International Journal of Agronomy
Volume 2019 (2019), Article ID 3064026, 11 pages
https://doi.org/10.1155/2019/3064026

Research Article

Genetics of Stay-Green Trait and Its Association with Leaf Spot Tolerance and Pod Yield in Groundnut

Rukiya Danful,¹ Yussif Baba Kassim,¹ Doris Kanvenaa Puozaa,² Richard Oteng-Frimpong,² Masawudu Abdul Rasheed,² Alexander Wireko-Kena,¹ and Richard Akromah¹

¹Department of Crop and Soil Sciences, Kwame Nkrumah University of Science Technology, Kumasi, Ghana
²Council for Scientific and Industrial Research-Savanna Agricultural Research Institute (CSIR-SARI), Tamale, Ghana

Correspondence should be addressed to Doris Kanvenaa Puozaa; doriskanp@gmail.com

Received 31 January 2019; Revised 9 June 2019; Accepted 13 July 2019; Published 30 July 2019

Academic Editor: Alpha Y. Kamara

Copyright © 2019 Rukiya Danful et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Despite its importance in providing income and food for smallholder farmers, fodder for livestock, and improving soil fertility through biological nitrogen fixation, groundnut yields are lowest on farmers’ fields in Sub-Saharan Africa due to biotic and abiotic constraints. Foliar fungal diseases account for over 80% reduction in groundnut productivity in some parts of Ghana. Unfortunately, chemical control of these foliar diseases has not yielded the desired results. Meanwhile, advances in phenotyping for disease tolerance in other crops have established a strong relationship between stay-green trait and foliar disease tolerance. However, this relationship has not been explored in groundnut. This study was designed to determine the genetic control of the stay-green trait and its relationship with leaf spot disease severity in groundnut. Twenty-five advanced groundnut breeding lines with varying degrees of tolerance for leaf spot tolerance were evaluated under diseased and disease-free conditions, after which four were selected for genetic studies. Results showed significant () differences among the genotypes for early leaf spot (ELS), late leaf spot (LLS), leaf area under greenness (LAUG), SPAD chlorophyll meter readings (SCMR), and yield traits. Leaf spot diseases caused 4.95 t·ha⁻¹ (64.54%) pod yield reduction in CHINESE, the widely cultivated groundnut variety in Ghana. There was a strong correlation between LAUG and ELS (r = 0.82, ) and LLS (r = 0.63, ), and genotypes that were stay-green had tolerance to both diseases. Stay-green trait in groundnut was detected to be under the control of a single recessive gene and hence may be used to select for ELS and LLS resistance.

1. Introduction

Groundnut (Arachis hypogaea L.) is an important leguminous crop that provides income and food for the poor smallholder farmers in developing countries [1]. The haulms after harvesting the pods are also used as nutritious fodder for livestock, especially during the dry season [2]. As a result, groundnut cultivation contributes to the sustainability of crop-livestock production systems in most African countries including Ghana. Although there has been a 9.2% expansion in the area under cultivation of groundnut since 2008 and the release of high-yielding cultivars [3], Sub-Saharan (SSA) Africa contributes only about 24% to the total global groundnut production [1].

Biotic and abiotic stresses have caused yield stagnation of groundnut in SSA affecting its total production [2]. Foliar fungal diseases are the major factors limiting groundnut productivity [4] with Cercospora leaf spot (CLS) being predominant [5]. In northern Ghana, CLS has been shown to cause up to 81.2% reduction in pod yield in groundnut [6]. The leaf spot diseases damage groundnut plants by reducing the available photosynthetic area through reduction of leaf area index, lesion formation, and stimulating leaflet abscission [7, 8]. As a result, it disrupts photosynthetic process which causes groundnut to produce less pods with inferior quality. The infections mainly attack the leaves leading to premature defoliation hence causing increase in stem percentage of the resulting fodder which reduces in vitro digestibility [9] when the haulms are fed to animals. Leaf spot disease occurs in two forms; early leaf spot (ELS) which is caused by Cercospora arachidicola S. Hori (Berk and M. A. Curtis) and late leaf spot (LLS) caused by Cercosporidium personatum Deighton [10]. Early leaf spot is characterized by light brown spots surrounded by yellow halo, while spots of late leaf spot are black and usually without yellow halo [11]. ELS and LLS typically occur together, and their spread and severity are influenced by the field cropping history, temperature, and relative humidity [12]. The leaf spot disease epidemics are affected by weather patterns such as hot and wet conditions [13]. Temperatures in the range of 25 to 30°C and high relative humidity favour infection and disease development [14].

Efforts have been directed at chemical control of leaf spot diseases in northern Ghana [6]. However, it has only been partially effective in controlling the disease on farmers’ fields [8] and substantially increases cost of production. The development and adoption of leaf spot resistant cultivars will therefore be a breakthrough to resource poor farmers in the middle- and low-income countries [15] including Ghana who cannot afford chemical control measures.

Genetic variation exists in cultivated groundnut for both ELS and LLS resistance, but the resistant genotypes are generally late maturing [16]. Direct selection for leaf spot resistance in groundnut is also difficult and has been reported to be associated with low yield, poor pod, and kernel characteristics and late maturity [16]. As a result, there is the need to consider other physiological traits that can confer tolerance to the two foliar diseases and enhance pod and haulm yields.

Stay-green is an important trait that allows plants to retain their leaves in an active photosynthetic state when exposed to stress conditions [17]. It has been found to be present in different crops [17] and widely used in breeding for disease resistance [18]. The stay-green trait can be scored on a large number of entries [19] and is associated with other important agronomic and physiological traits. It enables plants to maintain active photosynthesis under drought [20], enhances higher nitrogen concentration in plant organs [21], confers tolerance to drought, heat, cold, pathogens, and resistance to lodging [22, 23], and performs better under low nitrogen conditions [24]. Maintenance of green leaf area through grain filling has been associated with increased grain yield in wheat [25, 26], maize [27], and sorghum [28]. The stay-green trait occurs at three levels in plants, namely, the cell, leaf, and whole plant levels [29]. However, green leaf area at physiological maturity has proven to be a good measure of stay-green [30, 31] with the potential of enhancing foliar disease resistance in groundnuts.

The objectives of this study were to determine the (i) genetic control of the stay-green trait in groundnut and (ii) association between stay-green trait and leaf spots severity in groundnut.

2. Materials and Methods

2.1. Site, Plant Materials, and Design of Experiment

The experiment was carried out at the research station of Council for Scientific and Industrial Research-Savanna Agricultural Research Institute (CSIR-SARI), Tamale, Ghana, located at 09° 25′ 41″ N, 00° 58′ 42″ W and altitude of 183 m above sea level. The study area is characterized by a relatively dry climate with a unimodal rainfall ranging between 900 and 1200 mm annually. The rainy season begins in May and ends in October with few scattered precipitation in November. The soils of the area are Ferric Luvisols of the Tingoli series [32, 33].

