LTL muscle, the false positive rate reached 11.7% of shorter- or non-pasture-finished lambs misclassified as longer pasture-finished lambs. This finding, although preliminary, suggests that in terms of future use for authentication, visible spectroscopy on PF combined with PLS-DA is a method of discrimination fairer to the farmer than to the consumer when discriminating concentrate-fed from pasture-finished lambs and, conversely, visible spectroscopy on LTL muscle combined with PLS-DA is a method of discrimination fairer to the consumer than to the farmer when discriminating shorter- or non-pasture-finished lambs from longer pasture-finished lambs.

It is important to remember that the conditions of this experiment were defined to maximize the discriminant potential of the method. Indeed, alfalfa resists drought well, and in this experiment it was managed to ensure a high supply of green leaves available to the lambs. More diverse grasslands and grazing management systems may result in more diverse carotenoid intake levels, which would in term modulate plasma and tissue carotenoid concentrations (Dian et al., 2007b; de Oliveira et al., 2012b). Note too that Macari et al. (2017) demonstrated between-breed variability in the digestive and/or metabolic fate of carotenoid pigments, and Prache et al. (2018) showed that the accuracy of the discrimination between pasture-grazed and concentrate-fed lambs using visible spectroscopy on PF combined with PLS-DA was slightly better with the Romane breed compared to the Ile-de-France
and Limousine breeds. Therefore, further research is needed to investigate the accuracy of discrimination of pasture-finishing duration using visible spectroscopy on fat and muscle combined with PLS-DA on larger inter-breed datasets and in more diverse grassland conditions.

418

4. **Conclusion**

The first objective of this study was to evaluate the potential value of visible spectroscopy on fat and muscle combined with PLS-DA to discriminate different durations of alfalfa pasture-finishing in lambs.

No one tissue studied was able to discriminate the four pasture-finishing durations tested, but the visible spectra of PF, DF, and LTL muscle reliably discriminated concentrate-fed lambs from lambs that were finished on alfalfa pasture, even when the lambs had only grazed for 21 days before slaughter. Furthermore, the visible spectra of PF and LTL muscle reliably discriminated between lambs that had not grazed or only grazed alfalfa for a short duration (less than 22 days) from lambs that had been pasture-finished on alfalfa for a longer duration before slaughter (more than 41 days).

The second objective of this study was to determine the kinetics of the appearance and stabilization of the pasture signature in the visible spectra of lamb fat and muscle tissues. The study demonstrated that for most lambs, the pasture signature appeared in the visible spectrum of fat tissues between 0 and 21 days of alfalfa grazing and in the visible spectrum of LTL muscle between 0 and 42 days of alfalfa grazing. We also found that the pasture signature in the visible spectrum was not completely stabilized in any of the three tissues within the range of alfalfa grazing durations explored, but was acquired in a growing proportion of lambs with increasing length of pasture finishing.

This study shows that visible spectroscopy on PF, DF and LTL muscle combined with PLS-DA can inform on dietary changes of lambs made shortly before slaughter. Further research is now needed, with larger datasets involving more breeds and more diverse grazing conditions, in order to test the extent to which these results can be generalized.

439

440

441 **Conflict of interests**

None to declare.

443

444 Acknowledgements
445 The authors would like to thank L. Lavelle, C. Coustet and the staff of the INRAE Herbipôle
446 Experimental Unit, S. Faure and C. Labonne from UMR Herbivores for their technical support at the
447 slaughterhouse. We also thank V. Bellet from Institut de l'Elevage and C. Experton and S. Rouger
448 from Institut Technique de l'Agriculture Biologique for the implementation and animation of the
449 REVABIO project.

450

451 **Funding**

452 This work was supported by the Special Assignment Account for "Agricultural and Rural Development"
453 (CASDAR) of the French Ministry of Agriculture, Agrifood and Forestry, under project 19AIP5912 –
454 REVABIO.

