International Crops Research Institute for the Semi-Arid Tropics
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A cost–benefit analysis of the production system with improved and climate-resilient sorghum varieties in southern Mali
Get PDFGiven the persistently low adoption rate of improved sorghum varieties over decades, it is relevant to assess whether it is profitable or not to grow these varieties in Mali. Over the past years, little evidence has demonstrated the profitability analysis as decision-support information regarding the adoption of improved sorghum varieties. This study used cost-benefit analysis to assess the profitability of two Improved and Climate-Resilient Sorghum Varieties (ICRSVs), “Soubatimi and Tiandougou-coura” compared to the “Local” ones, using three years of average yield data (2017, 2018, and 2020) in Sikasso region, Mali. The objective was to perform a consistent cost-benefit analysis through net income, cost-benefit ratio, and gross profit margin. The study used a farm partial budget framework, sensitivity analysis, and stochastic dominance analysis methods. A final sample of 31 farmers’ on-farm trials under the fertiliser package of “100 kg complex cereal and 50 kg urea” per hectare was held as the agronomic package. The key findings showed that both varieties were profitable, with 79,661 CFA (123.56 USD) and 45,073 CFA (69.91 USD) average net incomes corresponding to 1.54 and 1.32 CBR, and 34 and 24 percents average gross profit margins, respectively, while growing the “local” varieties was not profitable, with an average loss of 12,113 CFA (18.79 USD) with 0.91 CBR and 10 percent average gross profit margin. In light of these results, the study suggests a large dissemination of the ICRSVs in Mali. Policy-makers should facilitate the implementation of outreach programs to inform smallholder sorghum farmers on the ICRSVs’ traits and profitability information as decision support tool for a larger adoption
Unveiling the hidden threat: A comprehensive study on groundnut phytoplasmas in the major growing regions of Andhra Pradesh, India
No full textGroundnut is one among India’s most significant food and cash crops and it is also an oilseed crop. It is affected by several fungal, bacterial and viral diseases, which plays a significant impact in lowering its yields. Among the many diseases that affect groundnut, phytoplasma associated diseases were once thought to be rather unimportant. However, the disease’s incidence has been increasing recently and it was likely posing a threat to groundnut farming. An investigation was carried out to identify the symptoms and disease incidence of groundnut phyllody, little leaf, witches’ broom in Andhra Pradesh. A roving survey was conducted across five major groundnut growing districts to assess the incidence of phytoplasmas in the groundnut cultivations, i.e., Anantapur, Kadapa, Kurnool, Sri Satya Sai and Tirupati districts in 2023 “kharif” season. Regarding the symptomatology of phytoplasma of groundnut there is great confusion with peanut bud necrosis, peanut stem necrosis, peanut clump disease, and peanut stunt disease as they share some similar symptoms
Seed protein electrophoresis in plant genetics: Commemorating the pioneering contributions of Prof. Chittaranjan Kole and team to the foundation of plant proteomics
Get PDFDespite the rapid progress of proteomics in human and other model organisms, plant proteomics has advanced at a comparatively slower pace. This review aims to highlight the pioneering work on seed protein markers detected by employing gel electrophoresis primarily by a team of Indian scientists that paved the way for elucidation of intervarietal and interspecific variation, evolution, and phylogenetic relationship of species and their association with resistance to pest and diseases. Far from being replaced, gel electrophoresis remains as an excellent supporting and different approach, offering a pathway to a more profound visualization and understanding of the cell proteome. This review focuses on how, from a historical standpoint, gel electrophoresis has significantly contributed to plant proteomics and other biological research. Acknowledging the pioneering work on seed storage proteins, this review serves as both a congratulatory gesture and a tribute to the eminent scientist Prof. Chittaranjan Kole and his team who pioneered the strategy of seed protein electrophoresis in crop biology research. Their findings, both directly and indirectly, have proven invaluable, particularly for those who ventured into proteomics without easy reach to sophisticated and expensive instruments/equipment to pursue DNA-based genomics research. This gel electrophoresis-based plant proteomics review includes the evolution of gel-based proteomics, their contribution to crop biology research, and future directions. It stands not only as a retrospective analysis but also as a testament to the enduring significance of gel electrophoresis in shaping the landscape of crop proteomics
