คำอธิบาย
Sontisuk Teerachaichayut
Non-destructive techniques have been applied successfully to predict internal quality in many kinds of foods and agricultural products. There were many research reports that showed empirical studies of the techniques in application have been demonstrated to offer rapid evaluation of qualities in both quantitative and qualitative analyses. Independent variables were measured related to dependent variables to establish the precise calibration models for evaluating internal qualities of foods and agricultural products. The techniques were studied including electrical based technique for detecting of granulation in tangerine fruit, predicting texture of jelly, classifying the freshness of sweet corn, determining moisture content of lime, photoelectric sensor technique for classifying the freshness of hen’s eggs, predicting granulation disorder in tangerines, image processing technique for determining mangosteen density, Near infrared spectroscopy (NIRs) technique for detecting borax in pork meatball, evaluating freshness of hen eggs, detecting quality for marian plum, predicting pH and total soluble solids of lime, classifying sweet corn based on storage time, predicting moisture content in sweet corn, classifying lime varieties, detecting internal mold infection in sweet tamarind, predicting nitrate level and internal browning in pineapple, detecting internal defects in mangosteen, detecting soluble solids content in Intact tomato, Fourier transform infrared spectroscopy (FTIRs) technique for assessing the levels of Robusta and Arabica in roasted ground coffee and hyperspectral imaging (HSI) technique for predicting the maturity index of intact pineapples, detecting texture and total soluble solids in jelly, predicting recovery yield of pineapple, detecting quality of dehydrated ginger, evaluating adulteration in tapioca starch, determining and classifying shelf life of cakes, detecting adulteration in Thai Pathumthani fragrant rice, assessing acidity and total soluble solids in guavas, predicting quality of hens' eggs.