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The purpose of this paper is to develop Artificial Neural Network (ANN)-based apple classifier. Testing effort is calculated using ANN method. The complete system is divided into two modules. In the first module, input (surface level apple quality parameter) from the different sources is collected by the software developed in Visual Basic through different input device like web camera, weight machine, etc. In the second module, the input data are used by ANN simulator to classify the apple according to their quality. The final result of an ANN model for apple classification is discussed; however, the modeling results showed that there is excellent agreement between the experimental data and predicted values. A low level of error prediction confirmed the fact that the Neural Network model is an effective instrument of the apple quality estimation. There is not any misclassification during testing. The paper presents alternative method for quality assessment of apple and provides consumers with a safer food supply. [ABSTRACT FROM AUTHOR]

Abstract In recent years, fish production from open waters in Central Himalayas, especially from riverine system, has declined considerably. Degradation of soil and water quality and poor infrastructure facilities are among the major causes of declined fish production in this region. Keeping this in view, the present investigation was carried out to assess the soil, water and infrastructure facilities by using geographical information system (GIS) and multi criteria evaluation approach which helped in understanding the key elements to develop and improve resource management strategies that are vital to ensure sustainable fish stocks in this region. Various important parameters of soil, water and infrastructure facilities of this mountainous region were thoroughly assessed by analytical hierarchy process (AHP) for development of fish culture. Based on these characteristics, sixteen thematic layers were prepared using the Geomedia Professional software to develop a series of GIS models/ sub-models. In this process, the region was categorized to different suitable locations for the development of highland and lowland fishery. The model output clearly indicates the location and extent for the development of this sector in different suitability scales viz., most suitable (51,112 ha, i.e. 13%) and moderately suitable (61,164 ha i.e. 15%) out of the total land cover area of Nainital district (about 402,000 ha). The study will help planners to design plans to harness maximum fish biomass and to derive social benefits from inland open waters in the region. [ABSTRACT FROM AUTHOR]

Organic waste disposal methods, notably landfilling, not only deplete resources but also contribute to environmental challenges. This research looks at potential barriers to organic waste management solutions. The objective of this study is to identify the barriers to organic waste management solutions from an actor's perspective, and to explore their causal relationships to overcome the organic waste management problem from a system perspective. Several key challenges were identified regarding organic waste management solution, the current intervention overview indicates that promoting and tracking attention towards "value to waste" would be an effective solution approach. Waste collection fees, unethical behavior, and a lack of engagement and commitment in activities show a subsequent effect on consumer-household solutions, which are currently acting as priority barriers in this research. In order to have a better understanding of this complex issue, a detailed knowledge of barriers (leading to organic waste) is discovered and evaluated with the application of fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL). The data for this research has been taken in the context of a developing economy like India. This work can provide structural support to the managers by knowing the cause (influencing) and effect-group (influencing) barriers to the effective implementation of an organic waste management system in a circular economy context. [Display omitted] • The research explores potential barriers to organic waste management solutions. • A fuzzy decision making method is used to evaluate the complex problem. • The method evaluates the key barriers in context of expert-made fuzzy judgments. • The study has been carried out and is focused in context of developing countries. • The study promotes flexible strategies to provide support to managers involved. [ABSTRACT FROM AUTHOR]

Information about the three-day national seminar that was held in India is presented. Topics include the role of higher education in addressing climate change, challenges of global warming and climate change faced by the Himalayan states and their people and effect of climate change to the society, agriculture and health. The seminar featured speaker Manju Sundriyal, scientist of Uttarakhand Science Education and Research Centre (USERC).

Food waste management is a growing environmental and economic issue for a developing country like India. This exploratory paper aims to prioritize key practices as "criteria" for food supply chains that lead to food waste reduction to ensure green waste management. Twenty-five criteria from the existing literature and expert inputs were assessed to resolve food waste reduction issues in food supply chains, especially in the agricultural sectors. The study identifies and ranks the intensities of each of the listed criteria. In the study, the Best-Worst Method, a multi-criteria decision-making approach, is applied. According to the findings, waste prevention at the earlier stages of food supply chains is given more priority compared to food waste minimization and treatment at the later stages. Hence, the study concludes "skill and training" as the highest ranked criteria, followed by "protection and infrastructure." Further, the study infers that understanding the individual intensities of criteria within a food supply chain can affect waste generation at each level, having a significant impact on waste reduction. The data in this research was evaluated in the Indian context. • Explores the green waste management problem in food supply chains. • 25 sub-criteria & 5 main criteria are listed in the circular economy context. •Conducted an empirical case study in the Uttarakhand region in India. • The Best Worst Method is used to evaluate the outcomes. • Training of growers is ranked as the topmost criteria. [ABSTRACT FROM AUTHOR]