Breeding groundnut for drought tolerance.

Abstract

Groundnut (Arachis hypogaea L.) is one of the world’s most important grain legumes for its quality edible oil and higher protein content. It is the major cash crop in the semiarid tropics where production is mainly under rain-fed condition. Recurrent drought is the major cause of low yields of groundnut in sub-Saharan Africa (SSA). Farmers in SSA grow unimproved groundnut varieties which are vulnerable to drought stress and insect pests and disease attack. Therefore, there is need to develop drought tolerant, locally adapted and high yielding groundnut varieties for sustainable production of the crop. Breeding groundnut for drought tolerance requires inexpensive, reproducible and high throughput screening systems. Understanding the agromorphological, physiological and molecular bases of drought tolerance aid in the development and release of new varieties with drought tolerance. Therefore, the objectives of this study were: (1) to assess farmers’ perceived production constraints, variety choice, and preferred traits of groundnut in eastern Ethiopia to guide future groundnut variety development and release, (2) to determine drought tolerance, kernel and fodder yield and quality amongst diverse groundnut genotypes for direct production or breeding, (3) to assess the genetic diversity and population structure among 100 groundnut genotypes using agronomic traits and high density single nucleotide polymorphism (SNP) markers, (4) to determine the combining ability effects of eight selected drought tolerant groundnut parental lines and their F2 families under drought-stressed (DS) and non-stressed (NS) conditions to select best performing parents and families for drought tolerance breeding. In the baseline work, participatory rural appraisal studies were conducted in two major groundnut-producing districts (Babile and Fedis) in eastern Ethiopia. The following data were collected involving 150 participant farmers: demographic descriptors, groundnut farming system, farmers’ knowledge about improved groundnut varieties, constraints to groundnut production, market access, and varietal trait preference. Chi-square and t-test analyses were conducted to determine statistical significance among the parameters across districts. Participant farmers identified drought stress (reported by 90% of respondents), poor soil fertility (88%), poor seed supply systems (67%), pre-harvest diseases (root rot and leaf spot) (59.5%), low yielding varieties (52.5%), low access to extension services (41.5%), low access to credit (21.5%) and limited availability of improved varieties (18.5%) as the major groundnut production constraints. The study identified the following farmer-preferred traits: high shelled yield (reported by 27.67% of respondents), early maturity (16.84%), and tolerance to drought stress (13.67%), market value (11.17%), good grain quality (10%), adaptability to local growing conditions (5.8%), and resistance to diseases (5.17%). Therefore, the aforementioned production constraints and farmer-preferred traits are key drivers that need to be integrated into groundnut breeding and variety release programs in eastern Ethiopia. In the second study, 100 groundnut genotypes were evaluated at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)/India during 2018/19 and 2019/20 under drought-stressed (DS) and non-stressed (NS) conditions using a 10 x 10 alpha lattice design with two replications. Seed and haulm samples collected at physiological maturity from DS and NS experiments to estimate Kernel and haulm quality parameters using near infrared spectroscopy (NIRS). Data were collected on kernel yield (KY), oil content (OC), oil yield (OY), protein content (PC), palmitic acid content (PAC), stearic acid content (SAC), oleic acid content (OAC) and linoleic acid content (LAC), haulm yield (HY) and fodder quality parameters such as the contents of dry matter (DM), ash, nitrogen (NC), neutral detergent fiber (NDFDM), acid detergent fiber (ADFDM), acid detergent lignin (ADLDM), in vitro digestibility (IVOMD) and metabolizable energy (ME). Data were subjected to parametric and non-parametric statistical analyses. Combined analysis of variance revealed significant (P< 0.05) genotype differences for all assessed traits. Genotype × water regime interaction effects were significant for KY, OC, ash content, NC, NDFDM and ADLDM. Kernel yield positively and significantly (P<0.05) correlated with oil yield (r = 0.99), LAC (r = 0.13), ash (r = 0.32), NDFDM (r = 0.54) under DS condition. Haulm yield was positively and significantly (P<0.05) correlated with OC (r = 0.24), NDFDM (r = 0.19), ADFDM (r = 0.18) and ADLDM (r = 0.17) under DS condition. Cluster analysis grouped the test genotypes into 12 distinct genetic groups. The study identified genotypes, ICGV 10178, ICGV 01260, ICGV 06175 and ICGV 10379 with high kernel and haulm yields, and CGV 181017, ICGV 01491, ICGV 15019, ICGV 181026, ICGV 16005 and ICGV 181063, with high oleic acid content. Furthermore, genotypes, ICGV 7222, ICGV 10143, ICGV 6040, ICGV 03042, ICGV 06175, ICGV 01260, ICGV 99241, ICGV 96266, ICGV 171027 and ICGV 01491, were selected with relatively better drought tolerance. The selected genotypes are recommended for further breeding and variety release under drought stress environments. In the third study, 99 of the test genotypes were profiled with 16, 363 SNP markers. The following phenotypic data collected during the second study were used for complementing the SNP data: days to 50% flowering (DF), SPAD chlorophyll meter reading (SCMR), Plant height (PH), number of primary branches (PB), specific leaf area (SLA), leaf relative water content (LRWC), total biomass (TBM), pod yield (PY), harvest index (HI), hundred seed weight (HSW), shelling percentage (SHP) and kernel yield per plant (KY) and days to maturity (DM). Analysis of variance, Pearson’s correlation coefficient, principal component and stress tolerance index were calculated. Pod yield per plant (PY), seed yield per plant (SY) and harvest index (HI) were significantly (p < 0.05) affected by genotype × environment interaction effects. Genotypes, ICGV 07222, ICGV 06040, ICGV 01260, ICGV 15083, ICGV 10143, ICGV 03042, ICGV 06039, ICGV 14001, ICGV 11380 and ICGV 13200, exhibited higher pod yield under both drought-stressed and nonstressed conditions. Pod yield exhibited significant (p < 0.05) correlation with SY, HI and total biomass (TBM) under both test conditions. Based on the principal component analysis, PY, SY,

