Shoot Fly Resistance in Sorghum: An Overview

Sorghum is an annual diploid C4 plant largely grown for food, fodder and feed purposes. Several insect pests pose major challenges to sorghum production from the seedling stage to maturity, among which the sorghum shoot fly Atherigona soccata (Rondani) is a major pest across Asia, Africa and Mediterranean Europe. Infestation by the pest is prevalent both during rainy and postrainy seasons. The exploitation of host-plant resistance can play a vital role in breeding for resistance to shoot flies. The shoot fly causes significant grain and fodder yield losses in sorghum in semi-arid regions. An integrated approach for host-plant resistance that combines morphological, genetic/molecular and agronomic approaches is key for the management of shoot fly infestations and the subsequent increase in sorghum productivity. To complement traditional breeding approaches, intervention in genomic approaches is required to enhance breeding efficiency. This review focuses on genetic approaches in sorghum for integrating shoot fly resistance and exploring genetic inheritance, variability and trait associations, including shoot fly resistance quantitative trait loci (QTLs)

A Comprehensive Review of Aflatoxin in Groundnut and Maize Products in Africa: Prevalence, Detection and Mitigation Strategies

Aflatoxins are a toxic secondary metabolite, mainly produced by the fungi Aspergillus flavus and A. parasiticus. Aflatoxin contamination of food is a global concern, as they are carcinogenic, mutagenic and teratogenic. Groundnuts and maize products are highly susceptible to aflatoxin contamination at both pre- and postharvest stages; this leads to a great risk for those countries that rely on these products for food and nutrition security as well as income. Groundnut and maize products have contributed a substantial amount of aflatoxin exposure to human and animal health risks, especially in countries that experience tropical climate and recurrent drought, favouring mould developments. Due to the strange health impacts of aflatoxin in agricultural commodities, different countries have set the acceptable limits for groundnut and maize products, whereas most of the countries use the same limit for both commodities. Detection and quantification of aflatoxins in groundnut and maize products are mainly through enzyme-linked immunoaffinity assay (ELISA) and high-performance liquid chromatography (HPLC), among others. However, currently rapid, accurate and cost-effective techniques are emerging to quickly monitor and enforce the regulation limits. Among the widely applied strategies for aflatoxin mitigation are biological control including atoxigenic Aspergillus strains, plant extracts, and chemical and physical methods of detoxification and decontamination. Aflatoxin decontamination using plant extracts is promising for most countries in sub-Saharan Africa owing to the availability, ease of access and affordability; however, there is a need for further screening to isolate the bioactive ingredients. This review could provide insight into the researchers, stakeholders and consumers on the prevalence of aflatoxin in groundnut and maize products as well as mitigation strategies to improve food safety

AI-Enabled UAV Borne Hyperspectral Imaging for Crop-Livestock Farm Management

Crop-livestock farming plays a crucial role in global agricultural communities by integrating crop production with livestock farming to create a sustainable and diversified farming system. However, this industry has become increasingly scrutinized due to environmental impact, climate change, and land degradation. As per present reports, crop residues, a significant livestock feed resource, are in shortage and have poor nutritional value. Moreover, various factors like heatwaves, drought, and diseases can negatively impact forage quality and reduce productivity. Conventional methods of assessing forage/crop residue quality face significant challenges, including labor-intensive, costly, time-consuming, and error-prone. UAV-based imaging can boost multi-dimensional crop improvement programs due to advantages like wider coverage, short revising times, high spatial resolutions, and ease of operation. Hyperspectral imaging (HSI) sensors provide enriched spectral information, enabling more precise investigations into feed quality evaluation, forage management, and livestock health. Artificial intelligence and machine learning (AI/ML) approaches can effectively analyze high-dimensional HSI data and extract meaningful insights. Integrating UAV-based HSI and AI/ML techniques is crucial to enhance crop-livestock farm management. This chapter explores the potential of UAV-based HSI and AI/ML for crop-livestock farm research and management, focusing on animal and forage health monitoring, and enhancing feed quality. We also emphasize AI/ML-based data analytics and algorithm development on UAV-borne HSI data to revolutionize crop-livestock farming

