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Delivering trait-enhanced varieties to African smallholders through a pangenomic breeding network
No full textPangenomics has been promoted to accelerate breeding of orphan crops, but smallholder farmers in developing nations have seen little benefit so far. To address this gap, we built a global pangenomic breeding network, integrating African breeding programs, U.S. land grant universities, and international nonprofit research organizations. Here we demonstrate that pangenomics, when integrated with local crop improvement knowledge and global scientific partnerships, can facilitate breeding of drought and pest resilient varieties for smallholders. To breed trait-enhanced sorghum varieties with lgs1-1 resistance to witchweed (Striga hermonthica) for smallholders in Niger, one of the world’s least developed nations, we used population genomics across local and global scales to develop lgs1-1 Striga resistance markers, and deployed them for rapid introgression of resistance into locally-preferred varieties. Genomic characterization, along with controlled experiments in laboratory, pot, field stations, and smallholder farms, confirmed lgs1-1 resistance was introgressed without loss of essential local-preference traits. New pangenomic resources, including global resequencing and graph pangenomes, further accelerated design of broadly-applicable markers. Unlocking the potential of pangenomics for stress-resilience breeding depended on stakeholder input, strong inference, South-led decision support software, and a dense collaborative network. The experience of the network provides a scalable roadmap for collaborative pangenomic breeding of trait-enhanced varieties for the world’s lowest-resourced farmers
Agricultural innovation targeting approaches and multi-stakeholder insights from Bangladesh
No full text22 page
Analysis of farmers’ indigenous knowledge, perceptions, and practices used in the control of parasitic weed striga among maize and sorghum farmers in Northern Nigeria
No full textThis study examined the socio-economic impact of the parasitic weed Striga infestation and the effectiveness of local and conventional control measures in Nigeria’s Gombe, Kano, and Jigawa States. Cross-sectional data from 925 respondents in 2020 was analyzed using descriptive and inferential statistics. Most respondents were male (94.8%), married (85%), and engaged in crop production (64%). The average landholding per household was 2 hectares, primarily used for cereal and legume cultivation, such as maize, sorghum, cowpea, and millet. The majority practiced mixed cropping (88%). Soil texture, moisture retention, color, and grass species appearance were used to assess farmland fertility. Striga infestation’s negative effects included stunted growth (59%), yellowing of crops (57%), yield decline (51%), and soil fertility reduction (19%). Respondents considered continuous cropping (63%), low fertilization (89%), poor crop management (79%), low rainfall (45%), and high temperature (45%) as the main causes of Striga infestation. Farmers used various methods for control, including appropriate fertilizer application (75%) and weeding (68%). Indigenous methods like a mixture of salt and potash and Parkia fruit powder were also common. The effectiveness of indigenous and conventional methods showed no significant difference between Jigawa and Katsina. In conclusion, Striga infestation significantly threatens crop production, income, and food security. It can be managed through both conventional and indigenous methods. Efforts should focus on educating farmers about agronomic practices to mitigate Striga infestation and promote the adoption of Striga-resistant crop varieties, especially in Striga-prone areas.59-6
Wheat yield and soil physicochemical properties through mineral nitrogen and vermicompost application in Lasta district, North Ethiopia
No full textEthiopia’s soils are losing essential nutrients and organic matter, causing a drop in agricultural output. This experiment was therefore conducted to evaluate the effect of combining mineral nitrogen (N) and vermicompost (VC) on bread wheat yield and soil physicochemical properties in the Lasta district. During the 2023 cropping season, the trial employed a factorial design with varying levels of N (0%, 50%, 75%, and 100% of recommended) and VC (0%, 50%, and 100% equivalent to N) on a farmer’s field. The soil samples were analyzed before and after treatment, and the data were analyzed using R software. The results indicated that the total N (TN) (0.131 ± 0.01%) and available phosphorus (Av. P) (22.97 ± 0.05) were recorded from 100% VC, the highest organic carbon (OC) (1.79 ± 0.01%) and CEC (36.8 ± 1.0 cmol+/kg) of the soil were recorded for the combined N and VC application, whereas the lowest TN (0.107 ± 0.01%) Av. P (19.17 ± 0.21), OC (1.05 ± 0.01) and CEC (23.37 ± 1.26) were recorded from the control. The highest grain (3955.33 ± 49.22 kg ha−1) and biomass (9.30 ± 0.1 t ha−1) yields were obtained with full N and VC application, while the lowest were observed in the control. Economic analysis revealed that applying fully recommended N with 100% VC as the N equivalent led to the highest net profit (290088.91 ETB) and acceptable marginal rate of return (1491.24%). It is recommended that farmers adopt 100% of the recommended N with 100% VC equivalence for optimal yields. Further research across diverse locations and years is suggested to validate and understand the residual effects on soil and yield improvements.3290
Extending physiological screening beyond the flag leaf: a canopy-wide approach to Wheat resilience under contrasting field conditions
No full textUnderstanding wheat's response to drought requires more than focusing on the flag leaf. In this study, 72 elite genotypes were assessed under irrigated and drought field conditions in Obregón, Mexico, using high-resolution phenotyping tools to quantify physiological responses across the full canopy including flag, second, and third leaves. Parameters such as SPAD chlorophyll content, PRI, quantum yield, stomatal conductance, light interception, and pigment-specific spectral indices were measured, alongside soil moisture profiles. Results revealed distinctive patterns in each canopy layer, with lower leaves playing a supplementary yet measurable role in maintaining canopy function under stress. This study highlights the need for integrating full-canopy physiological evaluations into breeding strategies for climate resilience.532-53
Does better information drive better seed choices? Experimental evidence from Kenya