Growth and yield responses of sorghum (Sorghum bicolor [L.] Moench) varieties to sowing time in a rainforest zone of Nigeria
Get PDFSorghum is an important staple and commodity crop for West Africa, however, its production rarely meet demand. Due to its importance, efforts should focus on extension of sorghum production frontiers beyond the current ecological boundaries (the savannas of West Africa). Field experiments were conducted to evaluate the influence of sowing date on the performance of sorghum varieties in a rainforest zone of Nigeria. Sowing dates were: 15th July, 2nd and 20th August and 5th September, 2017 and 18th July, 5th and 17th August and 7th September, 2018 while sorghum varieties were Improved Deko, CSR-01, SK5912, 121 CKSV-180 and SAMSORG 17. Sowing dates were coded: SD1 (Mid July), SD2 (early August), and SD3 (mid August) and SD4 (early September) for each year experiment (2017 and 2018). Sowing dates differed in growing season lengths and weather conditions. Early maturing varieties (121 CKSV-180, CSR-01 and SAMSORG 17) gave highest yield gain for mid August and early September sowing dates while the late maturing varieties (SK 5912 and Improved Deko) gave highest grain yields for mid July, early and mid August sowing dates. SAMSORG 17 and Improved Deko produced heaviest grain yields and CSR-01, SK5912 the lowest. Early and mid August (SD2 and SD3) dates are the best sowing dates and SAMSORG 17 and Improved Deko are the best varieties in the rainforest zone of Nigeria. The study highlighted the relevance of sowing date and cultivar choice as location-specific management strategy for sustainable sorghum production in the rainforest zone of southern Nigeria
Institutions influencing plot access and intergenerational land transfer: Policy insights from a smallholder irrigation scheme in Zimbabwe
Get PDFLand access is a challenge for young farmers in Africa and likely to become increasingly so, with institutions and intergenerational dynamics a critical influence. Access for existing and would-be young farmers is vital to ensure an age-diverse farming population and support generational renewal on smallholder irrigation schemes. This research adds to the literature on formal and informal institutions impacting plot access and households' perspectives on farm transfer, using a smallholder irrigation scheme in Zimbabwe as a case study site. Qualitative data from interviews with young people, parents and practitioners were analysed by applying the Institutional Analysis and Development framework. The findings firstly illustrate the hybridised and multi-level nature of plot access arrangements, including the flexible leasing arrangements engaged in by young farmers. The data supports the generation of testable hypotheses and theorisation that plot transfer is a staged process, highlighting parents' dilemma of balancing their own and their children's needs and reflecting both inability and reluctance to transfer control. Suggestions for policy and development and further research are highlighted in the conclusion, including the need for schemes to have a strong focus on stimulating rural development, cross-generational approaches to support ongoing land access for young farmers and further research
Ensuring sustainable crop production when yield gaps are small: A data-driven integrated assessment for wheat farms in Northwest India
Get PDFNorthwest India achieved remarkable wheat productivity gains during the past decades. However, this has been accompanied by increasing input levels and intensive production practices, raising questions about the economic and environmental sustainability of current cropping systems. A multicriteria integrated assessment is required for wheat farms in the region to understand the scope for cleaner wheat production in the future. Production practices from irrigated wheat fields (n = 3928) were evaluated for multiple sustainability indicators, namely yield gap, nitrogen (N)-use efficiency, profitability, and greenhouse gas emissions. Stochastic frontier analysis was combined with simulated potential yield (Yp) data to identify the causes of wheat yield gaps in the region. N-use efficiency was estimated by calculating the partial factor productivity of N, profitability was computed based on reported input-output amounts and prices, and greenhouse gas emissions were quantified using the Mitigation Options Tool (MOT). These indicators were subjected to a multicriteria assessment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) under different scenarios (i.e., different weights for different indicators). For each scenario, farmers’ fields were classified as most efficient, efficient, less efficient, and least efficient, and random forest was used to identify the most important management