455

456 **Authors ORCIDs**

457 L. Rey-Cadilhac: https://orcid.org/0000-0002-4554-7662

458 S. Prache: https://orcid.org/0000-0003-1660-5058

459

460 **Authors contributions**

461 L. Rey-Cadilhac: software, investigation, statistical analysis, writing original draft

462 D. Andueza: methodology, software, investigation, statistical analysis, review and editing

463 S. Prache: conceptualization, investigation, review and editing, project administration, funding
464 acquisition, supervision.

465 All authors have read and agreed to the manuscript.

466

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574 Tables

575 Table 1: Interpretation of the classification test in terms of discriminant

576 performances (adapted from van Stralen et al., 2009):

$$577 \text{ Sensitivity} = \text{TP}/(\text{TP}+\text{FN}) \times 100,$$

$$578 \text{ Specificity} = \text{TN}/(\text{TN}+\text{FP}) \times 100,$$

$$579 \text{ False negative rate} = \text{FN}/(\text{FN}+\text{TP}) \times 100,$$

$$580 \text{ False positive rate} = \text{FP}/(\text{FP}+\text{TN}) \times 100$$

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">Observed groups</th></tr><tr><th>Target group</th><th>Non-target group</th></tr></thead><tbody><tr><th rowspan="2">Predicted groups</th><th>Target group</th><td>True positive (TP)</td><td>False positive (FP)</td></tr><tr><th>Non-target group</th><td>False negative (FN)</td><td>True negative (TN)</td></tr></tbody></table>

581
<table><caption>Table 2: Animal performances and carcass characteristics</caption><thead><tr><th rowspan="2">Characteristic</th><th colspan="4">Treatment groups<sup>1,2</sup></th><th rowspan="2">SEM</th><th rowspan="2">P-value<sup>3</sup></th></tr><tr><th>L0</th><th>L21</th><th>L42</th><th>L63</th></tr></thead><tbody><tr><td>Number of lambs</td><td>35</td><td>36</td><td>36</td><td>34</td><td>-</td><td>-</td></tr><tr><td>Daily LWG between birth and slaughter (g/day)</td><td>250 (145–334)</td><td>231 (165–302)</td><td>240 (133–328)</td><td>255 (162–341)</td><td>3.8</td><td>0.103</td></tr><tr><td>LW at slaughter (kg)</td><td>38.6 (24.7–49.2)</td><td>35.9 (25.8–47.4)</td><td>37.8 (21.6–55.8)</td><td>38.5 (24.8–53.8)</td><td>0.59</td><td>0.148</td></tr><tr><td>LWG at pasture (kg)</td><td>-</td><td>0.2c (-4.3–4.2)</td><td>9.2b (3.0–14.2)</td><td>14.4a (3.1–22.1)</td><td>0.66</td><td>&lt;0.001</td></tr><tr><td>Cold carcass weight (kg)</td><td>17.4 (9.9–24.3)</td><td>16.6 (11.8–23.4)</td><td>16.6 (9.1–25.3)</td><td>17.6 (10.4–25.3)</td><td>0.29</td><td>0.292</td></tr><tr><td>Perirenal fat weight (g)</td><td>196 (55–543)</td><td>140 (41–355)</td><td>156 (37–313)</td><td>168 (24–379)</td><td>7.7</td><td>0.050</td></tr><tr><td>Dorsal fat thickness (mm)</td><td>2.9 (1.0–4.0)</td><td>2.5 (1.0–4.0)</td><td>2.5 ± (1.0–4.0)</td><td>2.6 (1.0–4.0)</td><td>0.08</td><td>0.081</td></tr><tr><td>Carcass fatness score</td><td>7.1a (4–11)</td><td>5.8b (4–8)</td><td>6.3ab (4–9)</td><td>6.4ab (4–9)</td><td>0.14</td><td>0.002</td></tr></tbody></table>

¹L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 and 63 days before slaughter, respectively.

