International Crops Research Institute for the Semi-Arid Tropics
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Flies Pests of Food Legumes
No full textThe agromyzid flies are important pests of many agricultural crops, including food legumes. The agromyzids belonging to the genera Melanagromyza, Phytomyza, Liriomyza, and Ophiomyia severely damage legume crops worldwide, causing enormous yield losses. Agromyzids are strictly host-specific, and few species exhibit oligophagy. Some species (Phytomyza spp.) are highly polyphagous, feeding on diverse host plants. The adult agromyzids are small flies, and the larval stages are internal feeders that damage leaves, stems, seeds, pods, or roots of the plants. Successful control of these pests requires strict monitoring, detection, identification, and knowledge of their host plants and biology. In this chapter, the economically important agromyzid flies infesting legume crops, their management, and other aspects are described in detail
Influence of Bidirectional Reflectance Distribution Function in Estimating Basic Soil Properties Using Airborne Hyperspectral Data
Full text linkRecent studies on hyperspectral remote sensing (HSR) have shown that the estimation accuracy of different vegetation characteristics improves when the HSR data are corrected for the bidirectional reflectance distribution function (BRDF) effects. Similar studies involving soil parameters are limited. Here, we used the BRDF-corrected HSR data collected using the airborne visible-infrared imaging spectrometer-next generation (AVIRIS-NG) sensor to estimate soil parameters over a 138-km2 agricultural catchment. Surface soil samples were collected from 173 ground reference locations (GRLs) from this catchment to measure clay and sand contents, pH, electrical conductivity (EC), and soil organic carbon (SOC) contents. The BRDF correction was applied using the flexible BRDF (FlexBRDF) algorithm, and a polynomial unmixing approach was used to extract soil spectra from the corrected image. The BRDF correction successfully removed the shading effects and produced smooth transitions along the overlapping regions when multiple AVIRIS-NG images were mosaicked. Upon unmixing, soil spectra could be extracted at 140 GRLs when BRDF-corrected spectra were used, while uncorrected spectra produced soil spectra only for 114 GRLs. Chemometric models were validated using 109 common GRLs to compare estimation accuracy across laboratory-measured soil spectra ( SSLab ) and those obtained from unmixing of BRDF-corrected and uncorrected spectra. The coefficient of determination ( R2 ) values in the validation datasets ranged from 0.40 to 0.83 for both the BRDF-corrected and SSLab data, while the uncorrected spectra showed poor estimation accuracy (R2: 0.25–0.56). The resulting root-mean-squared error (RMSE) was reduced by 10% and 47% for the BRDF-corrected soil spectra compared to their uncorrected data. The BRDF-corrected and unmixed soil spectra were used to map soil properties at ~5-m spatial resolution for the entire catchment. Low SOC contents in the resulting maps adjoining the Ganges river flowing through our study site captured the topsoil loss typically observed from river banks. Thus, the BRDF-corrected HSR data not only improved the accuracy of soil estimates but also showed potential to identify vulnerable areas needing precision management measures with high spatial resolution
Restoring Degraded Landscapes for Sustainable Crop Intensification and Improving the Livelihood Security of the Particularly Vulnerable Tribal Groups in Odisha, India
No full textLand degradation is one of the major challenges that affects about 29% of land area and impacting nearly 3.2 billion people, globally. Land degradation takes many forms and affects soil, forests, biodiversity, water and socio-economic services derived from the ecosystem. Moreover, rapidly changing land use and deforestation in uplands leads to accelerated land degradation and generates large volume of runoff along with high rate of siltation. This runoff loss not only creates water/moisture deficit in uplands but