practices governing the field classification. Wheat yield gaps were small (25–30 % of Yp or 2.4 t ha−1) and mostly attributed to the technology yield gap (ca. 20 % of Yp or 1.5 t ha−1). Ranking and grouping the farmers’ fields in the scenario with equal weights for all indicators revealed that at least 25 % of the fields had very high greenhouse gas emissions (>1500 kg CO2-eq ha−1) at a productivity level of 80 % most efficient fields adopting zero tillage) to achieve an overall objective of higher yield, lower greenhouse gas emissions, more profit and higher N-use efficiency, whereas residue retention and tillage intensity would need to be prioritized for minimizing greenhouse gas emissions. For the most efficient fields the decrease in greenhouse gas emissions was always associated with a decline in yield level. The most important management practices governing the field classification included the crop establishment method used for the previous rice crop, the number of tillage operations, residue retention, and the N fertilizer rate for wheat. The study provides a data-driven approach to screen trade-offs between performance indicators and to identify the management practices that can deliver sustainable and cleaner crop production in the future
A generalised hydrological model for streamflow prediction using wavelet Ensembling
No full textMachine learning (ML) models have recently been employed for precise streamflow prediction. These ML models, however, suffer from overfitting, non-scalability, non-transferability, and low predictive accuracy when used for unseen data that have high spatiotemporal variability and heterogeneity. To overcome these problems, a generalised streamflow model was, therefore, developed using novel Wavelet Ensembling (WE). The WE models were tested for several predictor combinations encompassing various terrain and flow conditions and were compared with the standalone and ensemble ML models. The generalisability of the models employed in the study was tested using transfer learning-based leave-one-out cross-validation (LOOCV). It was found that the WE models demonstrated a significant improvement over the standalone and ensemble ML models. The genetic algorithm (GA) optimised RF-based WE model (WE-RF-GA) was found to be the most efficient and generalised model, having the highest efficiency (NSE = 0.94, R2 = 0.95) and the lowest error (RMSE = 0.038, MAE = 0.028). The standalone and ensemble models showed higher predictive accuracy for tributaries, plain topography, and low-flow conditions compared to the mainstream flow, hilly terrain, and high-flow values. The WE models significantly reduced the performance gap of these models for the aforementioned conditions. This study would further enhance streamflow models and help predict streamflow effectively for data-scarce and ungauged basins
Rapid generation advancement of RIL population and assessing the impact of Rhizobium nodulation on crop yields in Chickpea
Get PDFChickpea, a widely cultivated legume, actively fix atmospheric nitrogen in root nodules through a symbiotic relationship with rhizobia bacteria. A recombinant inbred line (RIL) population, progressing from F2 to F7 generations, was developed in a short-period of 18 months using the Rapid Generation Advancement (RGA) protocol. The F7 RILs were evaluated during the 2020-21 and 2021-22 crop seasons under typical field conditions to quantify the effects of nodulation on seed yield (SY) and its associated traits. The analysis of variance revealed a highly significant difference (P < 0.01) among genotypes for seed yield and other agronomic traits, with no significant seasonal effect. In the pooled analysis, nodulating genotypes (NG) exhibited a substantial increase (P < 0.01) in SY (62.55%), 100-seed weight (SW100; 12.21%), harvest index (HI; 6.40%), number of pods per plant (NPPP; 39.55%), and number of seeds per plant (NSPP; 44.37%) compared to non-nodulating genotypes (NNG). Both NG and NNG exhibited a significant (P < 0.01) positive correlation between SY and NPPP (r = 0.64 and 0.63), NSPP (r = 0.66 and 0.61), HI (r = 0.27), and number of primary branches per plant (PBr) (r = 0.31), respectively. The top-performing genotypes for yield and related traits were predominantly nodulating. Genotype-trait bi-plot analysis identified nine nodulating genotypes as the most adaptable across the two seasons—six for SY, plant height, SW100, and three for days to first flowering and maturity. These findings underscore the critical role of nodulation in maximizing chickpea yields and the significant yield penalties associated with non-nodulation. To boost chickpea production, future breeding efforts should focus on developing genotypes with high compatibility with rhizobium strains
Role of functional genes for seed vigor related traits through genome-wide association mapping in finger millet (Eleusine coracana L. Gaertn.)
