Journal ofInternational Cooperation for
Agricultural Development

J Intl Cooper Agric Dev 2020; 18: 61–66

Field Report

Influence of Intra-annual Croping Seasonson Rice Yield in the Sahel
Oumarou Souleymane1), Adamou Haougui1), Adamou Basso1), Illiassou Mossi Maiga1)
1) INRAN (National Agricultural Research Institute of Niger) , BP 429, Niger

Received September 3, 2019 Accepted February 1, 2020
Abstract. Rice is a staple food in the Sahel countries. However, the crop production does not match population growth anddemand. Hence, it is important to enhance rice yield to meet the demand. Achieving greater yields depends on increasing total
crop biomass, because there is little scope to further increase the proportion of that biomass allocated to grain. Total crop biomass is determined mainly by crop photosynthesis and respiration losses, both of which are sensitive to environmental factors
such as temperature. Rice cultivation in Niger is practiced during two cropping seasons yearly. Climate parameters change
radically through the year across cropping seasons. The aim of this study was to assess intra-annual variation impact on rice
genotypes productivity. Hence, 35 breeding lines were evaluated during two cropping seasons in an alpha lattice design
with three replications. The results showed that the two cropping seasons were significantly different mega-environments.
The mega-environments impacted significantly and differently genotypes performances. Some genotypes performed wellin wet season while others did in dry season. The ideal genotype across cropping season was the genotype1. Both cropping
seasons were ideal for some genotypes. But none of them was for all the genotypes. To increase the yield and production eachgenotype should be cultivated during the ideal cropping season.
Key words: Rice, cropping season, influence, Sahel, yield

Introduction
Rice is one of mankind’s major food staples. Due to thecontinuing growth of the global population and a decreaseof availability of arable land, increasing grain yield is an
important goal of scientists and rice breeders particularly1).
Hence, world rice production must increase by 1% annually to meet the growing demand for food that will result
from population growth and economic development2).
Most of this increase must come from greater yields on
existing cropland to avoid environmental degradation, destruction of natural ecosystems, and loss of biodiversity3).
Achieving greater yields depends on increasing total crop
biomass, because there is little scope to further increase theproportion of that biomass allocated to grain. Total crop
biomass is determined mainly by crop photosynthesis andCorresponding authors email Id: umarsou@gmail.com

respiration losses, both of which are sensitive to environmental factors such as temperature4). Despite tremendous
improvements in technology and rice yield potential, theproduction remains highly dependent on climate, because
solar radiation, temperature, and precipitation are the main
drivers of crop growth.
Temperature is a major environmental factor affecting
the rice growth and development worldwide. Low andhigh temperatures are considered as the major environmental stresses for this crop plants. Both these stresses
have devastating effects on metabolism, growth, anddevelopment of plants. Rice is sensitive to low and hightemperature stresses. The optimal temperature for the ricecultivation is 25–35°C, and temperature below or higher
than optimal negatively affects the growth, physiology,
and yield of crop5). High temperature negatively affects thegrowth of roots and shoots, hampers pollination, causespoor anther dehiscence, and leads to spikelet sterility.

J Intl Cooper Agric Dev 2020 61

Likewise, low temperature delays rice germination andseedling establishment, hampers tiller formation, affects
flowering, causes panicle sterility, and finally leads tolower grain yield6, 7). According to previous study4) in thedry season, maximum temperature was not related to grain
yield. There was a negative relationship between grain
yield and minimum temperature and a positive relationship between grain yield and radiation. Grain yield was
related more closely to minimum temperature than radiation. They indicated that increases in night temperature,even small in magnitude, had a negative effect on the yieldof irrigated rice in the dry season and that the effect was
independent of radiation. In the wet season, grain yield andyield attributes were not related to minimum temperature,maximum temperature, or radiation. Furthermore, the occurrence of storm in the wet season caused crop lodging insome years, which could weaken the relationship between
yield and climatic parameters. Day high temperatures havebeen implicated to cause reductions in rice yield in manyrice-growing areas8–10).
Rice cultivation in Niger is practiced during two cropping seasons per year: wet season (from June to October)and dry season (from December to April). The climate of
the country is an arid and semi arid tropical type. Niger
is one of the world hottest areas and is characterized bythree types of seasons namely: the cold season (frommid-December to mid-February), the dry hot season (fromMarch to May) and the rainy season (from June to September). Thus, climate parameters (Temperatures, day light,
radiation, relative humidity) change radically through theyear. Therefore, it is important to know the effect of thesechanges on rice production. Hence, the goal of this study
is to assess intra-annual variation impact on rice genotypes
productivity.

