A survey was conducted in the southern region of Mozambique to: (1) determine farmers' perceptions of the main constraints limiting pea production and identify preferences regarding cultivars and traits, (2) the variability of selected to determine chickpea germplasm for drought tolerance, (3) to determine the gene action controlling drought tolerance, yield, and yield components in cowpea, and (4) to assess the genotype x environment interaction and yield stability of cowpea genotypes under drought-stressed and non-stressed conditions . The major constraints contributing to the low yields of cowpea in the country include biotic stress (insect pests, nematodes, diseases and weeds), abiotic stress (low soil fertility and drought), poor agronomic practices, poor seed quality, poor extension services, cultivation of low-yielding and unimproved cultivars and limited breeding work (INIA, 2003).
Introduction
World cowpea production and major constraints
Drought: definition, types of drought and progress made in drought research
Leaf area is reduced through reduced leaf area initiation (Clarke and Durdley, 1981), reduced leaf expansion due to extreme sensitivity of cell expansion to reduced turgor (Hsiao, 1973; Akeampong, 1986) and/or enhanced leaf senescence (Gardner et al. , 1985; Ludlow and Muchow, 1990). Unfortunately, early erect and more synchronously flowering cultivars are damaged by mid-season drought (Thiaw et al., 1993) due to the detrimental effects of drought on pod set and pod filling of erect.
Drought Tolerance: definition and mechanisms
Physiological aspects of drought tolerance such as stomatal conductance, osmotic adjustment, carbon isotope discrimination, assimilation rates, transpiration and water relations have been investigated in detail (Turk and Hall, 1980a,c; Hall and Patel, 1985; Itani et al., 1992b). Hall et al., 1997; Chiulele and Agenbag, 2004). Morphological aspects of drought tolerance have been conducted on root traits (Matsui and Singh, 2003) and on shoots (Mai-Kodomi et al., 1999a; Singh et al., 1999b).
Gene action controlling quantitative traits
Estimating gene action
Genotype by environment interaction (G×E) is the differential genotypic expression of the change in the environment (Yan and Hunt, 1998; Annicchiarico, 2002). Recently, the genotype plus genotype by environment interaction, commonly known as GGE biplot, has been proposed (Yan et al., 2000;
Farmers involvement in breeding programmes
The "who won-where" pattern allows the identification of mega-environments provided it is repeatable over years (Yan et al., 2001). In cowpea, Kitch et al. 1998) suggested that the use of participatory methods to select new improved varieties would improve the efficiency and effectiveness of the selection process because the intensities of selection used by farmers were similar to those used by breeders.
A stability analysis of flowering time as a screen for sensitivity to temperature and photoperiod in cowpea (Vigna unguiculata). Genotype × environment interaction in carbon isotope discrimination and seed yield in cowpea (Vigna unguiculata L. Walp.).
Introduction
Participatory methods have been widely used in agricultural research and have proven successful in obtaining crucial information that can contribute to increased crop productivity and the adoption of new, improved varieties (Sperling et al., 1993). In cowpea, Kitch et al. 1998) indicated that using participatory varietal selection to select new, improved varieties would improve the efficiency and effectiveness of the selection process, as the selection intensities used by farmers were comparable to what would be used by breeders used (Kitch et al., 1998). .
Materials and Methods
- Participatory Rural Appraisal (PRA)
- Participatory variety selection (PVS)
- Market survey of different cowpea seed types evaluated
- Data analysis
Bambey-21 Senegal Medium seed size and white seed, upright and firm Xingove Moz Large seed size, variegated, sprawling, high yield of tender leaves FN-1-13-04 Moz Large seed size, cream, sprawling, high yield of tender leaves INIA-41 Moz Large seed size, cream colored, elongated. Timbawene Creme Moz Large seed size, cream colored, sprawling, high yield of tender leaves UCR-P-24 UCR Large seed size, black eyed, upright, determined, early.
