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Synergistic use of Sentinel-1 and Sentinel-2 data for Fall Armyworm infestation detection and mapping in maize croplands
No full textFall Armyworm (FAW) is a widespread invasive pest in maize crops. This study aimed at detecting and mapping FAW infestations in maize fields across Bangladesh, using freely available Sentinel-1 and Sentinel-2 data. Field observations were conducted during the 2019-2020 maize growing season in 579 maize fields across six administrative divisions of Bangladesh. The study covered both infested and non-infested sites across four crop growth phases, namely vegetative phases 9 (V9) and 12 (V12), as well as the silking and maturing phases. Synthetic Aperture Radar backscatter values, spectral reflectance profiles, and eight vegetation indices were extracted from the Sentinel data and analysed using non-parametric statistical tests to identify differences between infested and non-infested fields. Machine learning models, specifically Random Forest - and Support Vector Machine, were then used to classify infestation severity based on five model input data combinations: (i) Sentinel-1, (ii) Sentinel-2, (iii) Sentinel-2 with vegetation indices, (iv) Sentinel-1 and Sentinel-2, and (v) Sentinel-1, Sentinel-2, and vegetation indices. The results indicated that infested maize fields exhibited reduced near-infrared reflectance and distinct backscatter patterns in sigma VHo, with notable variations at silking and maturity phases. The red edge (740 nm), near-infrared (865 nm) and shortwave infrared (1610-2190 nm) bands were particularly effective in distinguishing infestation levels across all growing phases. Among the studied vegetation indices, the Normalized Difference Vegetation Index , Modified Chlorophyll Absorption in Reflectance Index, Red Edge Simple Ratio, and Modified Simple Ratio - were identified as the most significant indicators for discriminating between non-infested and infested maize classes at all growing phases. RF achieved 94-96% accuracy (96% in V9) versus SVM's 78-80% using only Sentinel-1 data. Multi-source (Sentinel-1, Sentinel-2 and Vegetation Indices) integration improved both models in most cases. These results underscore the potential of integrating multi-source remote sensing data for scalable and accurate pest detection. Freely available Sentinel data is a valuable source of information for early pest detection and management aiding policymakers in identifying high-risk areas, implementing timely interventions, and promoting sustainable pest management strategies to protect maize production and reduce economic losses.7044-707
Identification of high blanchability donors, candidate genes and markers in groundnut
No full textBlanchability is the ability of seeds to shed their seed coat (testa) and is a trait of economic importance in the food processing industry, yet remains underexplored in breeding programs. In this study, blanchability was evaluated in 184 groundnut accessions from the ICRISAT minicore collection to identify associated genomic regions, candidate genes, and molecular markers. Significant variability was observed over two seasons, with values ranging from 3.98 to 70.08%. Ten genotypes, including ICG10890, ICG9507, ICG13982, and ICG297, showed high blanchability, with ICG297 emerging as a promising donor based on cluster analysis of blanchability and agronomic traits. Genome-wide associations study (GWAS) using the 58 K ‘Axiom_Arachis’ SNP array revealed 58 significant SNP-trait associations, highlighting important genes such as isocitrate dehydrogenase and ubiquitin ligase, which influence seed coat structure and cell wall integrity thereby affecting blanchability. Further, nine SNPs were selected via allele mining, among these four SNPs, on chromosomes A01 (snpAH00551, AhBL01), A06 (snpAH00554, AhBL02), B04 (snpAH00558, AhBL03), and B07 (snpAH00559, AhBL04), effectively distinguishing between high and low blanchability genotypes. These validated SNPs present valuable tools for genomics-assisted breeding. Overall, the finding contributes towards better understanding of the genetic basis of blanchability in groundnut, providing key genomic resources for improving processing-related traits
Unlocking the potential of dryland underutilised crops through market linkages approaches