A total of 25 advanced breeding lines of groundnut with varied levels of tolerance to leaf spot diseases were selected from the germplasm collection at the CSIR-SARI (Table 1). These lines comprised of four (4) released varieties and twenty-one (21) advanced breeding lines assembled from ICRISAT EIR in Mali and INERA in Burkina Faso.

Table 1: Genotypes used in the study and their characteristics and sources where they were obtained.

Genotypes
Attributes
Source

NKATIESARI
Medium maturity, resistant to ELS and LLS
SARI, Ghana

YENYAWOSO
Early maturity, ELS and LLS susceptible
SARI, Ghana

KPANIELLI
Late maturity, ELS and LLS resistance
SARI, Ghana

CHINESE
Early maturity, susceptible to ELS and LLS
SARI, Ghana

GK 7
Late maturity, ELS and LLS resistance
IER-Burkina Faso

GAF 1665
Late maturity, ELS and LLS resistance
SARI, Ghana

GAF 1723
Late maturity, ELS and LLS resistance
SARI, Ghana

SUMNUT 23
Medium maturity, ELS and LLS tolerance
Nigeria

ICGV 00064
Late maturity, ELS and LLS resistance
ICRISAT, Mali

ICGV-IS 08837
Medium maturity, ELS and LLS tolerance
ICRISAT, Mali

ICGV-IS 13015
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13018
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13041
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13045
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13052
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13071
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13078
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13079
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13081
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13086
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13110
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13113
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13114
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICGV-IS 13998
Medium maturity, foliar disease tolerance
ICRISAT, Mali

ICG 7878
Late maturity, ELS and LLS resistance
ICRISAT, Mali

ELS: early leaf spot; LLS: late leaf spot.

The study comprised of two parts: (i) evaluation of the genotypes for the stay-green trait and leaf spot (ELS and LLS) severity and (ii) genetic analysis of the selected genotypes for stay-green trait.

2.2. Evaluation of the Genotypes for the Stay-Green Trait and Tolerance to Leaf Spot Diseases

Evaluation of the 25 genotypes for leaf spot disease tolerance was done in the major cropping season when the disease incidence is usually highest. Disease infection was done under natural conditions with spreaders planted at border and between rows to ensure inoculum pressure for the disease development in 2016. To ensure zero incidence of the leaf spot diseases, the genotypes were evaluated for the stay-green trait in the minor season of 2016.

The experiment was laid in a partial lattice design with five blocks replicated three times. A plot comprised of four rows of 4 m long with inter- and intrarow spacing of 0.5 m and 0.1 m, respectively. One seed was planted per hill following the procedure of Naab et al. [7, 8]. The genotypes were grouped into late, medium, and early maturing based on the length of their maturity periods. Hence, planting dates were staggered in the order of late, medium, and early maturing group, respectively, to ensure that their reproductive stages (stage of high disease infection) coincided. Triple superphosphate (TSP) was applied at a rate of 60 kg P₂O₅ ha⁻¹ at two weeks after planting. The experiments were further supplemented with grounded oyster shells at a rate of 200 kg·ha⁻¹ to supply calcium [34].

2.3. Genetic Analysis of the Stay-Green Trait in Groundnut

After the field evaluation, two groundnut genotypes expressing the stay-green trait and resistance to leaf spot diseases (NKATIESARI and ICG 7878) were selected and crossed with two other genotypes, CHINESE and ICGV-IS 13081, that were non-stay-green and susceptible to leaf spot diseases using a biparental mating design. The F₁ progeny from each cross divided into two sets, one set was advanced to F₂, whereas the other set was saved for field evaluation.

The parents, F₁ and F₂, were evaluated for leaf spot severity and the stay-green trait during the major and minor seasons, respectively, in 2017. Spreaders were used to enhance the disease inoculum pressure on the disease evaluation plots. The experiment was arranged in a randomized complete block design (RCBD) with three replications. Single row plots of 2 m length were used with inter- and intrarow spacing kept at 0.5 m and 0.1 m, respectively.

2.4. Data Collection

Starting from pod initiation to physiological maturity visual, scoring for severity of ELS and LLS infection and stay-green were carried out at two weeks intervals. The severity of ELS and LLS infection was scored on a scale of 1 to 9 with 1 being completely resistant and 9 a dead plant [11]. The severity scores were used to compute the area under disease progress curve (AUDPC) value [35]. The stay-green characteristic of the genotypes was scored on a scale of 1 to 5 based on the proportion of the total leaf area that had senesced with 1 being no leaf senescence and 5 completely senesced plant [36]. The stay-green scores were used to compute the leaf area under greenness (LAUG) values [18]. Lower values of AUDPC and LAUG represent higher disease tolerance (lower disease severity) and stay-green in groundnut, respectively.

At pod initiation, data were also collected on leaf chlorophyll (SCMR) using a chlorophyll meter (TYS-A), and number of green leaves and leaf area (LA, cm²) using a leaf area meter (YMJ-B). In measuring SCMR, second fully opened leaves were clipped with the chlorophyll meter until readings stabilized and recorded. The leaves used to measure the SCMR were plucked for immediate leaf area measurement in the lab. Pod yield (PY, t·ha⁻¹) and reduction in pod yield (RPY, t·ha⁻¹) due to disease were also recorded at maturity. All data were taken on five (5) randomly selected plants.

AUDPC, LAUG, and RPY were computed using the formulae below:

where Yi is the disease level at time ti, t(i+1) − ti is the time in days between two sequential disease/stay-green scores, Si is the visual score at time ti, PYdfp is the pod yield on disease-free plot, and PYdp is the pod yield on disease plot.

2.5. Data Analysis

Statistical analysis was done using the R statistical software version 3.5.1 [37]. Using the lme4 package [38], a linear mixed effect model was fitted by the restricted maximum likelihood (REML) procedure to determine genotypic effects using the equation below:

where , μ, , , , and , denote the observation on genotype i in block j of replication k, grand mean, effect of replication k, effect of block j nested within replication k, effect of genotype i, and the residual effect, respectively.

Replicates, blocks nested within replicates, and the residual effect were all considered as random effects and genotypes as fixed effect. Fixed effect estimates were compared using t-tests based on Satterthwaite’s method for correcting degrees of freedom for Levene’s test of homogeneity of variance [39]. Effect comparison was done using the lmerTest package [40]. CHINESE, which is the most cultivated groundnut variety in Ghana’s guinea savanna agroecology, was set as the intercept using the “relevel()” command of R.

Based on the scale used in scoring stay-greenness, if a genotype has LAUG score of between 1 and 28, it was regarded as stay-green, between 29 and 42 as moderately stay-green, while between 43 and 70 as non-stay-green [36]. The genotypes were assigned to the various stay-green classes (stay-green, moderately stay-green, and non-stay-green) using the LAUG scores. The different classes were compared using variance component analysis and the comparison was done with the agricolae package [41] of R. To confirm the influence of stay-greenness on leaf spot tolerance, principal component analysis (PCA) was computed for the AUDPC scores of ELS and LLS using the vegan package [42] of the R statistical software.

Coefficients of relationship between pod yield, LAUG, SCMR, LA, ELS, and LLS AUDPC were estimated based on Pearson’s correlation criteria, while boxplot analysis was used to plot mean leaf chlorophyll content of the genotypes against growth stage to understand the variation of progress of leaf chlorophyll degradation among genotypes till the reproductive stage.

