Improved Groundnut Varieties Research Articles

Assessment of Groundnut Elite Lines under Drought Conditions and Selection of Tolerance Associated Traits

Investigation of groundnut genotypes response to drought stress could contribute to improving drought tolerance and productivity. The objective of this study was to investigate new improved groundnut varieties response to drought stress under controlled conditions to identify tolerant materials and drought tolerance related traits. Thus, three experiments were conducted during off-seasons: two experiments in lysimetric system in 2017 and 2018 and one experiment in pots in 2017, to assess twelve varieties in a randomized complete block design with 2 water regimes and 4 replications. The water regimes were a full irrigation (WW) and an intermittent drought imposed at flowering times (WS). The investigated morphophysiological traits like transpiration, specific leaf area, root dry matter, root length density, and yield components decreased under WS. Significant year effect and genotypic variation were observed on most of investigated traits. Genotypes ICGV 92206 and ICGV 06319 showed low transpiration and revealed high pod yielding and early maturing genotypes under both water regimes, while genotypes ICGV 92035, ICGV 92195, ICGV 02038, ICGV 07211, and ICGV 07210 were drought-sensitive for pods production but produced high haulm under both water regimes. ICGV 92206, ICGV 02005, ICGV 02125, and ICGV 06319 showed higher yielding than 55-437 and Fleur 11. In this study, low total transpiration to control water loss, chlorophyll content, and root length density revealed drought tolerance associated traits for pod production, while TTW, TE, RDW, and RV revealed drought tolerance associated traits for fodder production.

Adoption of varietal and accompanying groundnut technologies in Sokoto and Kebbi States of Northwestern Nigeria

The most recent improved groundnut varieties with farmers in Nigeria are SAMNUT 23, SAMNUT 24, SAMNUT 25 and SAMNUT 26. Amongst other things, this paper summarises outcomes of an adoption survey of these varieties in Sokoto and Kebbi States of North-western Nigeria. A total of 110 respondents were selected from administrative units where a donor funded project is being executed (coded herein as PLGA) and 110 from administrative units where project actions are absent (coded herein as NPLGA). The survey reveals that improved groundnut varieties are being grown amidst several other varieties designated as local. While SAMNUT 24 is being grown by 39% of respondents in PLGA and 19% of those in NPLGA, Kampala (a local groundnut variety) is being planted by 35 and 40% of respondents in PLGA and NPLGA, respectively. Farming experience, level of education and household size were found to influence household decisions to adopt groundnut varietal technologies and accompanying crop management practices at 1, 5 and 10% levels of significance. Gross Profit Margins in PLGA and NPLGA were 66,854 Naira (or $219) and 23,744 Naira (or $78), respectively, indicating that smallholder farmers could make nearly 64% additional cash incomes by adopting improved groundnut technologies.

Genetics, genomics and breeding of groundnut (Arachis hypogaea L.).

Groundnut is an important food and oil crop in the semiarid tropics, contributing to household food consumption and cash income. In Asia and Africa, yields are low attributed to various production constraints. This review paper highlights advances in genetics, genomics and breeding to improve the productivity of groundnut. Genetic studies concerning inheritance, genetic variability and heritability, combining ability and trait correlations have provided a better understanding of the crop's genetics to develop appropriate breeding strategies for target traits. Several improved lines and sources of variability have been identified or developed for various economically important traits through conventional breeding. Significant advances have also been made in groundnut genomics including genome sequencing, marker development and genetic and trait mapping. These advances have led to a better understanding of the groundnut genome, discovery of genes/variants for traits of interest and integration of marker‐assisted breeding for selected traits. The integration of genomic tools into the breeding process accompanied with increased precision of yield trialing and phenotyping will increase the efficiency and enhance the genetic gain for release of improved groundnut varieties.

Welfare impacts of improved groundnut varieties in eastern Zambia: A heterogeneous treatment effects approach

ABSTRACTThis paper examines the welfare impacts of improved groundnut varieties in eastern Zambia using data from a survey of over 600 households. We use the stratification-multilevel, matching-smoothing, and smoothing-differencing methods to analyse how treatment effects vary with the propensity to adopt improved groundnut varieties. We find consistent results across the models indicating that crop yields and incomes increase significantly with the propensity to adopt improved groundnut varieties. The results point to the need for policies and strategies that increase access to market information and overcome the constraints to adoption for realising the benefits from improved groundnut varieties in Zambia.

Molecular Mapping of Oil Content and Fatty Acids Using Dense Genetic Maps in Groundnut (Arachis hypogaea L.).