No full textZambia’s dryland underutilized crops, including sorghum, millets, cowpeas, groundnuts, and pigeon peas, present a transformative opportunity to enhance food security, climate resilience, and economic growth in the country’s semi-arid regions. These drought-tolerant, nutrient-rich crops are well-adapted to thrive in marginal environments where staple crops like maize struggle, yet they remain undervalued due to policy gaps, limited market access, and low awareness of their benefits. The Business-to-Business (B2B) Forum on dryland crops, held in Zambia, Lusaka on 22nd October 2025, brought together stakeholders from research institutions, government, the private sector, and farmer organizations to discuss these challenges and catalyse investment and partnerships. Drylands crops discussed in this forum are known to be inherently resilient to water scarcity, making them ideal for climate change adaptation in regions with erratic rainfall. They are also nutrient dense (protein, vitamins (A and C), minerals (iron, calcium), dietary fibre) offering a solution to malnutrition and dietary diversity. Economically, scaling up their cultivation and use could boost rural incomes, create jobs across value chains (from production to processing), and spur industrial growth. Despite these benefits, the crops face significant hurdles: low adoption of improved varieties, fragmented value chains, inadequate storage and processing infrastructure, and policy biases. To unlock the potential of these crops, the forum recommended six priority actions: (1) Strengthen Research & Development by investing in breeding, agronomic research, and value chain analysis to develop region-specific varieties; (2) Enhance Policy Support through national strategies, subsidies, and inclusion in food programs; (3) Boost Market Linkages by facilitating partnerships between farmers, processors, and buyers, and improving infrastructure; (4) Build Capacity by training farmers on climate-smart practices and business skills; (5) Raise Awareness through campaigns to promote their nutritional and environmental benefits; and (6) Mobilize Investment via public-private partnerships and donor funding. Immediate next steps include developing policy briefs to integrate these crops into Zambia’s agricultural strategies, organizing follow-up stakeholder meetings to create action plans, piloting community processing hubs, distributing improved seeds, and establishing a multi-stakeholder platform to track progress. By scaling up these “forgotten crops,” Zambia can achieve food security, improve livelihoods, and build a climate-resilient agricultural system. The forum emphasized that coordinated efforts can transform these underutilized crops into drivers of sustainable development, ensuring a more prosperous and resilient future for Zambian communities.33 page
Unlocking investment and innovation in dryland crops: A business forum on sorghum and groundnuts in Tanzania
No full textDryland crops such as groundnuts, sorghum, mungbean, cowpea, millets, and pigeon pea play a vital role in food and nutrition security, climate resilience, and livelihoods in Tanzania’s semi-arid regions. Despite their importance and adaptability to local agro ecologies, these crops remain under-commercialized, under-invested, and marginalized in the national agrifood systems conversations. Many improved varieties of these crops have been developed and released by national and international research institutions, but variety adoption and quality seed use remain low. This is attributed to several causes including weak linkages between research outputs and arket demand. Moreover, private sector involvement for these value chains is limited, primarily due to perceptions of low commercial viability, unpredictable demand, and a lack of investment incentives. Furthermore, value-added traits of these improved varieties are not sufficiently communicated to market actors to drive commercializatin decisions. Across the seed supply chains, several challenges continue to persist, ranging from misaligned early generation seed (EGS) systems, low use of variety licensing mechanisms to the lack of platforms for dialogue between farmers, breeders, seed producers, and off-takers. These bottlenecks hinder market development and restrict opportunities for scaling, enterprise growth, and employment generation within dryland crop value chains. Through science-based, locally led partnerships, CIMMYT and partners such as TARI seek address some of these challenges to accelerate the adoption of improved dryland crop varieties. With this hindsight, this Business-to-Business (B2B) forum was organized to offer a platform for learning, networking, and joint problem-solving, aiming to catalyse business growth and competitiveness within the sorghum and groundnut value chains. The event provided participants with access to knowledge on new varieties from researchers, connected potential business parters and mentors, and providing a space to co-develop practical solutions to long-standing challenges affecting the dryland crop sector.17 page
Modeling sorghum yield response to climate change in the semi-arid environment of Ethiopia