²Mean (minimum–maximum)

³Within a row, means with different letters are significantly different at $P \le 0.05$
Table 3: Performance of PLS-DA applied on the visible spectra of perirenal fat, dorsal fat and *longissimus*

*thoracis et lumborum* muscle to discriminate lambs from the four treatment groups

<table><thead><tr><th rowspan="2">Tissue</th><th rowspan="2">Discrimination<sup>1</sup></th><th rowspan="2">Accuracy (%)</th><th colspan="4">Proportion of misclassified lambs (%)</th><th colspan="3">PLS-DA parameters<sup>2</sup></th></tr><tr><th>L0<sup>1</sup></th><th>L21<sup>1</sup></th><th>L42<sup>1</sup></th><th>L63<sup>1</sup></th><th>Spectrum</th><th>LV</th><th>Permutation test (<i>P</i>-value)</th></tr></thead><tbody><tr><td>Perirenal fat</td><td>L0 vs L21 vs L42 vs L63</td><td>74.1</td><td>3.1</td><td>5.8</td><td>10.0</td><td>7.0</td><td>SNV-D/1<sup>st</sup>D</td><td>13</td><td>&lt;0.01</td></tr><tr><td>Dorsal fat</td><td>L0 vs L21 vs L42 vs L63</td><td>64.3</td><td>1.8</td><td>7.9</td><td>16.0</td><td>10.0</td><td>SNV-D/1<sup>st</sup>D</td><td>12</td><td>&lt;0.01</td></tr><tr><td>LTL<sup>3</sup> muscle</td><td>L0 vs L21 vs L42 vs L65</td><td>69.5</td><td>5.3</td><td>8.8</td><td>8.6</td><td>7.8</td><td>SNV-D/1<sup>st</sup>D</td><td>13</td><td>&lt;0.01</td></tr></tbody></table>

¹L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 and 63 days before slaughter, respectively

²SNV-D: Standard Normal Variate and Detrend; ¹stD: first derivative; LV: latent variables in the PLS-DA model

³LTL: *longissimus thoracis et lumborum*
593

<table><caption>Table 4: Existing studies using PLS-DA applied on the visible spectroscopy of fat or muscle tissues to discriminate feeding regimes in ruminants</caption><thead><tr><th>Article</th><th>Breed</th><th>N<sup>1</sup></th><th>Tissue<sup>2</sup></th><th>Discrimination<sup>3</sup></th><th>Accuracy (%)</th><th>Pasture duration in P (d)</th><th>Stall period duration in S or CS (d)</th><th>Pasture+stall periods in PS (d)</th></tr></thead><tbody><tr><td colspan="9"><strong>Lambs</strong></td></tr><tr><td>Dian et al. (2007a)</td><td>Limousine</td><td>307</td><td>Perirenal fat</td><td>P vs S</td><td>93.9</td><td>≥90</td><td>≥90</td><td></td></tr><tr><td></td><td></td><td></td><td>Caudal fat</td><td>P vs S</td><td>91.0</td><td></td><td></td><td></td></tr><tr><td>Dian et al. (2008)</td><td>Limousine</td><td>259</td><td>Perirenal fat</td><td>P vs S</td><td>94.9</td><td>≥90</td><td>≥90</td><td></td></tr><tr><td>Huang et al. (2015a)</td><td>Romane</td><td>189</td><td>Perirenal fat</td><td>P vs S vs PS</td><td>95.1</td><td>≥60</td><td>≥88</td><td>≥60P+28S</td></tr><tr><td></td><td></td><td></td><td></td><td>P vs S</td><td>100</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>P vs PS</td><td>99</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>S vs PS</td><td>96.7</td><td></td><td></td><td></td></tr><tr><td>Huang et al. (2015b)</td><td>Romane</td><td>224</td><td>Perirenal fat</td><td>P vs S vs PS</td><td>95.9</td><td>≥60</td><td>≥88</td><td>≥60P+28S</td></tr><tr><td></td><td></td><td></td><td>Caudal fat</td><td>P vs S vs PS</td><td>91.9</td><td></td><td></td><td></td></tr><tr><td>Prache et al. (2018)</td><td>Limousine</td><td>454</td><td>Perirenal fat</td><td>P vs S</td><td>94.5</td><td>≥72</td><td>≥68</td><td></td></tr><tr><td></td><td>Romane</td><td>406</td><td>Perirenal fat</td><td>P vs S</td><td>96.1</td><td>≥44</td><td>≥78</td><td></td></tr><tr><td></td><td>Ile de France</td><td>194</td><td>Perirenal fat</td><td>P vs S</td><td>94.8</td><td>≥45</td><td>Unknown</td><td></td></tr><tr><td colspan="9"><strong>Beef cattle</strong></td></tr><tr><td>Cozzolino et al. (2002)</td><td>Hereford</td><td>78</td><td>LTL muscle</td><td>P vs CS</td><td>80.8</td><td>All life</td><td>All life</td><td></td></tr><tr><td>Moloney et al. (2022)</td><td>Charolais and Limousine</td><td>45</td><td>LTL muscle</td><td>P vs S* vs PS*</td><td>64</td><td>199</td><td>199</td><td>98P+101S*</td></tr><tr><td></td><td></td><td></td><td></td><td>P vs S*</td><td>89</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>P vs S*+PS*</td><td>81</td><td></td><td></td><td></td></tr></tbody></table>