Results
- Importance of cowpea production in three districts of southern Mozambique
- Cowpea types grown by farmers in three districts of southern Mozambique
- Cowpea production constraints in the three districts of southern Mozambique
- Farmers’ selection criteria of cowpea varieties
- Ranking of twelve cowpea varieties in southern Mozambique
- Prices of three cowpea seed types in metical (Mt) at Maputo markets
There were strong, positive and significant correlations among districts in the ranking of major constraints to cowpea production (Table 2.6), indicating that the order was consistent among the three districts. Classification of cultivars based on seed traits was consistent among the three districts, as correlations among the three districts were strong, positive, and significant (Table 2.10).
Discussion
Farmers used yield and yield-related traits as the main criteria to select cowpea varieties. In a conventional breeding program, yield and yield-related traits are the most important selection criteria.
Conclusions
Farmers' ratings of cowpea varieties in the field were consistent with yield performance, except that Tete-2 was not among the top five genotypes despite its high yield. The fact that Tete-2 was not ranked among the top five varieties besides its high grain yield and the ranking of UCR-P-24 and Sh-50 as the most preferred varieties while they were not known locally indicated that the farmers uses criteria other than yield to select a variety.
Multivariate analysis was performed on stressed and non-stressed yield data and quantitative indices of drought tolerance were calculated (tolerance index, mean productivity, geometric mean productivity, stress intensity, stress sensitivity index and drought tolerance index). stress). Drought stress reduced yields of early and late genotypes, but genotypes responded differently to imposed drought stress, indicating that genetic variability for drought tolerance existed.
Introduction
Stress tolerance index has been indicated as the most suitable for screening genotypes for drought tolerance because it enables the identification of high yielding and drought tolerant genotypes (Fernandez, 1992). Very few studies have used quantitative indices of stress tolerance to assess drought tolerance on cowpea.
Materials and Methods
Site description and climatic conditions during the experimental period
Trial description and data collection
Data analyses
Where: µ is the overall mean, G are genotype effects, W are the effects of water regime, G×W are the interaction effects of genotype by water regime, Linear_r and Linear_c are the spatial adjustments for the rows and columns, respectively, r are the row effects, c are the column effects, rR is the interaction effects for row by replication, R is the replication effects, cR is the interaction effects for column by replication, rcR is the interaction effects of rows, columns, and replications, ε is the random term. Where: and is the yield of each genotype under drought-stressed and non-stressed conditions and and is the average yield of all genotypes under drought-stressed and non-stressed conditions.
Results
Results of 136 early maturing cowpea genotypes
Genotypes that combined lower tolerance index and stress sensitivity index and higher average productivity and stress tolerance index were drought tolerant. Correlation analysis between quantitative indices of stress tolerance and yield in stressed and unstressed conditions is shown in table 3.6.
Results of 80 late maturing cowpea genotypes
In contrast, genotypes combining the highest tolerance index and stress susceptibility index and the lowest average productivity or stress tolerance index were susceptible. The results showed that the stress tolerance index is strongly and positively related to unstressed yield, stressed yield, average productivity and geometric mean productivity.
Discussion
The correlations between stressed and unstressed yields were 0.71 and 0.51 for early and late genotypes, respectively. Fernandez (1992) also indicated that selecting the stress tolerance index would improve yield under both stressed and unstressed environments.
Conclusion
Selection for drought tolerance would be possible by exploiting the 'stay-green' trait under drought-stressed conditions and would be effective in early segregating generations. The most desirable genotypes to use as parents in a breeding program are INIA-41 for drought tolerance and IT93K-503-1 for drought tolerance and yield.
Introduction
Various criteria for evaluating cowpea for drought tolerance have been used and have been found to be useful. 2008) used visual symptoms of wilting, plant death and recovery as criteria for assessing genotypic differences in drought tolerance.
Materials and methods
- Site characteristics and environmental conditions during the experiments
- Cowpea germplasm
- Diallel mating design, field evaluation and data collection
- Data analysis
Where Yijk is the mean of ith or jth parental line or the F2 obtained by crossing ith and jth lines, µ is the grand mean, ri is the effect of ith replication, gjk is the effect of ikth genotype, (gr)ijk is the interaction of jkth genotype with ri replication, eijk is the experimental error specific to ijkth observation. Where Yijk is the mean phenotypic value, µ is the general mean, gi and gj are the general combining ability (GCA) effects of ith and jth lines respectively, Sij is the specific combining ability (SCA) effect of ijth crosses and eij is the environmental effect relating to ijde individual observation.