For the genetic analysis, the chi-square test was used to determine if the ratios of segregations observed at F₂ fitted expected Mendelian ratios. Broad and narrow sense heritability were estimated using the variances from biparental mating design (BIP) of parents and offsprings [43] (Table 2):

Table 2: Variance components for biparental mating design.

Sources of variation
df
Ms
EMS

Between families

MS₁

Within families

MS₂

Total

—
—

n: number of parents sampled per cross; r: number of individuals sampled per cross; : between family variance; : within family variance; MS₁: between family mean square; MS₂: within family mean square.

Narrow and broad sense heritabilities were estimated as shown in the following equations [44]:

where h² is the narrow sense heritability, H² is the broad sense heritability, VA is the additive variance, VD is the dominance variance, VEC is the environmental variance among families, and VEW is the environmental variance within families.

3. Results

3.1. Variation of Area under Disease Progress Curve for Leaf Spots and Leaf Area under Greenness among Groundnut Genotypes

The genotypes evaluated differed significantly () for leaf spot disease incidence and severity (Table 3). CHINESE had the highest AUDPC for ELS, but the severity was similar to that of ICGV-IS 13081, ICGV-IS 08837, ICGV-IS 13113, ICGV-IS 13114, ICGV-IS 13110, ICGV-IS 13018, ICGV-IS 13078, ICGV-IS 13041, and SUMNUT 23, while NKATIESARI expressed the lowest AUDPC for ELS (Table 3).

Table 3: Area under disease progress curve for early leaf spot (ELS AUDPC) and late leaf spot (LLS AUDPC) diseases and leaf area under greenness (LAUG) of 25 groundnut genotypes evaluated under disease and disease-free conditions in 2017.

Genotypes
ELS AUDPC
LLS AUDPC
LAUG

Estimate
Std. error
Sig
Estimate
Std. error
Sig
Estimate
Std. error
Sig

CHINESE (intercept)
215.80
11.71

205.01
16.54

58.54†
3.41

GAF 1665
−96.61
16.56

−85.22
20.68

−40.43§
4.17

GAF 1723
−88.57
16.48

−63.45
20.31

−35.69§
4.17

GK 7
−57.81
16.56

−30.56
20.68
ns
−38.02§
4.17

ICG 7878
−91.11
16.55

−82.23
20.66

−34.32§
4.14

ICGV-IS 00064
−73.68
16.56

−50.57
20.71

−39.74§
4.14

ICGV-IS 08837
−8.20
16.56
ns
−12.04
20.70
ns
−11.39†
4.14

ICGV-IS 13015
−56.44
16.56

−46.67
20.71

−24.16‡
4.17

ICGV-IS 13018
−23.36
16.48
ns
−12.13
20.29
ns
−22.17‡
4.14

ICGV-IS 13041
−24.67
16.56
ns
−14.66
20.68
ns
−19.97‡
4.17

ICGV-IS 13045
−42.71
16.48

−65.84
20.30

−20.59‡
4.17

ICGV-IS 13052
−40.05
16.48

−50.20
20.27

−22.10‡
4.17

ICGV-IS 13071
−37.77
16.41

−49.38
19.93

−18.94‡
4.14

ICGV-IS 13078
−32.48
16.55
ns
−43.89
20.67

−22.86‡
4.17

ICGV-IS 13079
−33.39
16.48

−46.41
20.29

−22.65‡
4.14

ICGV-IS 13081
−1.71
16.56
ns
−12.23
20.69
ns
−14.28†
4.14

ICGV-IS 13086
−41.75
16.41

−50.29
19.93

−26.01‡
4.14

ICGV-IS 13110
−21.57
16.56
ns
−12.70
20.68
ns
−24.91‡
4.17

ICGV-IS 13113
−17.95
16.55
ns
−5.11
20.65
ns
−25.81‡
4.17

ICGV-IS 13114
−16.82
16.55
ns
−12.25
20.66
ns
−29.58§
4.14

ICGV-IS 13998
−48.33
16.49

−46.12
20.34

−32.53§
4.14

KPANIELI
−69.80
16.49

−50.55
20.32

−35.14§
4.14

NKATIESARI
−98.33
16.49

−81.12
20.34

−40.77§
4.17

SUMNUT 23
−27.08
16.55
ns
9.59
20.67
ns
−14.00†
4.14

YENYAWOSO
−42.18
16.56

−63.81
20.69

−17.98‡
4.17

, , and indicate significance at 0.05, 0.01, and 0.001 levels of probability, respectively. ns: not significant. LLS: late leaf spot; ELS: early leaf spot; AUDPC: area under disease progress curve; LAUG: stay-green trait. § indicates stay-green genotype. ‡ indicates moderately stay-green genotype. † indicates non-stay-green genotype.

SUMNUT 23 had the highest AUDPC for LLS but was similar () to that of CHINESE (Table 3). The score of CHINESE, however, did not differ statistically for LLS from that of ICGV-IS 13113, ICGV-IS 13110, ICGV-IS 08837, ICGV-IS 13041, ICGV-IS 13114, ICGV-IS 13018, and ICGV-IS 13081. The least AUDPC for LLS was expressed by ICG 7878 and GAF 1665.

Furthermore, CHINESE had the highest leaf area under greenness (LAUG) (58.54, ) followed by ICGV-IS 08837, while NKATIESARI had the lowest LAUG (Table 3). Among the 25 genotypes tested, nine were categorized as stay-green, 12 moderately stay-green, and only four as non-stay-green (Table 3). The stay-green genotypes consisted of NKATIESARI, ICG 7878, GAF 1665, GAF 1723, GK 7, ICGV 00064, ICGV-IS 13114, ICGV-IS 13998, and KPANIELLI; the moderately stay-green genotypes were ICGV-IS 13015, ICGV-IS 13018, ICGV-IS 13041, ICGV-IS 13045, ICGV-IS 13052, ICGV-IS 13071, ICGV-IS 13078, ICGV-IS 13079, ICGV-IS 13086, ICGV-IS 13110, ICGV-IS 13113, and YENYAWOSO; while CHINESE, ICGV-IS 13081, ICGV-IS 08837, and SUMNUT 23 were considered as non-stay-green (Table 3).

3.2. Chlorophyll Content, Leaf Area (LA), Leaf Number, Pod Yield, and Reduction in Pod Yield due to Disease of Groundnut

Leaf chlorophyll content measured on genotypes under disease-free conditions at pod initiation and midpod filling was highest () in NKATIESARI and GAF 1665, compared to CHINESE (Table 4). CHINESE had lower leaf chlorophyll than GAF 1723, KPANIELLI, NKATIESARI, and SUMNUT 23 at pod initiation, while KPANIELLI, NKATIESARI, and SUMNUT 23 had lower leaf chlorophyll content at midpod filling (Table 4). At physiological maturity, GK 7 had significantly () higher leaf chlorophyll content, while ICGV-IS 08837 had lower leaf chlorophyll than CHINESE, respectively.