Enhancing seed oil content with desirable fatty acid composition is one of the most important objectives of groundnut breeding programs globally. Genomics-assisted breeding facilitates combining multiple traits faster, however, requires linked markers. In this context, we have developed two different F2 mapping populations, one for oil content (OC-population, ICGV 07368 × ICGV 06420) and another for fatty acid composition (FA-population, ICGV 06420 × SunOleic 95R). These two populations were phenotyped for respective traits and genotyped using Diversity Array Technology (DArT) and DArTseq genotyping platforms. Two genetic maps were developed with 854 (OC-population) and 1,435 (FA-population) marker loci with total map distance of 3,526 and 1,869 cM, respectively. Quantitative trait locus (QTL) analysis using genotyping and phenotyping data identified eight QTLs for oil content including two major QTLs, qOc-A10 and qOc-A02, with 22.11 and 10.37% phenotypic variance explained (PVE), respectively. For seven different fatty acids, a total of 21 QTLs with 7.6–78.6% PVE were identified and 20 of these QTLs were of major effect. Two mutant alleles, ahFAD2B and ahFAD2A, also had 18.44 and 10.78% PVE for palmitic acid, in addition to oleic (33.8 and 17.4% PVE) and linoleic (41.0 and 19.5% PVE) acids. Furthermore, four QTL clusters harboring more than three QTLs for fatty acids were identified on the three LGs. The QTLs identified in this study could be further dissected for candidate gene discovery and development of diagnostic markers for breeding improved groundnut varieties with high oil content and desirable oil quality.

Response of groundnut to plant density and phosphorous application in the Sudan savanna zone of Nigeria

Despite the recent release of several improved varieties of groundnut in Nigeria the productivities have not increase significantly due to lack of commensurate recommendation in agronomic practices. Two groundnut varieties were evaluated for their response to different plant density and phosphorus application in two locations in the Sudan Savanna zone of Nigeria in 2012 and 2013. The groundnut were planted at density of 44444, 66667, and 133333 hills ha-1 with average of two plants per hill. Phosphorus was applied at rate of 0 or 20 kg P ha-1. P fertilizer application increased pod and haulm yields by 26% and 16% respectively in Minjibir. It increased pod and haulm yields by 62% and 27% respectively in Wudil. Pod and haulm yields, harvest index, revenue, profit and cost benefit ratio increased with increasing plant density. Samnut-24 produced pod yields that were significantly higher than Samnut-22 across treatments. Pod yields at density of 133,333 hills ha-1 was 31% higher than at 66667 and 40% than at 44,444 hills ha-1. Application of fertilizer increased profit by 22% and 49% in Minjibir and Wudil respectively. Planting at density of 133,333 hill ha-1 increased profit by 19% and 27% over 66,667 and 444444 hill ha-1 respectively in Minjibir, while it increase profit by 9% in Wudil. Cultivation of Samnut-24 at high density with phosphorus application will make groundnut production a more profitable venture in Sudan Savanna zone of Nigeria.

English

Groundnuts are a key crop in Uganda, both as a source of nutrition and income. However, lack of knowledge and information on progressive practices along the groundnut value chain is a key contributor to the poor performance of the sub-sector. This study envisages establishing baseline knowledge on key aspects of groundnut production, processing and marketing with a view to identifying areas and gaps for capacity building interventions. A total of 155 farmers were randomly selected and primary data collected in early 2013 from three districts in Eastern Uganda namely; Bukedea, Mbale and Tororo. Results indicate that farmers were aware of most recommended pre and post harvest technologies/ practices including knowledge on improved groundnut varieties, superior agronomic practices, proper drying and cleaning, long-life storage, grading, sorting and packaging. However, even though most farmers had knowledge of the progressive technologies; quite a substantial number of them did not use these technologies in groundnut production and value addition. This finding points to presence of constraining factors that may hinder access and application of known technologies. Therefore, capacity building efforts to increase both access and utilization of value-enhancing groundnut technologies will eliminate the gap between awareness and use of these technologies for improved livelihoods. Key words: Awareness, groundnut, knowledge, technology utilization, Uganda.

Effects of social network factors on information acquisition and adoption of improved groundnut varieties: the case of Uganda and Kenya

Social networks play a significant role in learning and thus in farmers’ adoption of new agricultural technologies. This study examined the effects of social network factors on information acquisition and adoption of new seed varieties among groundnut farmers in Uganda and Kenya. The data were generated through face-to-face interviews from a random sample of 461 farmers, 232 in Uganda and 229 in Kenya. To assess these effects two alternative econometric models were used: a seemingly unrelated bivariate probit (SUBP) model and a recursive bivariate probit (RBP) model. The statistical evaluation of the SUBP shows that information acquisition and adoption decisions are interrelated while tests for the RBP do not support this latter model. Therefore, the analysis is based on the results obtained from the SUBP. These results reveal that social network factors, particularly weak ties with external support (e.g., researchers, extension agents, etc.), partially influence information acquisition, but do not influence adoption. In Uganda, external support, gender, farm size, and geographic location have an impact on information acquisition. In Kenya, external support and geographic location also have an impact on information acquisition. With regard to adoption, gender, household size, and geographic location play the most important roles for Ugandan farmers, while in Kenya information from external sources, education, and farm size affect adoption choice. The study provides insight on the importance of external weak ties in groundnut farming, and a need to understand regional differences along gender lines while developing agricultural strategies. This study further illustrates the importance of farmer participation in applied technology research and the impact of social interactions among farmers and external agents.

