Abstract

Fragmentation of paddy grains can be accelerated by the treatments and process during harvest, field-handling, drying, transportation, and upon milling. The main cause of shattering among others is the moisture content (MC) of the grains. Higher MC prompts the grain to be more fragile. In general, paddy grains with 13-14% MC are ideal for post-harvest processing. The objective of this study is to measure MC of intact paddy grain from c.v. Simauang by means of nondestructive evaluation using UV-VIS-NIR spectral assessment. The paddy grains samples with identical MC were put into 5mm quartz cuvette, and measured using UV-1600 spectrophotometer. The electromagnetic radiation absorbance under consideration upon spectral measurement fell between 190 and 1100nm. The grains’ actual MC then measured by primary method, based on weight measurement e.g. oven method. The samples are paddy grains which just had been harvested. Samples were then dried until its MC reduced by 2% before the measurements replicated. The measurements were stopped when the grain MC reached 9%. In this study, the Spectral data of the grains then preprocessed by means of Principal Component Analysis (PCA) before correlated with its moisture contents by Multi-layer-Perceptron Artificial-Neural-Network (MLP ANN) method. The developed model produce coefficient of correlation (R2) of 0.975, relative error of 0.1% and area under ROC curve of 1, indicating that the MC of paddy grains c.v. Simauang can be precisely identified by means of nondestructive evaluation using spectral analysis.

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