Table 4: Leaf chlorophyll content (SCMR) of 25 groundnut genotypes evaluated under disease-free conditions.

Genotypes
SCMR at pod initiation
SCMR at midpod filling
SCMR at physiological maturity

Estimate
Std. error
Sig
Estimate
Std. error
Sig
Estimate
Std. error
Sig

CHINESE (intercept)
26.95
1.70

28.74
1.94

32.68
2.28

GAF 1665
8.00
2.32

7.22
2.24

1.80
2.33
ns

GAF 1723
5.06
2.32

3.31
2.24
ns
2.45
2.33
ns

GK 7
4.25
2.32
ns
1.45
2.24
ns
5.68
2.33

ICG 7878
2.53
2.26
ns
0.83
2.18
ns
2.11
2.27
ns

ICGV-IS 00064
1.39
2.26
ns
−0.04
2.18
ns
0.28
2.27
ns

ICGV-IS 08837
0.49
2.26
ns
−2.39
2.18
ns
−4.93
2.27

ICGV-IS 13015
4.54
2.32
ns
3.45
2.24
ns
1.76
2.33
ns

ICGV-IS 13018
−0.74
2.26
ns
−1.45
2.18
ns
−0.13
2.27
ns

ICGV-IS 13041
1.28
2.32
ns
−2.89
2.24
ns
−3.28
2.33
ns

ICGV-IS 13045
0.42
2.32
ns
0.36
2.24
ns
−0.55
2.33
ns

ICGV-IS 13052
2.79
2.32
ns
0.29
2.24
ns
−4.35
2.33
ns

ICGV-IS 13071
2.88
2.26
ns
0.59
2.18
ns
0.12
2.27
ns

ICGV-IS 13078
0.71
2.32
ns
3.58
2.24
ns
0.18
2.33
ns

ICGV-IS 13079
2.14
2.26
ns
0.87
2.18
ns
−0.27
2.27
ns

ICGV-IS 13081
3.44
2.26
ns
2.32
2.18
ns
1.54
2.27
ns

ICGV-IS 13086
1.72
2.26
ns
−2.51
2.18
ns
−2.21
2.27
ns

ICGV-IS 13110
4.50
2.32
ns
1.57
2.24
ns
−0.21
2.33
ns

ICGV-IS 13113
4.86
2.32

−0.09
2.24
ns
−1.11
2.33
ns

ICGV-IS 13114
2.95
2.26
ns
0.11
2.18
ns
1.15
2.27
ns

ICGV-IS 13998
1.69
2.26
ns
−0.52
2.18
ns
−3.28
2.27
ns

KPANIELLI
6.52
2.26

5.25
2.18

3.78
2.27
ns

NKATIESARI
8.21
2.32

4.74
2.24

2.42
2.33
ns

SUMNUT 23
6.22
2.26

5.71
2.18

2.57
2.27
ns

YENYAWOSO
3.71
2.32
ns
1.93
2.24
ns
−2.32
2.33
ns

, , and indicate significance at 0.05, 0.01, and 0.001 levels of probability, respectively. ns: not significant. SCMR: leaf chlorophyll content.

Under disease conditions, GK 7 had the highest leaf chlorophyll content at pod initiation which was significantly () different from that of CHINESE (Table 5). Also, GAF 1665, GAF 1723, and SUMNUT 23 all had higher leaf chlorophyll than CHINESE. At midpod filling, all the genotypes were similar in terms leaf chlorophyll content except ICGV-IS 13052 which had significantly () lower chlorophyll content than that of CHINESE (Table 5). At physiological maturity, NKATIESARI had the highest leaf chlorophyll content under disease conditions which was significantly () different from that of CHINESE. GAF 1665, GK 7, ICG 7878, ICGV-IS 13015, ICGV-IS 13113, and KPANIELI had higher leaf chlorophyll content than that of CHINESE (Table 5).

Table 5: Leaf chlorophyll content (SCMR) of 25 groundnut genotypes evaluated under disease conditions.

Genotypes
SCMR at pod initiation
SCMR at midpod filling
SCMR at physiological maturity

Estimate
Std. error
Sig
Estimate
Std. error
Sig
Estimate
Std. error
Sig

CHINESE (intercept)
26.40
1.515

26.34
1.690

26.38
2.601

GAF 1665
3.78
1.672

2.80
2.361
ns
5.12
2.080

GAF 1723
4.11
1.616

0.90
2.298
ns
3.72
2.029
ns

GK 7
5.19
1.675

1.62
2.363
ns
4.19
2.081

ICG 7878
1.42
1.667
ns
−0.81
2.356
ns
4.70
2.076

ICGV-IS 00064
3.03
1.680
ns
1.30
2.368
ns
2.19
2.085
ns

ICGV-IS 08837
−2.23
1.677
ns
−3.69
2.366
ns
−2.19
2.083
ns

ICGV-IS 13015
1.66
1.682
ns
−1.75
2.369
ns
4.24
2.086

ICGV-IS 13018
1.13
1.611
ns
−3.68
2.294
ns
1.40
2.026
ns

ICGV-IS 13041
0.42
1.674
ns
−3.32
2.363
ns
0.42
2.081
ns

ICGV-IS 13045
1.56
1.613
ns
−3.98
2.295
ns
2.48
2.027
ns

ICGV-IS 13052
−0.45
1.605
ns
−4.78
2.288
∗
−2.71
2.022
ns

ICGV-IS 13071
0.01
1.558
ns
−2.08
2.233
ns
3.06
1.977
ns

ICGV-IS 13078
−1.92
1.671
ns
−3.25
2.360
ns
−0.14
2.079
ns

ICGV-IS 13079
1.18
1.612
ns
−1.52
2.294
ns
2.56
2.026
ns

ICGV-IS 13081
−1.29
1.676
ns
−1.93
2.365
ns
1.67
2.083
ns

ICGV-IS 13086
0.64
1.557
ns
−4.35
2.232
ns
1.01
1.977
ns

ICGV-IS 13110
1.29
1.674
ns
−3.60
2.363
ns
1.25
2.081
ns

ICGV-IS 13113
1.38
1.666
ns
−0.68
2.355
ns
4.24
2.076

ICGV-IS 13114
−1.18
1.666
ns
−2.37
2.356
ns
0.45
2.076
ns

ICGV-IS 13998
−0.17
1.626
ns
−3.14
2.306
ns
−0.48
2.035
ns

KPANIELI
1.11
1.622
ns
−0.41
2.303
ns
4.95
2.032

NKATIESARI
3.07
1.626
ns
2.67
2.306
ns
6.22
2.035

SUMNUT 23
4.09
1.671

−1.64
2.360
ns
0.97
2.079
ns

YENYAWOSO
1.62
1.675
ns
−1.94
2.364
ns
0.29
2.082
ns

, , and indicate significance at 0.05, 0.01, and 0.001 levels of probability, respectively. ns: not significant. SCMR: leaf chlorophyll content.