Material and Methods
Plant materials were composed of 35 breeding lines
including 5 checks (Table 1). The experimental Design
was an alpha lattice design with three replications. Eachreplication was made of 7 incomplete blocks of 5 entries.
The experiment was conducted through 2 cropping
seasons: the wet season and dry season 2015. Each plot
consisted of 5 rows of 5 m long. The distance between
and within the rows was 20 × 20 cm. Fertilizer application was done as follow: A pre-drilling base application of
200 kg.ha–1 of NPK (15-15-15) was made at transplanting
stage. A total of 100 kg.ha–1 of urea was made at panicle
initiation. Weeding was done before fertilizer application.
Hand weeding was also done when needed. The harvest
was done by eliminating one row from each side of theplot. (4.6 m × 0.60 m). Winnowing and weighing weredone at 14% moisture content. Agronomic traits in the
Table 2 were collected in all the trials. Statistical analysis
was performed using Genstat software version 18th. GGE
by plot method was used for genotypes by environment
interaction. Each cropping season was considered as anenvironment

Table 1. Entries list
Variety

NumberVariety

NumberWAB 2101-WAC1-1-TGR5-WAT B6
DKA-M2
FAROX 508-3-10-F43-1-1
IWA 2
JARIBU 220
TXD 88
WAB 1436-20N-3-B-FKR2-WAC1
WAB 2060-3-FKR1-WAC2-TGR4-B
WAB 2060-FKR4-WAC1-TGR5-B
WAB 2061-2-FKR1-WAC2-TGR4-B
WAB 2081-WAC2-2-TGR2-WAT B3
WAB 2094-WAC2-TGR4-B
WAB 2095-WAC1-TGR1-B
WAB 2098-WAC2-1-TGR2-WAT B2
WAB 2098-WAC3-1-TGR2-WAT B5
L-22-26-WAC B-TGR4-B
SK-19-38-2
WAB 2056-1-FKR-4

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

WAB 2056-2-FKR2-5-TGR1-B
WAB 2066-6-FKR4-WAC1-TGR1-B-WAT-B11
WAB 2076-WAC1-TGR1-B
WAB 2076-WAC2-TGR1-B
WAB 2094-WAC2-TGR2-B
WAB 2098-WAC3-1-TGR1-4
WAB 2101-WAC3-1-TGR1-WAT B6
WAB 2101-WAC4-1-TGR1-WAT B6
WAB 2125-WAC B-1-TGR3-WAT B1
WAB 2125-WAC B-1-TGR3-WAT B8
WAB 2134-WAC B-TGR1-B
WAB 2153-TGR3-WAT B5
NERICA-L19 (Check 1)
WITA 4 (Check 2)
WITA 12NERICA-L49
GAMBIAKA

19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35

62 J Intl Cooper Agric Dev 2020

Table 2. Data collected and collection methods
Agronomic data collection

MethodSeedling/vegetative vigor (21 and 42 days after seeding)
Date of 50% flowering
Date of maturity (85% of grains on panicle are mature)
Rate of final plant stand at harvest (%) (100% indicates that there are no missing plants/hills)
Lodging incidence (%)
Phenotypic acceptability at maturity
Spikelet fertility (%)
Panicle exsertion
Plant height at harvest (cm) (soil surface to the tip of the tallest panicle (awn excluded))(3 randomly selected plants)
Grain yield and moisture content (border rows should be excluded; 0.6 m × 4.6 m)
Panicle length (for 3 panicles of the plants used for measurement of plant height)
Panicle number (the 3 plants used for measurement of plant height)
1000-grain weight

Visual rating (SES)
RecordRecordVisual rating
Visual rating (SES)
Visual rating (SES)
Visual rating (SES)
Visual rating (SES)
Measurment
Measurment
Measurment
Measurment
Measurment

Results and Discussion

Table 3. ANOVA of variable yield across cropping seasons

Results

Source ofvariation

d.f.

SS

MS

vr

F pr.