Leveraging ML to predict climate change impact on rice crop disease in Eastern India

Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for current and future scenarios. The nine biophysical parameters are precipitation (Pr), maximum temperature (Tmax), minimum temperature (Tmin), soil texture (ST), available water capacity (AWC), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference chlorophyll index (NDCI), and normalized difference moisture index (NDMI) by Random forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), Artificial Neural Net (ANN), and Support vector Machine (SVM). The multicollinearity test Boruta feature selection techniques that assessed interdependency and prioritized the factors impacting crop disease. However, climatic change scenarios were created using the most recent Climate Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5-8.5 datasets. The rice crop disease validation was accomplished using 1105 field-based farmer observation recordings. According to the current findings, Purba Bardhaman district experienced a 96.72% spread of rice brown spot disease due to weather conditions. In contrast, rice blast diseases are prevalent in the north-western region of Birbhum district, affecting 72.38% of rice plants due to high temperatures, water deficits, and low soil moisture. Rice tungro disease affects 63.45% of the rice plants in Bankura district due to nitrogen and zinc deficiencies. It was discovered that the link between NDMI and NDVI is robust and positive, with values ranging from 0.8 to 1. According to SHAP analysis, Pr, Tmin, and Tmax are the top three climatic variables impacting all types of disease cases. The study’s findings could have a substantial impact on precision crop protection and meeting the United Nations Sustainable Development Goals

Multi-locus Genome-Wide Association Study Uncovers Candidate Genes for Early Leaf Spot and Rust Resistance in Groundnut

Early leaf spot (ELS) and rust, caused by Cercospora arachidicola and Puccinia arachidis respectively, are major fungal diseases limiting global groundnut (Arachis hypogaea L.) production. Mini-core set was evaluated for ELS at 3 locations Senegal, Malawi and Mali and for rust at Dharwad for three seasons using the modified 9-point scale. High-density genotyping was performed using whole genome resequencing data to identify genomic regions associated with early leaf spot and rust resistance. After quality filtering, 561,009 high-confidence SNPs were obtained. To dissect the genetic architecture of resistance to these diseases, genome-wide association study (GWAS) was conducted on 184 diverse groundnut mini-core lines which revealed four marker trait associations (MTAs) significantly associated with ELS resistance and twelve MTAs associated with rust resistance, collectively explaining 10–59% of the phenotypic variance. The most significant SNPs were Ah01_48511619 and Ah17_133493906 for rust resistance, which were clearly differentiating the resistant and susceptible minicore lines and also validated in other diverse populations. These SNPs encode sterol c4-methyl oxidase 1-2 and MYB transcription factor. Sterol c4-methyl oxidase 1-2 is involved in brassinosteroids biosynthesis which inturn has a role in salicylic acid pathway and MYB transcription factor involved in activation of WRKY disease resistance genes to combat against fungal pathogens. For ELS resistance, the most significant SNP (Ah14_140021024) is associated with MYB transcription factor explaining phenotypic variance of 59%. The validated markers and the predicted candidate genes can be useful in integrating favorable alleles into elite cultivars through marker-assisted selection (MAS) for the development of cultivars with improved disease resistance. The ELS markers can be utilized in the breeding programs upon further validation

Biochar Application: A Sustainable Approach for Managing Stem Rot Disease in Peanut Caused by Sclerotium rolfsii Sacc.

