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In India, the contribution of women workers in agriculture is steadily increasing daily, which governs a major share of the Indian agriculture sector. Hence farm tools and equipment must be designed by considering regionspecific anthropometric data of women workers. However, measuring and recording anthropometric dimensions is time-consuming and economically taxable. In the present study, regression models have been developed to predict different anthropometric dimensions using anthropometric data of 79 body dimensions of 720 women workers in central India aged between 25 and 55 years. Principal component and factorial analysis techniques were employed to extract significant body dimensions. The major objective of this study was to predict various anthropometric dimensions by regression models so that the time and effort required for several body dimension measurements would be reduced. [ABSTRACT FROM AUTHOR]

In Indian subcontinent, pineapple (Ananas Comosus) leaves are left unused after fruits are harvested resulting in a waste of natural resources that contain textile-graded fibers. The present study intended to develop a pineapple leaf fiber extractor to chip off the waxy layer of the leaf. The machine comprised feeding conveyor, feed rollers, scratching roller, combing roller, frame and motor as a power source with a transmission unit. The performance was evaluated under different independent variables, i.e. rpm of the scratching roller (100, 150 and 200 rpm), types of secondary roller (combing, serration and without secondary roller) and moisture content of leaf (85 ± 3, 78 ± 3 and 71 ± 2%). Response surface method of optimization was employed to optimize the operational parameters. Best combination of operating parameters was found to be 150 rpm scratching rollers, combing type secondary rollers and moisture content of 85 ± 3%. It was found that the retting duration, processing efficiency, and fiber yield were 4 days, 88.9%, and 2.41% at optimized parameters, respectively. Further, throughput capacity and power requirement were found to be 33 ± 2 kg/hand 1.5 kWh respectively. The developed machine found to be effective in extracting waxy layer on leaves with minimal damage to useable fiber. [ABSTRACT FROM AUTHOR]