The total number of green leaves per plant varied () among the genotypes. GAF 1665, GAF 1723, GK 7, ICG 7878, ICGV-IS 00064, KPANIELI, and NKATIESARI had significantly () higher number of green leaves than CHINESE at pod initiation (Table S1). At physiological maturity, CHINESE had similar number of green leaves compared to most genotypes. However, ICG 7878, NKATIESARI, KPANIELI, ICGV-IS 13114, ICGV-IS 13045, ICGV-IS 13015, ICGV-IS 00064, GAF 1665, GAF 1723, and GK 7 had significantly () higher number of green leaves.

Under disease-free conditions, genotypes YENYAWOSO and CHINESE had the highest number of leaves at pod initiation and physiological maturity, respectively (Table S2). On the contrary, ICGV-IS 13015, ICGV-IS 13071, ICGV-IS 13079, ICGV-IS 13086, and ICGV-IS 13113 had lower green leaf number than CHINESE at pod initiation. At physiological maturity , ICGV-IS 13045 and ICGV-IS 13114 were the only two genotypes with similar number of leaves () as CHINESE. The rest of the genotypes had significantly () lower leaf number than that of CHINESE (Table S2). Furthermore, genotype CHINESE had the highest leaf area (LA) at pod initiation but similar to that of ICGV-IS 13081, ICGV-IS 13086, ICGV-IS 13018, ICGV-IS 13041, ICGV-IS 13052, ICGV-IS 13110, ICGV-IS 13114, ICGV-IS 08837, ICGV-IS 13113, and ICGV-IS 13079 (Table S2). However, it had a leaf area which was higher than that of all the other genotypes including ICG 7878 and NKATIESARI.

When plants were infected by the leaf spot diseases, CHINESE recorded the least pod yield of 2.23 t·ha⁻¹ while NKATIESARI gave 6.18 t·ha⁻¹ as the highest (Table S3). Under disease-free conditions, CHINESE and NKATIESARI gave similar pod yields of about 7 t·ha⁻¹. The reduction in pod yield due to disease was highest in CHINESE (4.95 t·ha⁻¹) which was about 64.54% of pod yield obtained under disease-free conditions (Table S3).

3.3. Relationship between the Stay-Green Trait (LAUG), Leaf Spot Severity (AUDPC), Leaf Chlorophyll Content (SCMR), Leaf Area (LA), and Pod Yield

There were significant correlations among all the traits considered (Table 6). Pod yield had negative correlation with LAUG (r = −0.68, ), ELS AUDPC (r = −0.62, ), LLS AUDPC (r = −0.41, ), and LA (r = −0.68, ). Pod yield, however, had strong and positive correlation with SCMR (r = 0.70, ) at pod initiation, midpod filling (r = 0.68, ) and physiological maturity (r = 0.58, ).

Table 6: Correlation between pod yield, SCMR, LA, ELS AUDPC, and LLS AUDPC.

SCMR PI
SCMR MPF
SCMR PM
Pod yield
LLS AUDPC
ELS AUDPC
LA PI

LAUG
−0.72
−0.74
−0.84
−0.68
0.63
0.82
0.63

SCMR PI

0.92
0.73
0.70
−0.48
−0.8
−0.79

SCMR MPF

0.78
0.68
−0.63
−0.86
−0.86

SCMR PM

0.58
−0.59
−0.75
−0.59

Pod yield

−0.41
−0.62
−0.68

LLS AUDPC

0.85
0.54

ELS AUDPC

0.79

, , and indicate significance at 0.05, 0.01, and 0.001 levels of probability, respectively. SCMR: leaf chlorophyll content; LLS: late leaf spot; ELS: early leaf spot; AUDPC: area under disease progress curve; LAUG: stay-green trait; PI: pod initiation, MPF: midpod filling; PM: physiological maturity.

On the contrary, LAUG had strong and positive associations with LA at pod initiation (r = 0.63, ), ELS (r = 0.82, ), and LLS (r = 0.63, ) AUDPCs (Table 6). Also, LA at pod initiation had positive correlations with ELS (r = 0.79, ) and LLS (r = 0.54, ) AUDPCs.

Results from the principal component analysis conducted using the AUDPCs of ELS and LLS gave clusters of genotypes that were similar to the stay-green (LAUG) classes observed in Table 3 (Figure 1). Cluster “A” was made up of genotypes that had stay-green except ICGV-IS 13015 which expressed moderately stay-green based on the LAUG procedure. Clusters “B” and “C” were made up of genotypes with moderately stay-green, while cluster “D” consisted of non-stay-green genotypes (Figure 1).

Figure 1: A plot of principal component analysis using the AUDPCs of ELS and LLS. “A,” “B and C,” and “D” denote stay-green, moderately stay-green, and non-stay-green clusters, respectively.

Using LAUG as a stay-green criterion to group the germplasm, nine genotypes were found to be stay-grain (SG), twelve moderately stay-green (MSG), and four non-stay-green (NSG) (Tables 3 and 7). Variance component analysis of the stay-green classes showed significant () differences among the genotypes for LAUG, ELS AUDPC, LLS AUDPC, and pod yield. The stay-green class had the lowest LAUG, ELS AUDPC, LLS AUDPC, and the highest pod yield (Table 7), while the non-stay-green class recorded the highest LAUG, ELS AUDPC, LLS AUDPC, and the lowest pod yield. The moderately stay-green class of genotypes was in between the two extreme classes (Table 7).

Table 7: Comparison of different stay-green classes for pod yield, LAUG, ELS AUDPC, and LLS AUDPC.

Stay-Green Classes
No. of genotypes
LAUG
ELS AUDPC
LLS AUDPC
Pod yield (t·ha⁻¹)

Stay-green (SG)
9
22.17c
144.80b
150.83b
4.83a

Moderately stay-green (MSG)
12
36.17b
181.13a
165.77b
3.61b

Non-stay-green (NSG)
4
49.00a
206.43a
200.12a
3.19b

Means followed by different letters are significantly different at 0.05 probability level. LAUG: leaf area under greenness; AUDPC: area under disease progress curve; ELS: early leaf spot; LLS: late leaf spot.

3.4. Genetic Analysis of the Stay-Green Trait

3.4.1. LAUG of Parents and F₁ Generations, Segregation Ratios at F₂, and Heritability Estimates of LAUG in the Population

To understand the genetic basis of the stay-green trait, two stay-green and two non-stay-green genotypes were crossed for further analysis. Results of field evaluation of the parents together with the progeny showed that CHINESE and ICGV-IS 13081 non-stay-green parents had significantly () the highest mean LAUG compared to that of NKATIESARI and ICG 7878 (Table 8). F₁ from ICGV-IS 13081 × NKATIESARI and CHINESE × ICG 7878 crosses designated as SARGV 007 and SARGV 006, respectively, differed statistically from either parents and among themselves. Based on the stay-green classification criteria, SARGV 006 was classified as stay-green, while SARGV 007 as moderately stay-green (Table 8).

Table 8: Leaf area under greenness of parents, F₁s, and estimates of genetic variance components and heritability for stay-green trait.