HSW, SHP and HI contributed maximum variability for yield under the two water regimes. Hence, selection of these traits could be successful for screening of groundnut genotypes under droughtstressed and non-stressed conditions. Model-based population structure analysis grouped the studied genotypes into three sub-populations, whilst cluster analysis resolved the collections into five clusters based on pedigree, selection history, and market type. Cluster III and Cluster V consisted of the Spanish bunch types, late leaf spot (Phaeoisariopsis personata) and rust (Puccinia arachidis) resistant, and drought-tolerant genotypes. Analysis of molecular variance revealed that 98% of the total genetic variation was attributed to among individuals, while 2% of the total variance was due to variation among the subspecies. The genetic distance between the Spanish bunch and Virginia bunch types ranged from 0.11 to 0.52. Genotypes, ICGV 13189, ICGV 95111, ICGV 14421, and ICGV 171007, were selected for further breeding based on their wide genetic divergence. Data presented in this study will guide groundnut cultivar development emphasizing economic traits and adaptation to water-limited agro-ecologies including in Ethiopia. The fourth study examined the combining ability effects of eight selected drought tolerant groundnut parental lines and their F2 populations under drought-stressed (DS) and non-stressed (NS) conditions under glasshouse and field conditions at ICRISAT in 2020 rainy season. Data were collected on days to 50% flowering (DF), number of primary branches (PB), plant height (PH) (cm), SPAD chlorophyll meter reading (SCMR), specific leaf area (SLA) (cm2/g), pod yield (PY) (g plant- 1), shelling percentage (SHP) (%), kernel yield (KY) (g plant-1 ), total biomass (TBM) (g plant-1) and harvest index (HI) (%). ICGV 10178 was the best combiner genotype to increase SCMR, PY, SHP, KY, TBM and HI and, reduce SLA. The general combining ability (GCA) effects of parents were significant (P<0.05) for all assessed traits under all testing conditions except for PB under DS and NS conditions in the glasshouse. The specific combining ability (SCA) effects of progenies were significant (P<0.05) for all assessed traits except for PH across all testing environments and PB under field condition. Genotype ICGV 10178 was the best general combiner with positive contribution to SCMR, PY, SHP, KY, TBM and HI and reduced SLA. Crosses, ICGV 10178 X ICGV 11369, ICGV 10373 x ICGV 15083, ICGV 98412 x ICGV 15094 and ICGV 10178 X ICGV 98412, were the best specific combiners for enhanced pod yield and drought tolerance. Higher GCA: SCA rations were recoded for PY, KY and TBM across all the testing environments suggesting the predominant role of additive genes conditioning the inheritance of these traits. Therefore, the above new families are recommended for genetic advancement through single seed descent selection method to develop improved pure line groundnut varieties with high pod yield and drought tolerance.