594

¹N: number of animals

595

²LTL: *longissimus thoracis et lumborum*

596

³P: pasture-fed animals; S: in-stall concentrate-fed animals; PS: pasture-fed animals with an in-stall concentrate finishing period; CS: in-stall animals

597

fed corn silage

598

*During the in-stall period, concentrate-fed animals received grass silage *ad libitum*
Table 5: Misclassification rate of PLS-DA applied on the visible spectra of perirenal fat, dorsal fat and

*longissimus thoracis et lumborum* muscle in the different between-group pairwise discriminations

<table><thead><tr><th rowspan="2">Tissue</th><th colspan="7">Proportion of misclassified lambs in pairwise discriminations¹ (%)</th></tr><tr><th>L0 vs L21</th><th>L0 vs L42</th><th>L0 vs L63</th><th>L21 vs L42</th><th>L21 vs L63</th><th>L42 vs L63</th></tr></thead><tbody><tr><td>Perirenal fat</td><td>5.1</td><td>1.7</td><td>1.7</td><td>14.9</td><td>10.0</td><td>24.0</td></tr><tr><td>Dorsal fat</td><td>3.1</td><td>9.8</td><td>6.8</td><td>27.1</td><td>23.4</td><td>26.4</td></tr><tr><td>LTL² muscle</td><td>24.3</td><td>6.8</td><td>7.8</td><td>8.5</td><td>11.7</td><td>24.6</td></tr></tbody></table>

¹L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 and 63 days before slaughter,

respectively

²LTL: *longissimus thoracis et lumborum*
<table><caption>Table 6: Performance of PLS-DA applied on the visible spectra of perirenal fat, dorsal fat and *longissimus thoracis et lumborum* muscle to discriminate concentrate-fed lambs vs alfalfa pasture-finished lambs or lambs grazing alfalfa for 0 to 21 days vs lambs grazing alfalfa for 42d to 63 days</caption><thead><tr><th rowspan="2">Discrimination<sup>1</sup></th><th rowspan="2">Tissue<sup>2</sup></th><th colspan="5">PLS-DA performance parameters (%)<sup>3</sup></th><th colspan="3">PLS-DA parameters<sup>4</sup></th></tr><tr><th>Accuracy</th><th>Sensitivity</th><th>Specificity</th><th>False negative rate</th><th>False positive rate</th><th>Spectrum</th><th>LV</th><th>Permutation test (P-value)</th></tr></thead><tbody><tr><td rowspan="3">(a) L0 vs L21+L42+L63</td><td>Perirenal fat</td><td>92.8</td><td>90.6</td><td>99.6</td><td>9.4</td><td>0.4</td><td>Raw</td><td>11</td><td>&lt;0.01</td></tr><tr><td>Dorsal fat</td><td>92.0</td><td>92.1</td><td>91.6</td><td>7.9</td><td>8.4</td><td>Raw</td><td>8</td><td>&lt;0.01</td></tr><tr><td>LTL muscle</td><td>85.3</td><td>85.8</td><td>83.6</td><td>14.2</td><td>16.4</td><td>SNV-D/1<sup>st</sup>D</td><td>10</td><td>&lt;0.01</td></tr><tr><td rowspan="3">(b) L0+L21 vs L42+L63</td><td>Perirenal fat</td><td>90.1</td><td>83.6</td><td>93.4</td><td>13.1</td><td>6.6</td><td>Raw</td><td>14</td><td>&lt;0.01</td></tr><tr><td>Dorsal fat</td><td>76.5</td><td>73.0</td><td>79.8</td><td>27.0</td><td>20.2</td><td>SNV-D/1<sup>st</sup>D</td><td>15</td><td>&lt;0.01</td></tr><tr><td>LTL muscle</td><td>92.3</td><td>96.0</td><td>88.3</td><td>4.0</td><td>11.7</td><td>Raw</td><td>15</td><td>&lt;0.01</td></tr></tbody></table>

