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Castor (Ricinus communis) is an important oilseed crop in India’s arid and semi-arid regions. Its seeds yield 50% oil, rich in ricinoleic acid (80–85%), used in numerous industrial products. Castor roots play a vital role in plant growth and resilience, particularly under stress conditions like drought, salinity, low temperature, and heavy metal toxicity. Castor root architecture varies between tall and dwarf types and are influenced by seed quality, temperature, and oxygen availability. Root exudates, including sugars, amino acids, proteins, organic acids, lipids, and phenolics, facilitate nutrient uptake, microbial interactions, and stress mitigation. These exudates also contribute to metal detoxification, salt stress, low moisture or fertility levels to survive plants in adverse conditions. Phenolic root exudates offer disease resistance, while lipids and fatty acids aid in signalling for microbial communication. Fertilization and growth regulators influence root architecture and biomass too. Understanding castor root physiology and exudate composition is crucial for improving crop productivity, stress tolerance, and soil microbial ecology under changing environmental conditions.

Keywords: Castor, Ricinus communis, root exudates, rhizosphere, oilseeds, heavy metal.

Documentation of fibre yielding plant species survey of Vijayapura district of Karnataka comprising 13 tehsil was conducted during March 2018 to March 2025. The study was initiated with an aim to identify fibre and cotton yielding plant species of Vijayapura district. Fibre and cotton are used for commercial purposes. There are about 40 species of angiosperms belonging to 35 genera and 15 families of fibre and cotton exude plant species were documented. This district belongs to arid region of Karnataka State and unexploited the natural fibre other than cotton fibre. Cotton is a commonly cultivated plant in regions so this survey is most significant in documentation and traditional uses of other plant species. The potential uses are described by various researchers and scientists to look at their future perspectives of these previous natural resources in upcoming generation and conservation.

Keywords: Fibre, cotton, plant species, vijayapura.

The food industry produces a large volume of waste, much of which remains underutilized, with most being disposed of in landfills. To address this issue and boost nutritional value, this study developed cookies enriched with jackfruit seed flour and pomegranate seed powder, which are byproducts of food processing. The cookies were assessed for sensory properties using a 9 -point hedonic scale and evaluated for their antioxidant content, total phenolic content, and sensory acceptability. Statistical analysis was performed using ANOVA (Data Expert version 13). Findings revealed that the optimized cookies had higher levels of moisture (1.7%), ash (2.3%), fat (19.1%), fiber (1%), and protein (1.57%) but lower energy content (480.14 kcal) than control cookies. The antioxidant capacity was also significantly enhanced in the optimized cookies, with increased total phenolic content (TPC 9.256 mg GAE/100g), total flavonoid content (TFC 0.196 mg QE/gm), and DPPH activity (32.514%). Texture analysis showed that less force was required to break the optimized cookies, indicating a crisper texture than control cookies. This research offers a sustainable solution to reducing food waste by incorporating nutrient-dense byproducts into cookies, providing a novel method for enhancing the nutritional profile of baked goods.

Keywords: Jackfruit seed flour, pomegranate seed powder, antioxidant properties, total phenolic content, cookie formulation, texture analysis, sensory evaluation.

This study assessed the effects of open grazing on production activities of arable farmers in Niger State, Nigeria. Multistage sampling technique was used to select 154 registered arable crop farmers for this study. The study showed that the majority of the respondents (71.3%) were married, and their predominant age range were 31 – 40 years (66.9%) with a mean age of 34 years. In terms of educational attainment, (82.8%) of the respondents had formal education while only few had no formal education, with an average mean of 6 years of schooling. The result also showed that farmers are concerned about soil compaction and erosion caused by grazing animals, the need for additional fencing and other protective measures increases production costs and farmers perceive open grazing as a major threat to crop yields due to direct consumption and trampling of crops by livestock were major arable farmers’ perception on open grazing activities in the study area. The findings further show that open grazing can lead to conflicts between livestock and wildlife, potentially affecting biodiversity and crop pollination were major effects of open grazing on production activities of arable farmers in the study area. The results also show that, Aids to the victim of herders-farmers conflict to reduce the tendency of reprisal attacks (X?=3.46), Avoid dry season cultivation of crops (X?=3.40) and Help from local leaders to avoid impact of open grazing (X?=3.11) were major effective coping strategies to open grazing activities on arable farmers in the study area. It is therefore recommended that the government should establish and enforce designated grazing zones away from crop fields to minimize soil compaction, erosion, and crop damage.

Keywords: Grazing, production, arable farmers, activities and perception.

The onion maggot is a significant pest in onion production in the cold-arid region of Ladakh, causing substantial yield and quality losses. This study, conducted during the 2024 and 2025 cropping seasons, evaluated the effectiveness of black plastic mulch for managing onion maggot under field conditions. In 2024, mulching reduced bulb infestation to 2.3±0.8%, compared to 21.8±5.7% in the control. In 2025, infestation levels were 12.9±7.4% with mulch and 55.0±7.5% without mulch. In addition to reducing infestation, mulching increased bulb weight. Application of black plastic mulch in 2024 and 2025 increased mean bulb weight by 67.1% and 99.2%, respectively, compared to the control. Close plant spacing (10 cm × 10 cm) without mulch resulted in 159.2% and 38.4% higher crop damage than standard spacing (15 cm × 15 cm). These findings indicate that black plastic mulch and appropriate plant spacing should be integrated into pest management practices in trans-Himalayan Ladakh. This study represents the first report on the use of black plastic mulch as a management strategy for onion maggot.

Keywords: Black plastic, Delia antiqua, ladakh, IPM, mulching and onion maggot.

Little millet, a highly nutritious grain, is valued for its fiber, protein, and mineral content. Its adaptability across various agro-climates and increasing consumer demand have led to higher market prices and expanded cultivation. This study aimed to improve little millet’s yield and resilience by assessing combining ability and heterosis with machine learning. A line × tester design (4 lines × 5 testers) generated 20 hybrids, evaluated in a randomized complete block design. Traits like seed yield per plant were recorded, and genetic effects were partitioned into general combining ability (GCA) and specific combining ability (SCA). Heterosis was estimated based on parental performance. An artificial neural network (ANN) was used to predict outcomes and validated for accuracy. The analysis revealed significant GCA and SCA effects, indicating both additive and non-additive genetic influences. The parents GPUL-2, Nallasama, KOPLAM-53, and WV-126 were identified as strong general combiners. The crosses GPUL-4 × OLM-203 and Nallasama × GPUL-2 demonstrated superior performance, showing desirable heterosis and favorable SCA effects for seed yield and other traits. The ANN model achieved ~97% prediction accuracy, confirming genetic consistency. These findings highlight the importance of both additive and non-additive gene actions in improving yield and resilience in little millet.

Keywords: Little millet, combining ability, General Combining Ability (GCA), Specific Combining Ability (SCA), Artificial Neural Network (ANN), hybrid performance.