also invades mid- and lowlands of the landscape due to flooding, eutrophication, and heavy siltation in water bodies. These changes have been accompanied by negative externalities such as climate change, loss of biodiversity, poor retention ability of the landscape and heavy land degradation. These alterations have influenced number of planetary boundary conditions which are negatively influencing available natural resources, sustainability, and productivity of the landscape at local, regional, and global scale. These challenges are catastrophic, especially in uplands, those were historically covered with forests however, converted into desolated landscapes over the period. The impact is severe as these landscapes largely belonging to marginal and small landholders which coincide with high poverty and malnutrition. With the absence of resource availability, in habitants residing in these areas are compelled to migrate to urban centres in search of their livelihoods leaving behind their valuables and families. This situation often result in a precarious socio-economic conditions including large scale unemployment and delinquency in the society. However, this also provides an opportunity to harvest surface runoff through sciencebased
landscape resource conservation approaches using both engineering and biological measures. This facilitates improving the water retention ability of the landscapes which governs the water availability in surface and groundwater systems that facilitates sustainable intensification and diversification of agri-food system
Introgression and Mapping of Cotton Leaf Curl Disease Resistance from Wild Gossypium armourianum Kearney into Upland Cotton (G. hirsutum)
No full textCotton leaf curl disease (CLCuD), caused by the whitefly transmitted geminivirus complex (cotton leaf curl virus [CLCuV] and their satellite molecules), is a serious threat to successful upland cotton production in northwest India and Pakistan. The disease causes significant losses in fiber yield and the quality of cotton. Owing to the regular emergence of resistance-breaking strains of CLCuV, all the previously available CLCuD-resistant germplasms of upland cotton have become compromised, and none of the extant upland cotton cultivars is resistant to this disease. Therefore, alternate sources of CLCuD resistance need to be explored, as genetic resistance is the only pragmatic and tenable management strategy to combat this malady. Here, we report for the first time the introgression and mapping of CLCuD resistance from a related nonprogenitor wild diploid D-genome cotton species, Gossypium armourianum, into upland cotton. A backcross population (G. hirsutum/G. armourianum/G. hirsutum) was developed for this purpose. A single major QTL was found to be associated with resistance to CLCuD and was located on chromosome D01 through the genotyping-by-sequencing technique
Characterization of Nothopassalora personata Causing Late Leaf Spot Disease in Peanut Across Major Peanut-Growing Regions of India
No full textPeanut (Arachis hypogaea L.), also known as groundnut, is an important legume crop globally, serving as a key food and edible oil source for millions of people. Late leaf spot (LLS), caused by Nothopassalora personata (Berk. & M.A. Curtis) (syn. Cercosporidium personatum [Berk. & M.A. Curtis] Deighton), is the most destructive foliar fungal disease affecting peanuts, resulting in severe defoliation and yield losses of 40 to 90%. As a highly adaptable and evolving pathogen, N. personata rapidly develops new pathotypes, posing an ongoing threat to peanut crop. Monitoring the prevalence and genetic diversity of this pathogen in various agroecologies is requisite for tracking its spread and identifying areas of high risk. This study aimed to evaluate the disease severity and genetic diversity of N. personata across major peanut-growing regions in India. The survey revealed that disease severity (DS) ranged from 36.75 to 91.70%, with high humidity and moderate temperatures fostering disease progression. During the survey, the characteristic symptoms were observed, including dark brown lesions surrounded by chlorotic halos, advancing to necrosis and defoliation in severe cases. Forty isolates of N. personata were collected and identified through microscopic and molecular analysis using LSU-specific primers. Of these, five isolates (OD-8, KA-6, GJ-12, AP-3, and AP-4) exhibited high virulence in detached leaf assay. These results provide critical insights into the epidemiology of LLS, contributing to the development of effective disease forecasting models, which in turn guide targeted control measures. Further, whole-genome sequencing of N. personata isolates with different virulence patterns could identify key pathogenicity-related genes, paving the way for innovative control measures and the development of peanut varieties with enhanced resistance