¹L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 and 63 days before slaughter, respectively

²LTL: *longissimus thoracis et lumborum* muscle

³See Table 1. Accuracy: overall proportion of lambs correctly classified; Sensitivity: ability to correctly classify the lambs of (a) the L21+L42+L63 groups in discrimination tests and (b) the L42+L63 groups in discrimination tests (groups called 'target group'); Specificity: ability to correctly classify the lambs of (a) the L0 group in discrimination tests and (b) the L0+L21 groups in discrimination tests (groups called 'non-target group'; False negative rate: proportion of lambs wrongly assigned to the non-target group when they are part of the target group; False positive rate: proportion of lambs wrongly assigned to the target group when they are part of the non-target group)

⁴SNV-D: Standard Normal Variate and Detrend; 1stD: first derivative; LV: latent variables in the PLS-DA model
<figure><img src="image_3.png" /></figure>

Figure 1: Overview of the experimental design. Brown-coloured periods refer to indoor feeding on a concentrate-based diet, and green-coloured periods refer to outdoor grazing on alfalfa. Lambs were divided into 4 treatment groups, i.e. concentrate-fed lambs (L0), and lambs grazing alfalfa for 21 days (L21), 42 days (L42) or 63 days (L63) before slaughter.
<figure><img src="image_4.png" /><figcaption>Figure 2: Mean absorbance spectrum of (a) perirenal fat, (b) dorsal fat, and (c) *longissimus thoracis et lumborum* muscle at wavelengths between 400 and 700 nm.</figcaption></figure>

L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 or 63 days before slaughter, respectively.
<figure><img src="image_5.png" /><figcaption>Figure 3: Proportion of lambs misclassified and correctly classified in the pairwise discriminations using PLS-DA on the visible spectra of (a) perirenal fat, (b) dorsal fat, and (c) *longissimus thoracis et lumborum* muscle.</figcaption></figure>

L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 or 63 days before slaughter, respectively.

\*, \*, \*\* and † indicate a significant ($P \le 0.05$, $P \le 0.01$ and $P \le 0.001$, respectively) and a tendency ($P \le 0.10$) towards significance difference in the proportion of lambs correctly and incorrectly classified.
<figure><img src="image_6.png" /><figcaption>Figure 4: Variable importance for the projection (VIP) scores of the PLS-DA on the visible spectra of (a) perirenal fat and (b) dorsal fat for classification of the L0 treatment group vs L21+L42+L63</figcaption></figure>

treatment groups.

Wavelengths for which the VIP score is ≥ 1 are highlighted in grey.
<figure><img src="image_7.png" /><figcaption>Figure 5: Variable importance for the projection (VIP) scores of the PLS-DA on the visible spectrum of *longissimus thoracis et lumborum* muscle for the classification of L0+L21 treatment groups vs L42+L63 treatments groups.</figcaption></figure>

L0: concentrate-fed lambs; L21, L42, L63: lambs grazing alfalfa for 21, 42 or 63 days before slaughter, respectively.

Wavelengths for which the VIP score is ≥ 1 are highlighted in grey.