This effects of combined microwave and hot air on drying of sapota (Acharas zapota L.) slices were studied. The slices were dried from the initial moisture level of 75-78 % (w.b.) to a final moisture content of ~10 % (w.b.). Process parameters such as drying time, moisture diffusivity, specific energy consumption and quality attributes of dried sapota slices were evaluated. Drying time at the power level of 2 W.g-1 reduced up to 14 to 21 times compared to only hot air drying. Dincer and Dost model was used to estimate Biot number and mass transfer coefficient which ranged from 0.29 to 1.23, and 0.23×10-7 m.s-1 to 8.81×10-7 m.s-1, respectively. Specific energy consumption was reduced by 12 to 17 times during combination drying (2 W.g-1, 50-70 °C) compared to only hot air drying (50-70 °C). Process modelling results indicated that Midilli model was best fitted describing the drying kinetics of sapota slices during combination drying. Optimization for better quality dried sapota slices suggested slice thickness of 5 mm using combination of microwave (1.5 W.g-1) and hot air drying (60 °C).
Physical properties of quality protein maize (var. HQPM-1 and Vivek QPM) kernels were evaluated as a function of moisture content in the range of 15- 45 % (w.b.). Length, width, and thickness of HQPM increased linearly from 10.09 mm to 10.35 mm, 8.05 mm to 8.44 mm, and 4.45 mm to 4.93 mm, respectively. The increase in dimensions of Vivek QPM was from 9.93 mm to 10.51 mm, 8.11 mm to 8.53 mm, and 4.25 mm to 4.76 mm, respectively. Sphericity, surface area, and volume of both QPM varieties increased linearly with moisture content. True density decreased from 1210.81 kg.m-3 to 1193.0 kg.m-3 for HQPM-1, and 1247.55 kg.m-3 to 1163.15 kg.m-3 for Vivek QPM variety; while bulk density decreased from 761.65 kg.m-3 to 662.12 kg.m-3 for HQPM-1, and 740.45 kg.m-3 to 687.48 kg.m-3 for Vivek QPM variety. Static and dynamic angle of repose of the kernels underwent polynomial increase with increasing moisture content. Highest value of static coefficient of friction of QPM was observed on wooden surface, followed by cast iron, aluminium and galvanised iron, owing to their surface characteristics.
Viability assessment of bacteria is critical in monitoring of food or environmental samples. Existing methods are time-consuming, labour-intensive or require trained manpower and costly chemicals. Potential of commonly used UV-visual spectrometer was explored for rapid viability detection of Escherichia coli (ATCC 8739). Spectra of samples (live and dead cells) mixed in different proportion revealed clear differences. Live bacterial suspension showed absorption peak at 260 nm with decreasing amplitude as the proportion of live bacteria was reduced in the suspension and vice-versa. Principal component analyses (PCA) of spectral data showed clear clustering of samples based on the level of live bacterial cells (5 % significance level). Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLSDA) yielded 100 % correct classification with test samples. The percentage of live and dead bacteria in a suspension could be predicted with coefficient of determination (R2) of 0.980 and 0.977 for calibration and validation sample sets, respectively, in the range of 259-261 nm using Multiple Linear Regression (MLR). Low standard errors of calibration (4.5), prediction (4.8) and high R2 (0.98) indicated the potential of UV visual spectrometer to detect and predict live and dead cells of E. coli in a suspension.
Agricultural land-suitability analysis is a prerequisite to achieve optimum utilization of the available land resources for sustainable agricultural production. The Analytical Hierarchy Process (AHP) technique coupled with Geographic Information System (GIS) can be a unique tool for land-suitability studies. AHP-GIS technique based on soil nutrient criteria of soil texture, pH, organic carbon, electric conductivity, available nitrogen, phosphorous, potassium, and zinc was used for land-suitability assessment in Tarkeswar Block, Hooghly district, West Bengal for growing potato. The study area was classified into suitable land categories based on soil nutrient levels analysed from 50 randomly-selected plot-based soil samples. Pair-wise comparison matrix-based ranking was computed considering the importance of each criterion for potato crop in the area. Suitability maps were developed and analysed in ArcGIS software environment. The total area was classified into ‘highly suitable’ class occupying 61 ha (21%), ‘moderately suitable’ class in 195 ha (67%), ‘marginally suitable’ class in 32 ha (11%) and ‘not suitable’ class in 3 ha (1%) land areas. Yield distribution map of potato crop showed nearly 106 ha (36.5%) area producing higher tuber yield of 20 t.ha-1. The proposed suitability map was validated against crop yield map where nearly 253 ha (87%) area classified under ‘highly suitable’ to ‘moderately suitable’ classes was found to give better potato yield of 15 t.ha-1or more. The AHP-GIS technique can be used for crop rotation analysis for multiple seasons for better crop selection in long run.