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The role of Technology Transfer Units, examined in this study, was found to be vital to expedite the process of disseminating new varieties and their production technology.

A total of 1,000 households were surveyed in the sampled states. A probit model was used to analyse.

Age, education, land holding, tractor use and number of working family members in agriculture were found to significantly affecting adoption of the new seed varieties. Technology transfer through licensing has impacted the adoption of new seed varieties positively by highlighting Punjab possessing the highest adoption and western Uttar Pradesh was majorly adopting the old variety.

The authors believed in farmers’ memory to recall the varietal information of wheat.

The study recommended various incentives to attract the seed industry in UP to minimize the economic loss potentially suffered by them.

Quality seeds are germane to increase the productivity of crops, and it is paramount to disburse the seed varieties to the end users in an efficient way to achieve the overall objective of productivity enhancement.

In this context, a study was conducted in three states of India, namely, Punjab, Haryana and Uttar Pradesh (UP) to find out the adoption rate of newly developed varieties of wheat, HD 3086 after three years (2014–2015) of its commercialization by IARI as well as HD 2967, which was released in 2011.

This paper aims to assess the impact of incorporating foxnut powder (FP) into bakery products to evaluate their effect on product quality and nutritional characteristics.

Samples of refined flour (control) and refined wheat flour with varying levels of FP were prepared for each bakery item. Sensory evaluations using a nine-point hedonic scale were conducted. Different concentrations of FP (20% for cakes, 12.5% for bread and 12.5% for doughnuts) were tested to achieve sensory acceptability.

The addition of FP at specified concentrations achieved sensory acceptability in the tested bakery items, significantly impacting overall acceptability. Incorporating FP led to textural attribute alterations, including increased hardness, gumminess and chewiness, alongside reduced cohesiveness and elasticity. Color properties were influenced, affecting lightness, redness and yellowness of the bakery items. Proximate composition analysis highlighted shifts in moisture, protein, fiber, fat and ash content between control and accepted samples. Mineral content analysis revealed notable differences in calcium, potassium, iron, magnesium and sodium between control and accepted samples.

These findings demonstrate the potential of FP to enhance bakery products, offering promising industrial applications in producing nutritionally enriched and visually appealing baked products.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.