Means genotypes
Mean LAUG
Variance components and heritability

Genetic parameter
LAUG

CHINESE
42.00 ± 1.16a
Phenotypic variance (VP)
22.16

ICGV-IS 13081
42.00 ± 0.01a
Environmental variance (VE)
3.17

SARGV 007 (F₁)
32.67 ± 0.73b
Genetic variance (VG)
18.98

SARGV 006 (F₁)
28.00 ± 1.04c
Additive variance (VA)
2.04

NKATIESARI
11.67 ± 1.17d
Dominance variance (VD)
16.94

ICG 7878
10.50 ± 0.01d
Broad sense heritability (H²)
0.86

Midparent value
26.54
Narrow sense heritability (h²)
0.09

Means followed by same letters are not statistically different.

The phenotypic variance was partitioned into the various components (Table 8) to estimate progress that can be realized through breeding. The genetic component of the variation (18.98) was higher than that of the environment (3.17). Dominance was significantly higher (16.94) than the additive (2.04) genetic variances (Table 8). Heritability estimates ranged from a low narrow sense heritability (h², 0.09) to a very high broad sense heritability (H², 0.86).

Generation mean analysis of selected F₁ progeny advanced to F₂ and evaluated for the stay-green trait showed that there was no significant difference () between observed and expected ratios at F₂ based on the chi-square test (Table 9). The F₂ population segregated in the ratio of 1 (stay-green) : 3 (non-stay-green).

Table 9: Proportion of stay-green classes (segregation ratios) at F₂.

Genotype
Observed
Expected

Stay-green
Non-stay-green
Stay-green
Non-stay-green
Total
χ² (1 : 3)
value

SARGV 006-1
2
8
2.5
7.5
10
0.133
0.715

SARGV 008-1
3
10
3.25
9.75
13
0.026
0.873

χ²: chi-square.

4. Discussion

Biotic stresses such as disease infection reduce groundnut yield in many environments. Despite considerable efforts directed at fungicidal control of the disease in the guinea Savanna zone of Ghana [6], there is high incidence of leaf spot diseases on farmers’ fields largely due to partial effectiveness of chemical control measures [8]. As a result, sustained maintenance of genetic progress in the improvement of disease resistance is essential, and this will require the identification and combination of new genetic variation. The AUDPC is a very convenient summary of plant disease epidemics that incorporates initial intensity, the rate parameter, and the duration of the epidemic which determines final disease intensity [45]. Based on the leaf spot severity scores observed in this study, genotypes GAF 1665, GAF 1723, ICG 7878, and NKATIESARI were highly resistant to early and late leaf spot diseases. Also, stay-green (SG), moderately stay-green (MSG), and non-stay-green (NSG) genotype classes were found to have significant AUDPCs for ELS and LLS with SG class having the least values. This result depicts the resistance of the genotypes to leaf spot diseases. The high level of leaf spot tolerance exhibited by the SG class might be due to their leaf characteristics such as thick palisade layer, dark green colour, and small stomata which have all been found to obstruct the growth of spores of Cercospora arachidicola and Cercosporidium personatum [46]. It is therefore not surprising that leaf chlorophyll content at pod initiation, midpod filling and physiological maturity all had strong negative correlation with the AUDPCs of ELS and LLS conferring resistance to the pathogens.

Stay-greenness based on visual score of the proportion of green leaf area maintained at physiological maturity has been used as a criterion for selecting stay-green genotypes in maize [19], sorghum [36], wheat [18, 47], and sunflower [48]. The significant differences observed among the groundnut genotypes for LAUG in this study was due to the varied degrees of leaf senescence at physiological maturity during which the stay-green trait was expressed. The observed genotypic difference in the expression of the trait can be attributed to the different genetic backgrounds of the genotypes. Borrell et al. [28] that the stay-green trait is associated with Stg QTL regulating canopy size through constraining the size of the upper leaves. Genotypes that exhibited lower rates of leaf senescence through physiological maturity (lower LAUG) were also observed to have relatively smaller leave area. Similar clustering patterns were also observed when the genotypes were grouped based on their AUDPC scores for ELS and LLS using principal component analysis as opposed to using LAUG as a stay-green criterion. Although CHINESE had the highest leaf area under greenness (highest rate of leaf senescence) depicting non-stay-greenness, it had the highest number of leaves at pod initiation and physiological maturity under disease-free conditions. This suggests that in the absence of leaf spot disease infections, CHINESE is capable of replacing leaves which have been lost through natural senescence. However, in the presence of leaf spot disease infections, CHINESE loses this ability resulting in a reduced number of leaves at physiological maturity compared to pod initiation stage.

Crop maturity is usually characterized by senescence, chlorophyll loss, and a progressive decline in photosynthetic capacity. However, some genotypes exhibit decreased or delayed chlorophyll catabolism [49] resulting in maintenance of their chlorophyll content for a longer period. This phenomenon was portrayed in the groundnut population used in this study. During the reproductive phase, genotypes that had lower LAUG also had relatively higher mean chlorophyll content at pod initiation, midpod filling, and physiological maturity. Although there was no significant difference among the genotypes for leaf chlorophyll content during the reproductive phase, variation among the genotypes increased as the crops advanced towards physiological maturity with midpod filling being the stage with the highest variance (results not shown). This indicates that some genotypes (non-stay-green) were undergoing rapid leaf chlorophyll catabolism than others (stay-green), and hence, the lack of nonconstant variance across the reproductive stage. These results suggest that the most important stay-green classes (stay-green and non-stay-green) required to make breeding progress are present in the population.

However, the genotypes performed differently under the disease and disease-free conditions in pod yield with CHINESE being the worst affected under the disease conditions but became the best when there was no leaf spot disease infection. The percent reduction in pod yield due to leaf spot diseases in CHINESE was about 65%. This highlights the importance of leaf spot diseases as a major yield reduction stress in groundnut production [4, 5].

The strong positive relationship between LAUG and AUDPC for ELS and LLS suggest the possible influence of the stay-green trait on leaf spot severity. Also, the ability of the AUDPC scores to segregate the genotypes into groups synonymous to those of LAUG further highlights the interplay of these three traits in groundnut. The results agree with findings of different authors [49, 50] who showed that stay-green trait influences different diseases in other crops. For instance, sorghum recombinant inbred lines (RILs) carrying stay-green QTLs (stg1, stg3, or both (stg1 + 3)) expressed high levels of resistance to Macrophomina phaseolina and Fusarium thapsinum [50]. Also, the negative association between LAUG and pod yield means selecting for stay-greenness (lower LAUG) will enhance pod yield. This may be achieved either through reduced disease severity or enhanced photosynthetic activity of the plant via delay in chlorophyll catabolism [49], which results in prolonging the active photosynthetic period. The strong association between LAUG, pod yield, and ELS and LLS AUDPC with leaf chlorophyll content suggests that sustained leaf chlorophyll content during the reproductive phase is essential for maintenance of stay-greenness, higher pod yield, and higher tolerance to leaf spot diseases in groundnut.