Unveiling the efficiency and effectiveness of two distinct mutagens in early mutant generations of sodic tolerant finger millet [Eleusine coracana (L.) Gaertn] genotype
Full text linkFinger millet is an essential small millet that has gained attention for its high calcium content and C4 physiology. The self-pollination nature of the crop paves the way for the deliberate advent of candid variability, for which induced mutagenesis would be a suitable breeding method for the quick de- velopment of improved cultivars. In the present indagation, the sodic tolerant variety TRY1 finger millet was subjected to gamma rays and EMS to obtain early maturing genotypes. A preliminary experiment was conducted to investigate the LD50 value biological damages incurred by different mutagen doses, and mutagenic efficiency, effectiveness was estimated. Doses of gam- ma rays were used in the range of 100–500Gy. The EMS concentrations were 10 mM–50 mM. The LD50 values derived were 326.53 Gy of gamma rays and 15.36 mM EMS. Reduction in various quantitative traits became colinear with increased dose, irrespective of the mutagens. In the M2 generation, the chlorophyll mutants such as albino, xantha, chlorina, viridis, albomaculata and xantha viridis were noticed. The highest noted chlorophyll mutant was chlorina (1.906 %–Gamma ray and 2.748 %–EMS), and viridis (0.701 %–gamma ray and 0.451 %–EMS) was with the least frequency. Mutagenic effectiveness was high in lower doses of the mutagen (1.65–250 Gy and 5.20–10 mM). The mutagenic efficiency was higher in lower doses of both the mutagens, con- cerning the mutagenic frequency and lethality (0.116-250 Gy, 0.085-10 mM) injury (0.336–250 Gy, 0.176–15 mM) and sterility (0.205–250 Gy, 0.206–10 mM). Thus, gamma ray and EMS at their minimum dose proved efficient in inducing variations
Effects of land management practices on runoff and soil and nutrient losses in the rainfed agroecosystem of the Beles River Basin, Ethiopia
Full text linkThe Beles River Basin is facing severe soil erosion driven by human-induced activities, leading to significant losses of soil organic carbon (SOC) and nutrients (nitrogen (N) and phosphorus (P)). Effective land management practices (LMPs), including mechanical, biological, and agronomic techniques, are potential strategies for mitigating this degradation, but their effectiveness depends on site-specific and agroecological conditions. However, limited information is available on this aspect of the study area. The objective of the current study was to evaluate the effects of LMPs in the warm subhumid lowlands of the Beles River Basin on runoff, soil loss, and sediment-associated losses of SOC, N, and P from agricultural land. Four LMPs (vetiver grass strips (VGS), conservation agriculture (CA), soil bunds (SB), and fanya juu (FJ)) were evaluated via runoff plots arranged in a randomized complete block design (RCBD) with three replicates. Farmer practices were used as a control (C). The experiments, which were performed over three years (2021–2023), generated runoff, soil loss, and nutrient loss data. The three-year mean annual runoff ranged from 58.5 to 407.5 mm, and the soil loss ranged from 4.3 to 45.4 t/ha, whereas the annual rainfall varied between 1,402 mm in 2021, 1,254 mm in 2022, and 1,261 mm in 2023. On average, runoff was reduced by 36%–85%, and soil loss was reduced by 53%–91% in the LMP-treated plots. Additionally, sediment-associated losses of SOC, N, and P were reduced by 55%–90%, 52%–90%, and 28%–72%, respectively. The results revealed significant differences (p < 0.05) among the treatments in terms of reducing runoff, soil loss, and sediment-associated losses of SOC, N, and P. The mean annual runoff and soil loss rates during the study were 407.5, 230.3, 136.3, 59.6, and 58.5 mm and 45.4, 21.5, 11.1, 4.5, and 4.3 t/ha under the control, VGS, CA, SB, and FJ practices, respectively. The highest rates of runoff and soil loss were observed under the control conditions (407.4 mm and 45.4 t/ha). Runoff, soil loss, SOC, and nutrient (N and P) losses were significantly lower (p < 0.05) in the plots treated with FJ and SB than in the other plots. However, CA and VGS also significantly varied (p < 0.05) in reducing runoff, soil, SOC, and nutrient losses over the years. These results highlight the key role of LMPs in warm subhumid lowland rainfed agroecosystems as effective land management techniques for controlling soil and nutrient loss