Soilborne pathogens are often difficult to manage due to a wide host-range and long-term survival of pathogens. Inorganic and organic soil amendments are considered as one of the key management strategies. Biochar, produced through biomass pyrolysis under oxygen-limited conditions, has gained attention for enhancing soil structure, sequestering carbon, improving water retention, and boosting fertility. Beyond its role in soil enhancement, biochar shows potential in managing soilborne diseases. This study explores the multifaceted impact of biochar in managing stem rot disease in peanut, as well as its influence on soil properties and microbial communities. The effects of different biochar concentrations such as 0% (no biochar + S. rolfsii), 1%, 3% and 5% on Sclerotium rolfsii-induced stem rot were thoroughly assessed. Under laboratory conditions, biochar did not exhibit inhibitory effects on S. rolfsii at any concentration; however, it significantly reduced sclerotia formation, indicating a concentrationdependent suppression of pathogen resting structures. Moreover, biochar treatments effectively delayed disease onset and slowed disease progression in peanut plants, with notable variation observed among genotypes and biochar concentrations. Interactions involving genotypes ICGV 171002 and ICGV 181035 with BC2 + Sr (3% biochar + S. rolfsii) and BC3 + Sr (5% biochar + S. rolfsii) demonstrated superior disease suppression under controlled conditions. Field evaluations further validated these findings, revealing genotype-specific responses to biochar applications. However, no significant difference was observed between BC2 + Sr (3%) and BC3 + Sr (5%) in their ability to manage stem rot disease compared to controls. In addition to disease management, biochar improved soil fertility by increasing nitrogen, phosphorus, and potassium levels while enhancing soil organic matter, electrical conductivity and pH. These findings highlight biochar’s potential as a sustainable soil amendment, contributing to disease suppression and soil health improvement. Further research is needed to optimize biochar application strategies across diverse agricultural settings

A Ralstonia effector RipAU impairs peanut AhSBT1.7 immunity for pathogenicity via AhPME-mediated cell wall degradation

Bacterial wilt caused by Ralstonia solanacearum is a devastating disease affecting a great many crops including peanut. The pathogen damages plants via secreting type Ш effector proteins (T3Es) into hosts for pathogenicity. Here, we characterized RipAU was among the most toxic effectors as ΔRipAU completely lost its pathogenicity to peanuts. A serine residue of RipAU is the critical site for cell death. The RipAU targeted a subtilisin-like protease (AhSBT1.7) in peanut and both protein moved into nucleus. Heterotic expression of AhSBT1.7 in transgenic tobacco and Arabidopsis thaliana significantly improved the resistance to R. solanacearum. The enhanced resistance was linked with the upregulating ERF1 defense marker genes and decreasing pectin methylesterase (PME) activity like PME2&4 in cell wall pathways. The RipAU played toxic effect by repressing R-gene, defense hormone signaling, and AhSBTs metabolic pathways but increasing PMEs expressions. Furthermore, we discovered AhSBT1.7 interacted with AhPME4 and was colocalized at nucleus. The AhPME speeded plants susceptibility to pathogen via mediated cell wall degradation, which inhibited by AhSBT1.7 but upregulated by RipAU. Collectively, RipAU impaired AhSBT1.7 defense for pathogenicity by using PME-mediated cell wall degradation. This study reveals the mechanism of RipAU pathogenicity and AhSBT1.7 resistance, highlighting peanut immunity to bacterial wilt for future improvement

Institutional and technological innovations for sustained change in smallholder irrigation schemes in southern and Eastern Africa

Water management systems must become more adaptable to alleviate projected shortfalls. Integrated socio-institutional and technological interventions are required to generate sustained change in irrigation water management and the profitability for smallholders and their schemes. We illustrate this by conducting an ex-post analysis of the ‘Transforming Irrigation in Southern Africa’ (TISA) project, which was implemented in two phases from 2013 to 17 and 2017–2023. The project introduced institutional and technological innovations to smallholder irrigation schemes in Tanzania, Mozambique and Zimbabwe: Agricultural Innovation Platforms as a participatory approach to engage farmers and stakeholders; and soil moisture monitoring tools to support farmer learning. We hypothesised that these innovations, despite differing socioeconomic and biophysical conditions in the three countries, would work synergistically to improve farmers’ adaptive capacity and generate sustained change. In this paper, we test our hypotheses through a synthesis of peer-reviewed TISA literature, focussing on four smallholder irrigation schemes and five factors identified in the literature as critical for increasing farmers’ adaptive capacity. Drawing predominantly on household surveys administered at the beginning, middle and end of the TISA project, we analyse a set of relevant indicators linked to the five factors. In addition to many changes, we found changes in irrigation management, including a reduction in total water use to less than half pre-TISA levels. Further, the changes were sustained when the schemes transitioned from an intensive research-for-development phase into a more operational phase. This research also shows that when governments listen to farming communities and revise institutional arrangements, such as water scheduling and scheme constitutions, this fosters more sustainable irrigated agriculture. We conclude that when initiating development projects for sustained change within smallholder irrigation schemes policy makers and donors must commit sufficient project time and funding for both a development phase and a transition to an operational phase. Programs must take a participatory approach and support multiple interventions including both socio-institutional and technological interventions