Results
- Analysis of variance
- Combining ability analyses
- Performance of parents and F2 populations for stay-green under drought
- Yield performance of parents and F2 populations
- General combining ability for stay-green, yield and yield components
- Phenotypic correlations between yield and yield related traits
Genotype IT93K-503-1 also had positive and significant GCA scores for number of pods per plant along with IT82E-18 and INIA-152. Genotype IT93K-503-1 had highly significant positive GCA effects in the three environments for number of seeds per pod.
Discussion
Drought tolerance assessment using stay-green trait
Considering the above, for genetic improvement for drought tolerance using stay-green as a selection trait, genotypes IT93K-503-1 and INIA-41 may be more desirable to use as parents.
Performance of genotypes based on yield and yield components
Given the moderate magnitude of the GCA:SCA ratio, selection for yield and number of pods per plant would be effective in late-segregating generations when genes are fixed. This implies that this genotype may be the most desirable for yield improvement, but under drought conditions the number of pods per plant should be used as a selection criterion.
Conclusions
Genotype × environment interaction and grain yield stability of pea genotypes in stressed and non-stressed environments in .
Introduction
The GGE biplot is constructed by plotting the two principal components (PC1 and PC2) derived from the singular value decomposition (SVD) of the environment-centered data (GGE matrix) to create three-component matrices; matrix of singular value (string), matrix of eigenvectors of the genotype and matrix of eigenvectors of the environment. Two concepts of stability have been reported, static or biological and dynamic or agronomic stability (Kang, 1998).
Materials and methods
- Site characterization and climatic conditions during the experimental period
- Cowpea germplasm
- Experimental design, field evaluation and data collection
- Data analysis
The polygon is formed by connecting the genotype markers that are furthest from the origin of the biplot so that all other genotypes are included in the polygon. Further from the origin of the biplot in the direction of the AEC ordinate shows greater G×E and reduced stability (Yan, 2002).
Results
Analysis of variance
Yield performance of genotypes within sites, seasons and water regimes and
The grain yield of the 48 genotypes varied between 707 and 2572 Kgha-1 in non-stressed conditions and between 529 and 1696 Kgha-1 in stressed conditions. The highest grain yield under non-impaired conditions was recorded in 2009 main season while it was recorded under non-impaired conditions in 2009 off-season.
The GGE biplot
The environment 2009 off-season non-stressed (D1) was the most discriminating environment followed by the 2010 main season non-stressed (E1) and 2009 off-season stress. The environments most representative of the two mega-environments were Umebluzi-2009-main-season-not-stressed (B11), Umbeluzi-2009-main-season-stressed (B12), Umbeluzi-2009-off-season-not-.
Discussion
Performance of genotypes across sites, seasons and water regime
Given their ability to withstand drought and produce consistent yields over seasons, the genotypes INIA-81D, INIA-24, INIA-5 and INIA-1 would be recommended for specific locations, including those characterized by drought stress. Overall, the genotypes INIA-81D, INIA-24 and INIA-5 would be recommended for wide adaptation due to their drought tolerance combined with less yield variation from season to season and high average site yield.
The GGE biplot
According to this principle, genotypes such as Nhavanca and INIA-51 would be considered stable, followed by INIA-81D, INIA-24, INIA-25 and INIA-5, because they combined high average yield across sites and water regimes and variation low yield throughout. season. Genotypes such as IT82E-18, Namuesse-D, VAR-3A, INIA-36, INIA-12 and Monteiro would be considered the most unstable.
Conclusions
Introduction
Summary of the Major Findings
- Participatory Plant Breeding: Assessment of Farmers’ Perceptions and
- Assessment of cowpea genotypes for variability in drought tolerance
- Gene action controlling drought tolerance, yield and yield related traits
- Genotype × environment interaction and grain yield stability of cowpea
Two hundred and sixteen genotypes were grouped into four groups according to their yield ability under stressed and non-stressed conditions and their drought tolerance. Multivariate analysis using drought-stressed and non-stressed yield and quantitative indices of stress tolerance was a useful method for evaluating the variability of pea genotypes for drought tolerance.
Breeding Implications for the Findings
Conclusions and the Way Forward