Synergistic effects of aquatic weed biochar and inorganic fertilizer on soil properties, maize yield, and nitrogen use efficiency on Nitisols of Northwestern Ethiopian Highlands
Full text linkSoil acidity and poor fertility limit crop production in Ethiopia. Biochar from organic wastes, such as water hyacinth (Eichhornia crassipes), offers a potential solution. This study investigated the effects of co-applying water hyacinth biochar (WHB) with inorganic fertilizers on soil characteristics, maize yield, and nitrogen (N) use efficiency under field conditions. Four rates of WHB (0, 5, 10, and 20 t ha−1) were combined with two levels of recommended inorganic fertilizers (half and full rates of 180/138 kg N/P2O5 ha−1), plus a control (no biochar/fertilizer), during the 2022 and 2023 growing seasons. Results indicated that WHB significantly improved soil physicochemical properties (p < 0.05), across fertilizer rates, demonstrating both additive and independent effects. Consequently, WHB application reduced bulk density, increased porosity, and soil pH, and decreased exchangeable acidity and exchangeable Al3+, with the 20 t ha−1 WHB rate eliminating exchangeable Al3+. Moreover, available phosphorus, organic carbon, total nitrogen, cation exchange capacity, and exchangeable potassium were significantly improved (p < 0.05). Co-applying WHB with half and full rates of chemical fertilizers enhanced maize grain yield by 33.6 % and 30.8 %, respectively, compared to sole half and full fertilizer rates (non-biochar), with yield increases of up to 10 % in the second year compared to the first. Maize total biomass and 1000-grain weight also showed significant improvements. Nitrogen use efficiency significantly improved, especially when WHB was used with half the fertilizer level. These findings demonstrate the potential of combining WHB with inorganic fertilizers to improve soil fertility and enhance crop production in acidic soils
Patent Examination Process through AI and its Challenges in India, EU and the US
Full text linkThe role of Artificial Intelligence (AI) in the patent examination for the United States Patent and Trademark Office (USPTO), European Patent Office (EPO), and Indian Patent Office (IPO) is under development. Traditional patent examination systems currently encounter increasing difficulties in managing rising worldwide patent applications. The combination of machine learning (ML) technology with natural language processing (NLP) simplifies prior art research while improving patent classification methods and claims examination, thus enhancing patent examination effectiveness and precision. The USPTO uses similarity search as an AI tool and EPO utilises AI-PreSearch for automated classification and prior art identification tasks. The integration of AI in India focuses on modern process implementation to handle increasing numbers of patent applications and corresponding examination delays. The article shows how AI can reinvent global patent
examination through specific recommendations for its future development
Integrating carbon sequestration and yield optimization in Indian cropping systems
Full text linkAgriculture contributes significantly to greenhouse gas (GHG) emissions but also holds strong potential for mitigation – particularly through soil organic carbon (SOC) sequestration. This study evaluates the impact of integrated management practices—such as biochar application, optimized irrigation, and fertilizer management on yield improvement and SOC sequestration in semi-arid regions of Maharashtra, India. Using APSIM simulations across five districts and diverse cropping systems, it compares these practices with conventional farming. Results indicate that integrated practices consistently improve yields, SOC levels, and economic viability. For instance, maize yields under integrated practices increased by over 30 %, with substantial SOC gains. A cost-benefit analysis reveals high benefit-cost ratios, making these practices economically viable for smallholder farmers. This study highlights the transformative potential of integrated practices in addressing food security and environmental sustainability, especially in semi-arid regions. Policy recommendations include subsidizing biochar, promoting precision irrigation technologies, and integrating SOC sequestration strategies into national climate action plans. These findings provide actionable insights for scaling sustainable agricultural practices in resource-constrained settings