Agroinfiltration-mediated transient assay for rapid evaluation of constructs in pigeonpea

The process of generating stable transformants is time-consuming, labor-intensive, and genotype-dependent. In contrast, transient gene expression techniques, such as agroinfiltration, offer a rapid assessment of gene function and expression. Agroinfiltration, widely employed for studying gene function, has been extensively applied in leaf tissues of Nicotiana benthamiana and various other plant species. Despite its broad utility in various plants, to our knowledge, no prior investigation has been reported in pigeonpea. In this study, we developed an agroinfiltration method for transiently expressing a green fluorescent protein (mGFP5) reporter gene in four pigeonpea genotypes using syringe infiltration at the seedling stage under greenhouse conditions. The expression of the reporter gene mGFP5 was assessed at 72-, 96-, and 120 h post-infiltration (hpi). Additionally, we assessed the effect of morphogenic genes, specifically growth-regulating factor 4 (GRF4) and GRF-interacting factor 1 (GIF1), from both rice and pigeonpea on the expression of mGFP5 in four pigeonpea genotypes. Our findings demonstrate that OsGRF4-GIF1 led to enhanced mGFP5 expression compared to CcGRF4-GIF1 in four diverse pigeonpea genotypes. Fluorescence could be detected till 120 hpi. Furthermore, PCR, RT-PCR, and fluorescence quantification confirmed the presence and expression of mGFP5 at 72 hpi. Our results highlight the efficacy of agroinfiltration in quickly evaluating candidate genes in four genetically diverse pigeonpea genotypes, thereby reducing the time required for the initial assessment of constructs suitable for diverse molecular biology analyses

Understanding resistance mechanisms in crop wild relatives (CWRs) of pigeonpea (Cajanus cajan L.) against pod borer Helicoverpa armigera (Hub.)

The pod borer, Helicoverpa armigera (Hübner), is a highly destructive pest of leguminous crops, particularly pigeonpea (Cajanus cajan L.). This crop suffers significant damage from H. armigera, with estimated yield losses ranging from 30 to 40% annually. Despite extensive screening of elite pigeonpea accessions from the primary gene pool for resistance, no stable and true resistant or tolerant accessions have been identified. In this study, we screened 96 pigeonpea accessions from diverse gene pools for resistance to H. armigera using larval (first and third instar larvae) antibiosis during Rainy-2022. Based on k-means clustering, 50% of these accessions were selected for further evaluation in Rainy-2023 under field and laboratory conditions. Notably, accessions of Cajanus scarabaeoides from the secondary gene pool—specifically ICP 15716, ICP 15718, and ICP 15726—exhibited the lowest pod damage ratings (3.0–3.6), lower per cent larval survival (26–46%), and reduced per cent larval weight gain (27.0–35.18%) over two seasons. In addition, Rhynchosia suaveolens (ICP 15867) from the quaternary gene pool also exhibited minimal damage rating and low larval weight gain. The correlation of pod damage and oviposition with pod trichome density, pod length and pod width revealed that these morphological traits are key factors in conferring resistance against H. armigera. The Multi-trait Genotype Ideotype Index (MGIDI) identified seven superior accessions of C. scarabaeoides—ICP 15718, ICP 15716, ICP 15726, ICP 15730, ICP 15744, ICP 15732, and ICP 15703—as optimal candidate accessions for future breeding programs. This study highlights the critical role of host plant resistance in developing resilient pigeonpea cultivars resistant to H. armigera and emphasizing the potential of utilizing wild relatives in crop improvement strategies