The observed significant difference between the stay-green and non-stay-green parents for LAUG suggests that genetic differences existed between the parental lines used for the crosses. The LAUG of the F₁ generation was higher than the midparent value and were closer to that of the non-stay-green parents. It is therefore possible that the allele controlling the non-stay-green trait is partially dominant over the stay-green allele [43]. The 1 : 3 segregation ratio of stay-green to non-stay-green genotypes observed at F₂ also indicates stay-greenness in groundnut is controlled qualitatively by a single recessive gene. The trait can therefore be expressed only when the two alleles are in the same state. Similar findings have been reported in wheat [51] and rice [52]. However, in maize, it has been reported that the stay-green trait is quantitatively inherited with 17 QTLs clustered on four chromosomes accounting for 73.08% of the total genetic variance [53]. The higher broad sense heritability compared to the narrow sense heritability observed for stay-green trait in the current study implies that making selection from the existing population will bring about more genetic advancement than making crosses and selecting from the progenies [44].

5. Conclusion

The stay-green trait (LAUG) had a positive association with ELS and LLS and, hence, has the ability to confer resistance to leaf spot disease in groundnut. Since it is relatively easier to score for this trait on a large number of entries, groundnut breeders can use this trait to select for ELS and LLS resistance in groundnut in areas with low disease pressure. Leaf area at pod initiation and leaf chlorophyll at pod initiation, midpod filling, and at physiological maturity can also be used to select for stay-green, ELS, and LLS resistance since there was a strong association between them. Our results show that stay-green trait in groundnut is under the control of a single recessive gene. Since the genotypes used were advanced breeding lines, which have attained homozygosity at majority of their loci, making selection from the existing population will bring about more genetic gain due to the high broad sense heritability.

Data Availability

Data used to support these findings and the analysis code can be sourced from the corresponding author.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work was supported by the Tropical Legume (TL) III (OPP1114827) and Alliance for a Green Revolution in Africa (AGRA) (2014 PASS 012).

Supplementary Materials

Table S1: number of green leaves (NGL) of 25 groundnut genotypes evaluated under disease conditions. Table S2: leaf area (LA) and number of green leaves (NGL) of 25 groundnut genotypes evaluated under disease-free conditions. Table S3: pod yield and its reduction due to ELS-LLS infection of 25 groundnut genotypes evaluated under disease and disease-free conditions. (Supplementary Materials)

References

S. Nedumaran, P. Abinaya, P. Jyosthnaa, B. Shraavya, P. Rao, and C. Bantilan, Grain Legumes Production, Consumption and Trade Trends in Developing Countries, ICRISAT Research Program, Markets, Institutions and Policies, Patancheru, India, 2015.

J. Pasupuleti, S. N. Nigam, M. K. Pandey, P. Nagesh, and R. K. Varshney, “Groundnut improvement: use of genetic and genomic tools,” Frontiers in Plant Science, vol. 4, p. 23, 2013.

J. Ndjeunga, B. R. Ntare, F. Waliyar et al., “Early adoption of modern groundnut varieties in West Africa,” 2008, http://oar.icrisat.org/2360/.

S. B. Thakur, S. K. Ghimire, N. K. Chaudhary, S. M. Shrestha, and B. Mishra, “Variability in groundnut (Arachis hypogaea L.) to Cercospora leaf spot disease tolerance,” International Journal of Life Sciences Biotechnology and Pharma Research, vol. 2, no. 1, pp. 254–262, 2013.

A. R. Khan, M. Ijaz, I. U. Haq, A. Farzand, and M. Tariqjaved, “Management of Cercospora leaf spot of groundnut (Cercospora arachidicola & Cercosporidium personatum) through the use of systemic fungicides,” Cercetari Agronomice in Moldova, vol. 47, no. 2, pp. 97–102, 2014.

S. K. Nutsugah, M. Abudulai, C. Oti-Boateng, R. L. Brandenburg, and D. L. Jordan, “Management of leaf spot diseases of peanut with fungicides and local detergents in Ghana,” Plant Pathology Journal, vol. 6, no. 3, pp. 248–253, 2007.

J. B. Naab, K. J. Boote, P. V. V. Prasad, S. S. Seini, and J. W. Jones, “Influence of fungicide and sowing density on the growth and yield of two groundnut cultivars,” Journal of Agricultural Science, vol. 147, no. 2, pp. 179–191, 2009.

J. B. Naab, S. S. Seini, K. O. Gyasi et al., “Groundnut yield response and economic benefits of fungicide and phosphorus application in farmer-managed trials in northern Ghana,” Experimental Agriculture, vol. 45, no. 4, pp. 385–399, 2009.

S. Pande, R. Bandyopadhyay, M. Blümmel, J. Narayana Rao, D. Thomas, and S. S. Navi, “Disease management factors influencing yield and quality of sorghum and groundnut crop residues,” Field Crops Research, vol. 84, no. 1-2, pp. 89–103, 2003.

S. C. Leal-Bertioli, A. José, D. M. Alves-Freitas et al., “Identification of candidate genome regions controlling disease resistance in Arachis,” BMC Plant Biology, vol. 9, no. 1, p. 112, 2009.

P. Subrahmanyam, D. McDonald, F. Waliyar et al., “Screening methods and sources of resistance to rust and late leaf spot of groundnut,” 1995, http://oar.icrisat.org/3477/.

A. K. Singh, V. K. Mehan, and S. N. Nigam, “Sources of resistance to groundnut fungal and bacterial diseases: an update and appraisal,” 1997, http://oar.icrisat.org/6676/.

B. B. Shew, M. K. Beute, and J. C. Wynne, “Effects of temperature and relative humidity on expression of resistance to Cercosporidium personatum in peanut,” Phytopathology, vol. 78, p. 493, 1988.

S. N. Nigam, Groundnut at a Glance, ICRISAT, Patancheru, India, 2014.

S. L. Dwivedi, S. N. Nigam, R. Jambunathan, K. L. Sahrawat, G. V. S. Nagabhushanam, and K. Raghunath, “Effect of genotypes and environments on oil content and oil quality parameters and their correlation in peanut (Arachis hypogaea L.),” Peanut Science, vol. 20, no. 2, pp. 84–89, 1993.

C. C. Holbrook and W. Dong, “Development and evaluation of a mini core collection for the U.S. peanut germplasm collection,” Crop Science, vol. 45, no. 4, pp. 1540–1544, 2005.

H. Thomas and C. J. Howarth, “Five ways to stay green,” Journal of Experimental Botany, vol. 51, no. 1, pp. 329–337, 2000.

A. K. Joshi, M. Kumari, V. P. Singh et al., “Stay green trait: variation, inheritance and its association with spot blotch resistance in spring wheat (Triticum aestivum L.),” Euphytica, vol. 153, no. 1-2, pp. 59–71, 2007.

G. Bekavac, B. Purar, M. Stojaković, D. J. Jocković, M. Ivanović, and A. Nastasić, “Genetic analysis of stay-green trait in broad-based maize populations,” Cereal Research Communications, vol. 35, no. 1, pp. 31–41, 2007.