SeasonResidual

1
66

7.183
14.724

7.183
0.223

32.20

< 0.001

Total

67

21.906

The analysis of variances (Table 3) shows highly
significant differences among cropping seasons. Hence,
genotypes yields significantly change along the year fromseason to season.
The Fig. 1 shows two mega environments. Thus, each of
the cropping seasons constituted a distinct mega environment. The cropping season 1 (wet season) has the longest
vector, thus, it discriminates better the genotypes than season2 (dry season). WAB 2101-WAC1-1-TGR5-WAT B6,
DKA-M2 and FAROX 508-3-10-F43-1-1 performed wellin dry season but had poor performances in wet season.
Most of the genotypes gave more yield in environment 2(dry season) than in environment 1 the best among themare 15 and 18. Genotypes (1) WAB 2095-WAC1-TGR1-B
wone in one sector while genotype WAB 2098-WAC3-1TGR2-WAT B5 (genotype 15), WAB 2153-TGR3-WAT
B5 (genotype 30), WAB 2134-WAC B-TGR1-B (genotype29), and WAB 2094-WAC2-TGR4-B (genotype 12), wone
in the other sectors.
The highest average yield across cropping season wasobserved in with genotypes 1 (WAB 2101-WAC1-1TGR5-WAT B6) followed by genotypes 15 and 18 (Fig.
2). However, all these genotypes were very sensitive toenvironment effect. Hence, cropping season have influences on genotypes yield.
The genotypes comparison plot (Fig. 3) showed that theideal genotype is the genotype 1 (WAB 2101-WAC1-1TGR5-WAT B6) followed by genotypes 7, 2 and 3.
Environments comparison plot (Fig. 4) showed thatboth cropping seasons were ideal for some genotypes. But
none of them was for all the genotypes.

Fig. 1. Genotypes yield comparison plot

J Intl Cooper Agric Dev 2020 63

Fig. 2. Genotypes ranking plot

Fig. 4. Environments comparison plot

Discussion

Results showed that there were two different megaenvironments. Thus, the intra-year cropping seasons weredifferent. These differences may be due to environments
64 J Intl Cooper Agric Dev 2020

Fig. 3. Scatter plot showing mega environments and sectors

factors, especially climate factors, hence, edaphic ones
remains the same. Results also showed that genotypes
performed better according to mega-environments.
The temperature appears to be the critical determinant
for the rice growth. Rice, being a tropical and sub-tropicalplant that requires a fairly high temperature ranging from20º to 40ºC. Crop is adversely affected by high temperature in the lower elevation of the tropics. This critical temperature differs according to variety, duration of criticaltemperature, diurnal changes and physiological changes ofplant11). According to previous study12), low temperature
depresses the rate of germination and prolongs it beyond
the desirable span of 6 days while, high temperature of
35ºC or more halted the germination because of high respiration rate. As reported previously13), temperature has alarge influence on germination, especially in the first weekof post germination growth it also affects the rate of leaf
emergence. A long germination period may imply weaker
plantlets and less vigorous rice plants at vegetative stage.
Low temperature occurring during booting and/or heading
stage induces spikelet sterility11). Hence, dry cropping season that generally starts in November during cold period
may negatively impact the crop yield unless the variety
is not tolerant to this stress. High temperature provides
more tiller buds and thereby increases tiller number14).
Higher maximum and minimum temperature during tillering reduce the yield and depress the yield during panicle
initiation15). According to previous study16), tillering rate isinhibited by low temperature, but the period of tillering is
prolonged, resulting in more tillers and more panicles thanat high temperature. High temperature induced spikelet
sterility as stated previously11). They additionally, showedthat rice is very sensitive to high temperatures at heading
and next most sensitive at about 9 days before heading.
One or two hours of high temperature at anthesis has adecisive effect on the incidence of sterility. Consequently,
the yield will reduce as a result of poor pollen shedding
as well as inadequate pollen growth in temperature above
about 34ºC17). This phenomenon may occur in Niger ricecultivation during the dry season. Hence, the booting andanthesis stages may coincide with high temperatures ofMarch and April months unless the seeding and transplanting were performed too early to avoid the stress. This may
result in reduced yield.
Solar Radiation may differently impact on rice production according to the two cropping seasons. As reported
previously18), sunshine in a week prior to transplanting
and the two weeks period coinciding with the grandperiod of elongation is conducive for better yield. Contrastingly, shading delays tillering and decreases tillering
rate. Irrespective of varieties, shading increases the plantheight; leaf area index and total chlorophyll content andsignificantly reduces the tiller number and total dry matter production19). Solar radiation and temperature during
reproductive stage (before flowering) had the greatest
influence on rice yield because they determine the numberof spikelets m–2 and the most critical sunlight requiring
period is around the heading stage20). Thus, high rainfall
in rainy cropping season may result in the decreased availability of sunlight.
Rainfed pattern discriminates significantly the twoenvironments and may differently impact genotypes yieldthroughout the year. The rains that only occurred during
the wet season facilitate irrigation by providing water freeof cost. Furthermore, as reported previously21), an amountof dissolved substances deriving from the weathering ofrocks and soil were included in irrigation water. These
substances were higher in wet season than dry season andwill contribute to soil fertilization and plant nutrition. During the wet cropping season the relative humidity is alsohigh. This can positively impact rice growth and development, hence, increase productivity. Nevertheless, rains
may severely interfere with irrigation water management
and cause flooding that can reduce yields.
Acknowledgment
We will like to acknowledge Africa Rice Center for
funding and seed provision

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