Technical Efficiency Differential of Groundnut Production in Jigawa State, Nigeria

This study was undertaken to principally determine the technical efficiency differential of groundnut production by adopters and non-adopters of Institute for Agriculture (IAR) groundnut varieties in Jigawa state, Nigeria.Interview schedule was used to collect data from a sample of 227 respondents who were selected randomly from the four agricultural zones in the study area. The analytical tools employed in data analysis include descriptive statistics and stochastic frontier production function. The result of the Maximum Likelihood Estimation of the stochastic frontier production function revealed that the maximum, minimum and mean efficiencies of farmers who adopted IAR groundnut varieties were 91%, 18% and 70% respectively while in the case of farmers who did not adopt, the maximum, minimum and mean efficiencies were 88%, 18% and 63%. This implies that the farmers who adopted IAR groundnut varieties are more technically efficient than farmers who did not adopt IAR groundnut varieties. Therefore, adopting of IAR groundnut varieties by farmers can contribute in enhancing their technical efficiency.The sources of technical inefficiency of adopters of IAR groundnut varieties were age (P<0.01), family size (P<0.01), education (P<0.01), extension (P<0.01) and credit(P<0.05). The result of the inefficiency model of the non-adopters of IAR groundnut varieties revealed that the major factorsinfluencing the technical inefficiency were family size (P<0.01), education (P<0.01), farming experience (P<0.05) and extension contact (P<0.05). Based on the findings of the study, Based on the findings of the study, it is recommended that Government should fast track seed multiplication and distribution through effective extension service delivery to farmers so as to intensify and sustain the adoption of improved groundnut varieties towards enhancing the technical efficiency of groundnut farming households.

Evaluation of Genetic Traits for Improving Productivity and Adaptation of Groundnut to Climate Change in India

AbstractAnticipated climate change will alter the temperature and rainfall characteristics of crop growing seasons. This will require genetic improvement of crops for adapting to future climates for higher yields. The CROPGRO model for groundnut was used to evaluate genetic traits of Virginia and Spanish types of groundnut for various climate scenarios of India. The analysis revealed that productivity of groundnut can be increased in current and future climates by adjusting the duration of various life‐cycle phases, especially the seed‐filling to physiological maturity (SD‐PM). Increased maximum leaf photosynthesis rate (AMAX), increased partitioning to reproductive organs (XFRT) and increased individual seed‐fill duration (SFDUR) all contributed to the increase in pod yield in all climates. More determinate pod set (shorter PODUR) was beneficial only in the water deficit environments. The positive effect of increasing specific leaf area (SLA) and leaf size (SIZLF) on pod yield was greater in environments more favourable for plant growth. Increasing reproductive tolerance to high temperature by 2 °C increased pod yield of groundnut in warmer environments, especially where the crop often suffers from drought. Increased adaptive partitioning to roots (ATOP) increased drought resistance of groundnut on high water‐holding capacity soils. Combination of traits had additive effects and pod yield increased substantially. These results indicate that the CROPGRO model can be used to assess the potential of individual or combination of plant traits for guiding breeding of improved groundnut varieties for current and future climates.

Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda

Summary This paper evaluates the ex post impact of adopting improved groundnut varieties on crop income and poverty in rural Uganda. The study utilizes cross-sectional data of 927 households, collected in 2006, from seven districts in Uganda. Using propensity score matching methods, we find that adopting improved groundnut varieties (technology) significantly increases crop income and reduces poverty. The positive and significant impact on crop income is consistent with the perceived role of new agricultural technologies in reducing rural poverty through increased farm household income. This study supports broader investment in agriculture research to address vital development challenges. Reaching the poor with better technologies however requires policy support for improving extension efforts, access to seeds and market outlets that simulate adoption.

Adoption of Agricultural Innovations in Developing Countries: A Survey

This paper reviews various studies which have provided a description and possible explanation to patterns of innovation adoption in the agricultural sector. The survey points out that the tendency of many studies to consider innovation adoption in dichotomous terms (adoption/nonadoption) may not be appropriate in many cases where the actual decisions are defined over a more continuous range. More attention needs to be given to the socio-cultural and institutional environment in area studies so that their interrelation with economic factors affecting adoption can be inferred. The presence of several interrelated innovations is another aspect that needs to be considered more carefully in future research, since a number of simultaneous decisions may be involved. Furthermore, the possibility of regular sequential patterns in adopting components of a new technological package should be specifically addressed in future studies. Finally, the impact of differential adoption rates on land holding distribution merits attention in future research.