H. Thomas and C. M. Smart, “Crops that stay green,” Annals of Applied Biology, vol. 123, no. 1, pp. 193–219, 1993.

K. D. Subedi and B. L. Ma, “Nitrogen uptake and partitioning in stay-green and leafy maize hybrids,” Crop Science, vol. 45, no. 2, pp. 740–747, 2005.

M. O. Adu, D. L. Sparkes, A. Parmar, and D. O. Yawson, “Stay green in wheat: comparative study of modern bread wheat and ancient wheat cultivars,” ARPN Journal of Agricultural and Biological Science, vol. 6, pp. 16–24, 2011.

S. A. Silva, F. I. F. de Carvalho, J. L. Nedel et al., “Análise de trilha para os componentes de rendimento de grãos em trigo,” Bragantia, vol. 64, no. 2, pp. 191–196, 2005.

M. Antonietta, H. A. Acciaresi, and J. J. Guiamet, “Responses to N deficiency in stay green and non-stay green argentinean hybrids of maize,” Journal of Agronomy and Crop Science, vol. 202, no. 3, pp. 231–242, 2016.

J. T. Christopher, M. Veyradier, A. K. Borrell, G. Harvey, S. Fletcher, and K. Chenu, “Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics,” Functional Plant Biology, vol. 41, no. 11, pp. 1035–1048, 2014.

M. S. Lopes and M. P. Reynolds, “Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology,” Journal of Experimental Botany, vol. 63, no. 10, pp. 3789–3798, 2012.

S. Trachsel, D. Sun, F. M. SanVicente et al., “Identification of QTL for early vigor and stay-green conferring tolerance to drought in two connected advanced backcross populations in tropical maize (Zea mays L.),” PLoS One, vol. 11, no. 3, Article ID e0149636, 2016.

A. K. Borrell, E. J. van Oosterom, J. E. Mullet et al., “Stay‐green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns,” New Phytologist, vol. 203, no. 3, pp. 817–830, 2014.

A. Borrell, G. Hammer, and E. Oosterom, “Stay-green: a consequence of the balance between supply and demand for nitrogen during grain filling?” Annals of Applied Biology, vol. 138, no. 1, pp. 91–95, 2001.

A. K. Borrell, G. L. Hammer, and A. C. L. Douglas, “Does maintaining green leaf area in sorghum improve yield under drought? I. Leaf growth and senescence,” Crop Science, vol. 40, no. 4, pp. 1026–1037, 2000.

M. K. Wanous, F. R. Miller, and D. T. Rosenow, “Evaluation of visual rating scales for green leaf retention in sorghum,” Crop Science, vol. 31, no. 6, pp. 1691–1694, 1991.

W. K. Atakora and P. K. Kwakye, “Carbon dioxide emission from ferric luvisols: the role of mineral nitrogen fertilizers and soil temperature in the Guinea savanna agro-ecological zone of Ghana,” Journal of Agriculture and Ecology Research International, vol. 7, no. 1, pp. 1–17, 2016.

R. Oteng-Frimpong, S. P. Konlan, and N. N. Denwar, “Evaluation of selected groundnut (Arachis hypogaea L.) lines for yield and haulm nutritive quality traits,” International Journal of Agronomy, vol. 2017, Article ID 7479309, 9 pages, 2017.

R. Oteng-Frimpong, Y. B. Kassim, R. Danful, R. Akromah, A. Wireko-Kena, and S. Forson, “Modeling groundnut (Arachis hypogaea L.) performance under drought conditions,” Journal of Crop Improvement, vol. 33, no. 1, pp. 125–144, 2019.

J. E. Van Der Plank, “Dynamics of epidemics of plant disease,” International Journal of Pest Management: Part B, vol. 11, no. 3, pp. 307–317, 1965.

W. Xu, D. T. Rosenow, and H. T. Nguyen, “Stay green trait in grain sorghum: relationship between visual rating and leaf chlorophyll concentration,” Plant Breeding, vol. 119, no. 4, pp. 365–367, 2000.

R Core Team, R: A Language and Environment for Statistical computing, (“Great Truth”), R Foundation for Statistical Computing, Vienna, Austria, 2019.

D. Bates, M. Maechler, B. Bolker et al., Lme4: Linear Mixed-Effects Models Using “Eigen” and S4, 2019.

W.-Y. Loh, “Some modifications of levene’s test of variance homogeneity,” Journal of Statistical Computation and Simulation, vol. 28, no. 3, pp. 213–226, 1987.

A. Kuznetsova, P. B. Brockhoff, and R. H. B. Christensen, LmerTest: Tests in Linear Mixed Effects Models, 2019.

F. de Mendiburu, Agricolae: Statistical Procedures for Agricultural Research, 2019.

J. Oksanen, F. G. Blanchet, M. Friendly et al., Vegan: Community Ecology Package, 2019.

G. Acquaah, Principles of Plant Genetics and Breeding, Blackwell Publishing Ltd, Oxford, UK, 2007.

A. R. Hallauer, M. J. Carena, and J. B. M. Filho, Quantitative Genetics in Maize Breeding, Springer Science & Business Media, Berlin, Germany, 2010.

L. V. Madden, G. Hughes, and F. Van Den Bosch, The Study of Plant Disease Epidemics, American Phytopathological Society, Saint Paul, MN, USA, 2007.

T. A. Coffelt and D. M. Porter, “Field screening of reciprocal chico × florigiant peanut populations for resistance to leafspot in Virginia,” Peanut Science, vol. 13, no. 2, pp. 57–60, 1986.

M. Kumari, R. N. Pudake, V. P. Singh, and A. K. Joshi, “Association of staygreen trait with canopy temperature depression and yield traits under terminal heat stress in wheat (Triticum aestivum L.),” Euphytica, vol. 190, no. 1, pp. 87–97, 2013.

A. J. de la Vega, M. A. Cantore, M. M. Sposaro, N. Trápani, M. López Pereira, and A. J. Hall, “Canopy stay-green and yield in non-stressed sunflower,” Field Crops Research, vol. 121, no. 1, pp. 175–185, 2011.

H. Thomas and H. Ougham, “The stay-green trait,” Journal of Experimental Botany, vol. 65, no. 14, pp. 3889–3900, 2014.

A. Adeyanju, J. Yu, C. Little et al., “Sorghum RILs segregating for stay-green QTL and leaf dhurrin content show differential reaction to stalk rot diseases,” Crop Science, vol. 56, no. 6, pp. 2895–2903, 2016.

S. A. Silva, F. I. F. de Carvalho, V. de R. Caetano et al., “Genetic basis of stay-green trait in bread wheat,” Journal of New Seeds, vol. 2, no. 2, pp. 55–68, 2001.

K.-W. Cha, Y.-J. Lee, H.-J. Koh, B.-M. Lee, Y.-W. Nam, and N.-C. Paek, “Isolation, characterization, and mapping of the stay green mutant in rice,” Theoretical and Applied Genetics, vol. 104, no. 4, pp. 526–532, 2002.

P. R. Belícuas, A. M. Aguiar, D. A. V. Bento, T. M. M. Câmara, and C. L. de Souza Junior, “Inheritance of the stay-green trait in tropical maize,” Euphytica, vol. 198, pp. 163–173, 2014.