No full textIn Ethiopia, sorghum is a vital food security crop, predominantly cultivated in semi-arid, rain-fed agricultural landscapes. However, the increasing effects of climate change now present a serious threat to its sustainable production. This study assessed the impacts of climate change on three popular sorghum varieties (ESH-1, ESH-2, and Melkam) in three semi-arid areas of Ethiopia using a crop-climate modeling approach. Calibration and validation of the CERES-Sorghum model demonstrated strong agreement between simulated and observed values, confirming its reliability for application. Climate projections from three GCM models show temperature increases up to 2.1 °C by the 2050s and 4 °C by the 2080s. Rainfall changes varied by location, with Mieso projected for a 21.8 % increase and Melkassa showing minimal change but high variability. Our findings reveal highly differential and location-specific yield responses across varieties under projected climate. Although projections show Kobo yields remaining stable or increasing slightly under climate change, sensitivity analysis reveals potential yield declines of up to 44 % with a 20 % rainfall reduction. In contrast, projections for Melkassa showed consistent yield declines across all varieties, exhibiting strong sensitivity to temperature changes, where a 1.5 ∘C increase potentially reduces yields by up to 40 %. In comparison, Mieso displayed mixed responses, with the ESH-2 variety performing notably better under future scenarios. These findings suggest that current agronomic practices may be insufficient to sustain yields under climate scenarios, threatening future food security. Thus, developing and implementing climate-resilient strategies, including cultivating drought-tolerant sorghum cultivars, optimizing irrigation, and enhancing soil health, is crucial to ensure effective adaptation and regional food security
Genetic diversity of tropical maize (Zea mays L.) inbred lines using phenotypic clustering
No full textGenetic diversity in maize is a valuable natural resource and plays a key role in hybrid breeding programs. The present study was conducted to assess the magnitude of genetic diversity among 107 tropical maize (Zea mays L.) inbred lines using phenotypic traits. Significant variability was observed for all the 11 traits. Days to 50% tasseling (DFT), days to 50% silking (DFS), plant height (PH), ear height (EH), cob length (CL), cob girth (CG), kernel rows per cob (KRPC), kernel per row (KPR), shelling percent (SP), seed weight (SW) and grain yield (GY). High heritability and genetic advance were observed for the traits Viz., DFT, DFS, CL, CG and KRPC, indicating their suitability for effective selection. In contrast, traits like GY, SP, and SW showed low heritability, suggesting stronger environmental influence and the need to exploit heterosis for yield improvement. Cluster analysis of inbred lines grouped them into seven distinct clusters, with considerable inter-cluster distances, particularly between Cluster II and V. Principal component analysis (PCA) revealed that the first five PCA components explained over 80% of the total variation. Potential genetically diverse genotypes Viz., CIMMYT-19, BHG-19, UASBM-69 and AHG-76-1 were identified by the PCA biplot as promising sources for hybridization. Overall, the results showed the importance of flowering and cob-related traits for selection and demonstrate the combined utility of cluster analysis and PCA in identifying diverse parental lines, thereby providing a strong foundation for hybrid development and genetic improvement of maize.1466-147
Bayesian divergence-based approach for genomic multitrait ordinal selection
No full textEffective genomic selection for ordinal traits, such as disease resistance scores, is a persistent challenge in plant breeding due to the discrete, ordered nature of these phenotypes. This study presents a novel Bayesian divergence-based framework for multitrait ordinal selection, implemented in the extended Multitrait Parental Selection R package (MPS-R). By leveraging decision-theoretic loss functions, including the Kullback–Leibler (KL) divergence, Bhattacharyya distance, and Hellinger distance, our approach quantifies the distance between candidate distributions and breeder-defined target distributions. Through extensive simulations under 6 scenarios combining different genetic correlation structures and heritability levels, we demonstrate the comparative performance of each loss function. KL divergence consistently yielded superior genetic gains, especially in moderate heritability settings. Additionally, random sampling validation using real wheat disease resistance data confirmed the utility of these methods in practical breeding contexts. The MPS-R package implements this methodology through user-friendly functions tailored for ordinal trait selection in breeding applications. Our results demonstrate that this toolset provides a flexible, robust, and biologically grounded framework to enhance selection efficiency in breeding programs targeting complex, multitrait ordinal phenotypes. A couple of limitations employed by the simulation scheme used on the study are also discussed.jkaf18