Get PDFFinger millet (Eleusine coracana (L.) Gaertn.) is a calcium-rich, nutritious and resilient crop that thrives even in harsh environmental conditions. In such ecologies, seed longevity and seedling vigor are crucial for sustainable crop production amid climate change. The current study explores the genetics of accelerated aging on seed longevity traits across 221 diverse accessions of finger millet through genome-wide association approach (GWAS). A significant variation was identified in germination percentage, germination rate indices, mean germination time, seedling vigor indices and dry weight upon aging treatment. GWAS model from 11,832 high-quality SNPs identified through Genotyping-by-Sequencing (GBS) approach produced 491 marker-trait associations (MTAs) for 27 traits, of which 54 were FDR-corrected. A pleiotropic SNP, FM_SNP_9478 identified on chromosome 7B was associated with the traits viz., germination after aging, germination index after aging and their relative measures. Functional annotation revealed DET1 and expansin-A2 influenced seed coat integrity, critical for germination and aging resilience. Probable protein phosphatase 2C3 and piezo-type ion channels contributed to mechanical sensing and stress adaptation in seeds. Beta-amylase and acetyl-CoA carboxylase 2 were identified for seed metabolism and stress response. These insights lay the framework for targeted breeding efforts to improve seed quality and resilience under diverse production conditions
Uncovering Novel Sources of Stem Rot Resistance in Groundnut: Insights from Diverse Gene Pools and Genomic Regions
No full textStem rot, caused by the soil-borne pathogen Sclerotium rolfsii, is a significant threat to groundnut cultivation, particularly in regions like the United States, India, and Australia, leading to yield losses of up to 80%. A multi-season phenotyping study was conducted on 184 minicore germplasm accessions under both sick field conditions and oxalic acid assays, revealing high heritability with a substantial environmental influence (36%). The oxalic acid
assay demonstrated an 80% concordance with field screening, providing a reliable complement to field-based phenotyping. Genotypes ICG163, ICG875, and ICG111 exhibited consistent and stable resistance across seasons. Resistance was exclusive to Virginia-type groundnut, including both bunch and runner types. Genotyping with the 'Axiom_Arachis' array (58,000 SNPs) identified 13 stem rot resistance-associated genomic regions across 8 chromosomes through GWAS, with LOD scores between 4.5 and 12.4, and R² values ranging from 6.9% to 58%. A total of 145 candidate genes linked to resistance stages were identified, including those involved in pathogen perception, inhibition, toxin detoxification, stress tolerance, and transcription factors for protective compound synthesis. Pathway analysis highlighted immune response mechanisms during early stage of infection and triggered a hypersensitive response in severe infection conditions leading to apoptosis. All Marker-trait associations (MTAs) were validated using allele-specific markers, facilitating their direct application in breeding. Introgression lines developed from secondary gene pool species (A. kempff mercadoi × A. hoehnei) and tertiary gene pool (A. glabrata) identified higher resistance genotypes, with lines like ICGIL 17101 showing <10% mortality. Ongoing efforts involve crossing A. glabrata with cultivated groundnut using embryo rescue techniques, providing valuable resources for breeding programs