Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/27/2017
Publication Date: N/A
Citation: N/A Interpretive Summary: Sesame and chickpeas are important crops for Ethiopia as both are major exports providing small farmers and the country much revenue. Proper storage of these crops to prevent post-harvest loss is a major challenge made more difficult by the lack of availability of affordable moisture meters. USDA-ARS previously developed a low-cost moisture meter which measures moisture content using relative humidity (RH) and temperature (T) measurements of the static air within the grain. Moisture content is mathematically calculated from RH and T and requires calibration for each crop type. The work that was conducted was to determine meter calibrations for Kabuli chickpea, and black and white sesame. Moisture content measurement error using the determined calibrations was found to be about 0.5% for Kabuli chickpea and 0.25% for both black and white sesame. Calibrations for the two sesame types were found to be different and thus require separate calibration parameters. The new calibrations developed will provide accurate measurement of these three crops and will provide farmers a method to monitor harvesting, drying, storage and conditioning of these crops. This work will help minimize post-harvest losses and return more food or income back to the farmer.
Technical Abstract: Sesame and chickpeas are important crops for Ethiopia as both are major exports providing small farmers and the country much revenue. There is a lack of information on fundamental equilibrium moisture content (EMC) relationships for these products which would help facilitate better monitoring and storage. For this reason EMC adsorption and desorption prediction models based on temperature (T) and relative humidity (RH) were developed for the modified Chung-Pfost and modified Henderson models for kabuli chickpea (KC), black sesame (BS), and white sesame (WS) seeds. Samples for adsorption and desorption tests were conditioned to various moisture content (MC) levels for EMC test models. Samples (~500 gm) were placed in multiple sealed enclosures equipped with T and RH sensors, placed in an environmental chamber, and exposed to three temperatures (15oC, 25oC, and 35oC). For KC samples, the MCdb% ranges used for model development were 11.6%-19.5% and 8.9%-16.9% for adsorption and desorption, respectively; for BS, the range was 5.0%-8.7% and 4.3%-6.9%, respectively, and for WS, 4.2%-8.7% and 3.5%-7.6%, respectively. Nonlinear regression was used to determine model coefficients for the modified Henderson and modified Chung-Pfost equations. Prediction statistics for KC adsorption and desorption models yielded a SEE of 0.53% and 0.68% MCdb, respectively; for BS, SEE was 0.23% and 0.13%, respectively; and for WS, SEE was 0.28% and 0.25%, respectively. Model coefficients will be used in a moisture meter based on EMC measurement which is currently being used as part of a USAID postharvest project in various African and Asian countries. These EMC models may also be important for other grain operations which include harvesting, drying, storage, conditioning, and processing.