Chapter 1. A review of existing knowledge on water use and nutritional water productivity in South Africa
No full textIn South Africa, while the nation is food secure at the national level, a substantial portion of the population lives in poverty and faces food insecurity, particularly in rural areas. The country’s water scarcity, variable rainfall patterns, and unequal distribution of irrigation resources further complicate the issue. Agriculture, which relies heavily on irrigation, is a major water consumer and contributor to food production. Efforts to address these challenges include exploring strategies like rainwater harvesting and improving water productivity in agriculture. The Water Research Commission (WRC) has played a pivotal role in developing innovative solutions to enhance water productivity, focussing on environmentally sensitive approaches and the water–energy–food nexus. Achieving food security in water-scarce regions like South Africa necessitates dynamic institutions, improved water productivity, and sustainable agricultural practices. This chapter emphasises the urgency of addressing these issues to ensure a healthier and more productive life for rural communities while promoting sustainable development and water-based agriculture.1-2
Diversity of phosphorus-solubilizing microbes isolated from different cropping systems of Zimbabwe for use as biofertilizers with rock phosphate
No full textSoil phosphorus deficiency and the high cost of mineral fertilizers necessitate research into alternative strategies. Inoculating seeds with adapted phosphorus-solubilizing microorganisms (PSMs) could be a cost-effective option. This study explored diversity, including phenotypic and genotypic characteristics of PSMs from selected soils and cropping systems of Zimbabwe, for coapplication with rock phosphate (RP). Culturable PSMs were isolated from preincubated or cowpea rhizosphere soil. Over 91% of the 37 isolates (PSM1–PSM37) were bacteria, while 8% were fungi. Diversity was higher in Dorowa (H′ 2.99; DMn 8.49) than that in Marondera (H′ 2.85; DMn 7.57), and under groundnut and maize (H′ 3.26) than other crops. Some PSMs occurred only in Marondera (8%) and Dorowa (14%). The P solubilization index on RP-amended Pikovskaya medium, ranged between 1.00 and 15.9. Sixty-five percent of the best 28 isolates were Gram-negative cocci or bacilli, while 35% were Gram-positive cocci. A dendrogram based on morphological, biochemical, and functional characterization grouped the isolates into two major clusters and four subgroups. On the basis of 16S recombinant DNA analyses, the Bacillus genus predominated (61%), with the highest P solubilization capacity (Bacillus amyloliquefaciens), while the rest (39%) were Enterobacter, Microbacterium, Paenibacillus, Klebsiella, Priestia, Acinetobacter, Nocardioides, and Kocuria genera. In conclusion, studied soils harbor diverse PSMs that solubilize RP, indicating their potential to develop affordable bioinoculants for improved productivity on P-limited soils. The study pioneers the discovery of diverse PSMs native to Zimbabwean soils. Further studies are required to evaluate PSM–RP efficacy with various crops under glasshouse and field conditions and benchmark with conventional fertilizers
Challenges to wheat disease resistance and current global strategies
No full textWheat yields have continued to increase globally at a steady pace over the past decade despite challenges faced by breeding programs from evolving and migrating races of rust and other wheat disease-inducing fungi. Additionally, pathogens are becoming tolerant to fungicides because of their injudicious use. We highlight the challenges in breeding and deploying resistant varieties and discuss global strategies to protect wheat from diseases. The continuous identification, utilization, and deployment of diverse resistance genes and quantitative trait loci for durable adult plant resistance, supported by precision phenotyping, marker-assisted and genomic selection, real-time pathogen diagnostics, and the rapid diffusion of resistant varieties, are helping to minimize crop losses while enhancing productivity. The potential for genetic engineering, including the introduction of resistance gene cassettes and precise genome editing of susceptibility or resistance genes, has also increased because of the recent acceptance of genetically modified wheat carrying the HB4 (R) drought tolerance gene in some countries.201-20