This study evaluated the performance of fifteen wheat (Triticum aestivum L.) genotypes across eight locations representing all three agro-climatic zones of Bihar during the rabi season of 2023–24. The trials were conducted in randomised complete block designs with three replications at the following locations: Pusa, Piprakothi, Purnea, Madhepura, Sabour, Tilondha, Islampur, and Mokama. GGE biplot analysis was used to identify the best genotypes in each environment and assess the stability of the selected genotypes. Analysis of variance revealed significant effects of genotype (G), environment (E) and their interaction (G × E) on grain yield, indicating a strong environmental influence. The first two principal components (PC1 and PC2) explained 70.1% (PC1=44.3% and PC2=25.8%) of the total G×E variation. Genotypes DBW 303, DBW 327, RAUW 120, RAUW 121 and DBW 187 were high yielding, demonstrating wider adaptability. The polygon view of the biplot identified three mega-environments: ME-1: Madhepura, where BRW 3922 was superior; ME-2: Pusa, Piprakothi, Purnea, Sabour, Tilondha, and Mokama, where DBW 303 performed best; and ME-3: Islampur, where DBW 187 excelled. Genotype BRW 3921, despite being at a polygon vertex, showed poor general adaptability. These results demonstrate the efficacy of GGE biplot analysis for identifying both stable and environment-specific wheat genotypes, providing valuable insights for breeding programmes aimed at improving wheat productivity in Bihar.
Pearl millet has emerged as a key climate-resilient crop, capable of withstanding harsh environmental conditions and mitigating the adverse effects of climate change while ensuring stable productivity and supporting food and income security in vulnerable regions. This study aimed to identify the optimal combination of sowing time, cultivar and nitrogen level for maximising pearl millet productivity under summer and kharif conditions.Three factor field experiments were conducted in split-split plot designs with three replications during the summer and kharif seasons of 2024 to evaluate the growth, yield and yield-contributing traits of pearl millet. The three factors were: main factor: sowing time (summer: D₁ –5 February2024, D₂ –20 February2024, D₃ –7March2024; kharif: D₁ –28 June 2024, D₂ –13 July 2024, D₃ –28 July 2024), sub factor: cultivars (C₁ –CO 10 and C₂ –COH 10) and sub-sub factor: nitrogen fertilisation levels (N₁ –75%, N₂ –100% and N₃ –125% of the recommended dose of nitrogen). Experimental data were analysed using principal component analysis and heat maps were generated for interpretation. The results indicated that early sowing (D₁), in combination with the cultivar COH (C2) and 125% RDN (N3), significantly enhanced yield and itscomponents in both seasons. On average across both seasons, grain yield under D₁ was 11.0% higher than D₃ and 4.6% higher than D₂. The improved cultivar COH 10 (C₂) yielded 9.0% more than CO 10 (C₁), while 125 % RDN (N₃) application led to yield increasesof 5.1% and 14.9% over N₂ and N₁, respectively. The interaction effects among sowing date, cultivar selection and nitrogen levels were instrumental in optimising crop performance. These findings highlight the significance of season-specific, input-responsive agronomic strategies in maximising the productivity potential of pearl millet under changing climatic conditions.
Shallot production is generally influenced by the adequacy of nutrients in the soil, so it requires regulation of planting density and nutrients, especially NPK.The aim of this research was to determine the effect of planting density and inorganic fertilisation on shallot production and quality.The factorial design was randomised complete blockwith three replications.The research treatments consisted of the plant density factor and the inorganicnutrient rates factor.There were four levels of plant density: 100, 67, 50, and 44 plant/m2.There were four inorganic fertiliser treatments: (T1) 40 kg/ha N, 94 kg/ha P,40 kg/ha K(basic fertiliser) +24 kg/ha N, 24 kg/ha P, 24 kg/ha K (supplementary fertiliser); (T2)40 kg/ha N, 94 kg/ha P, 40 kg/ha K(basic fertiliser)+ 23 kg/ha N (supplementary fertiliser);(T3) 64 kg/ha N, 118 kg/ha P,64 kg/ha K(basic fertiliser)+ 23 kg/ha N(supplementary fertiliser);(T4) 40 kg/ha N, 94 kg/ha P,40 kg/ha K(basic fertiliser)+ 31 kg/ha N, 8 kg/ha P, 27 kg/ha K(supplementary fertiliser).Based on the results of this research, that thethe treatmentwithplanting density at 100 plant /m2or the fertiliser treatment at 40 kg/ha N, 94 kg/ha P, 40 kg/ha K)+(24 kg/ha N, 24 kg/ha P, 24 kg/ha K produced highest bulb fresh weight of shallot
Agricultural water scarcity is enormous in sub-Saharan African countries. Meanwhile, continuous flooding remains the primary irrigation method for rice. However, improved aerobic rice varieties, when grown in unsaturated but optimum soil water conditions, produce better yields with less water. Promoting improved and user-friendly irrigation scheduling methods would help farmers overcome the complexities and attain optimum soil water conditions for rice. This study assessed the impact of irrigation scheduling methods on the agronomic performance of rice under upland conditions of the Tono irrigation scheme in the Upper East Region of Ghana. The experimental design was a randomised complete block with three replications. Ten treatment combinations were used and consisted of irrigation scheduling methods at five levels (tensiometer, wetting front detector, chameleon sensor, alternate wetting and drying (AWD), and continuous flooding) with two rice varieties (Agra and Nerica 4). The effects of treatments on the agronomic traits measured were significant (P < 0.001). The combined use of irrigation scheduling methods and Agra gave higher yields than with Nerica 4. Continuous flooding and Agra gave the highest yield of 7.91 t/ha. The wetting front detector in conjunction with Agra obtained 7.30 t/ha yield but was statistically similar to the yields of continuous flooding and Agra. Tensiometer-scheduled irrigation on Agra produced the highest plant height, tillers, 1000 seed weight, and irrigation water-use efficiency of 104.30 cm, 327.30 tillers/m², 30.80 g, and 5.86 kg/m³, respectively. The study concludes that integrating sensor-based irrigation scheduling technology with a tensiometer into the practice of irrigation in irrigated ecologies can support the sustainable production of upland rice and improve water savings in Ghana.
Understanding emerging policies and policy pathways is key to shape sustainable food systems (SFS) through coordinated and systemic policy interventions. This review analysed 205 peer-reviewed articles from Scopus and Web of Science databases, systematically selected using PRISMA guidelines, forming a thematically and structurally saturated corpus for scientometric analysis. A combined bibliometric and thematic analysis was employed to understand the policy pathways for SFS. Performance analysis revealed a highly concentrated authorship and institutional structure, with 88% of publications originating from high-income countries, led by the United States, Italy, and the United Kingdom, and dominated by institutions, namely Wageningen University and the University of California. Keyword co-occurrence and thematic mapping revealed foundational research domains including food systems, sustainability, and food policy, as well as emerging themes governance, resilience, greenhouse gas emissions and alternative food networks. Thematic analysis indicated a transition from technical and efficiency-based policy models toward more transformative, participatory, and mission-oriented approaches. The review highlights emerging attention to governance reform, resilience, greenhouse gas mitigation, and alternative food networks, while identifying persistent gaps in policy implementation, cross-sectoral coherence, and the inclusion of marginalised and indigenous perspectives. Overall, the findings indicate that transforming SFS requires not only improved policy design but also structural transformation of policy-making processes, with greater epistemic inclusivity and interdisciplinary engagement.