No full textDespite advances in hybrid maize performance in Kenya, many farmers continue planting varieties released over two decades ago. Farmer experimentation with and use of relatively newer hybrids is crucial to improve regional food security, especially amid the increasing pressures of climate change. This study uses a randomized controlled trial to assess the degree to which contextually relevant and product-specific performance information influences farmer seed choice. Farmers in the treatment group received yield data for ten hybrids grown by farmers in the previous growing season in their county, while those in the control group received placebo information unrelated to seed selection. The intervention tripled farmers’ intent to buy top-performing hybrids (from 7% to 27%) and more than doubled actual purchases (from 5% to 13%). Stockouts prevented some intended purchases, but treated farmers were still more likely to choose these hybrids. This study highlights a critical gap: farmers tend to lack independent and credible up-todate information on seed performance. Investing in rigorous testing of currently available hybrids and improving how results are shared with farmers can help address this issue. Providing credible performance data can support better decision-making, speed up varietal turnover, and strengthen seed systems in Kenya and beyond
Assessing the accuracy of multi-model approaches for downscaling land surface temperature across diverse agroclimatic zones
No full textLand surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current LST estimates for field-level hydrological, agricultural, and ecological operations is challenging due to their coarse spatiotemporal resolution. In the current article, we compared three different models, namely 1) Thermal Sharpening (TsHARP), 2) Thin Plate Spline (TPS), and 3) Random Forest (RF) for downscaling LST from 100 to 10 m by using high-resolution Sentinel-1,2 optical-microwave data. TsHARP, TPS, and RF are commonly used methods for improving the spatial resolution of large-scale environmental or climate data to finer scales for field-level applications. The analysis was performed at agricultural farms in the semi-arid, arid, and per-humid regions of India during the winter and summer seasons of 2020-21 and 2021-22. The calibration accuracy of the RF model was in better agreement with the coefficient of determination (R2), root mean square error (RMSE), and normalized RMSE (nRMSE) values ranging between 0.961-0.997, 0.103-0.439 K, and 0.034-0.143%, respectively, and lower values of standard errors for all three locations. Though the validation accuracy of models varied between the regions, RF and TPS consistently outperformed the TsHARP model. Further the impact of individual features on LST downscaling was analyzed using Accumulated Local Effects (ALE) plot. The study concluded that RF is an effective and adaptable strategy that can be used in various agroclimatic zones and land cover types, suggesting its broader applicability in agricultural and ecological operations. Finer resolution LST data with enhanced precision can support tailored field-level decision-making and interventions in agriculture and environmental monitoring
Transcriptomic analysis to understand the nitrogen stress response mechanism in BNI-enabled wheat
No full textA comparative transcriptomic analysis was conducted for the nitrogen-efficient (BNI-Munal) and derivative parent Munal wheat genotypes to unravel the gene expression patterns across four nitrogen levels (0%, 50%, 75%, and 100%). Analyzing the genes of BNI-enabled wheat helps us understand how they are expressed differently, which heavily influences BNI activity. Grain yield and 1000-grain weight were higher in BNI Munal than in Munal. All the other traits were similar in performance. Varying nitrogen dosages led to significant differences in gene expression patterns between the two genotypes. Genes related to binding and catalytic activity were prevalent among molecular functions, while genes corresponding to cellular anatomical entities dominated the cellular component category. Differential expression was observed in 371 genes at 0%N, 261 genes at 50%N, 303 genes at 75%N, and 736 genes at 100%N. Five unigenes (three upregulated and two downregulated) were consistently expressed across all nitrogen levels. Further analysis of upregulated unigenes identified links to the NrpA gene (involved in nitrogen regulation), tetratricopeptide repeat-containing protein (PPR), and cytokinin dehydrogenase 2. Analysis of downregulated genes pointed to associations with the Triticum aestivum 3BS-specific BAC library, which encodes the NPF (Nitrate and Peptide Transporter Family) and the TaVRN gene family (closely related to the TaNUE1 gene). The five unigenes and one unigene highlighted in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were validated in Munal and BNI Munal. The results obtained will enhance our understanding about gene expression patterns across different nitrogen levels in BNI wheat and help us breed wheat varieties with the BNI trait for improved NUE
Adapting sorghum and other millets to climate challenges: An integrated bibliometric and meta-analysis of global literature
No full textSorghum and other millets, despite being known for their resilience, face significant agroclimatic challenges, including erratic rainfall, high temperatures, drought, dry spells and nutrient-poor soils. These crops, being significantly important in semi-arid and arid regions globally, invite more research focus. Given the lack of structured synthesis of climate adaptation research for sorghum and other millets, we conducted a systematic literature review to identify trends and associations in research with bibliometric analysis and estimate effectiveness of various climate adaptation options with meta-analysis. It is evident from our results that there's a shift in research trends towards data-driven techniques, such as machine learning, bio-fertilizers like biochar, nutrition-related areas like biofortification, and climatic hazard like waterlogging in sorghum and other millets literature. In terms of climatic hazards, drought and dry spells are the most studied phenomena. Our findings from meta-analysis show that agricultural adaptation options like stress tolerant varieties, tillage practices, and multiple adaptation options with tillage and integrated nutrient management show, 53 %, 52 % and 38 % mean yield improvement, respectively. Moreover, we examined the relationship of yield improvement with critical environmental factors such as soil, rainfall and temperature. This study provides a macroscopic overview of accumulated knowledge and underscores the need for continued and targeted interventions to enhance climate resilience of sorghum and other millets