Application of thermal imaging combined with machine learning for detecting the deterioration of the cassava root.

Freshness is an important parameter that is indexed in the quality assessment of commercial cassava tubers. Cassava tubers that are not fresh have reduced starch content. Therefore, in this study, we aimed to develop a new approach to detect cassava root deterioration levels using thermal imaging with machine learning (ML).

Modified specific gravity method for estimation of starch content and dry matter in cassava.

An empirical model for the estimation of starch content (SC) and dry matter (DM) in cassava tubers was developed as an alternative method to polarimetry and dry oven. These improved estimation equations were developed based on the specific gravity (SG) method. To improve accuracy, the one hundred-seventy-four sample were obtained from four commercial varieties of cassava in Thailand including KU50, CMR38-125-77, RY9 and RY11, respectively.

Predicting Marian Plum Fruit Quality without Environmental Condition Impact by Handheld Visible-Near-Infrared Spectroscopy.

Handheld near-infrared spectroscopy was used to study the effect of integration time and wavelength selection on predicting marian plum quality including soluble solids content (SSC), the potential of hydrogen ion (pH), and titratable acidity (TA). For measurements representing actual conditions, the on-tree fruits were scanned under in-field conditions. The assumption was that the robust model might be achieved when the models were developed under actual conditions.

Stress and acid-base balance in chickens.

Two trials were conducted to study the effects of continuous infusion of adrenocorticotropic hormone (ACTH) on acid-base balance in broiler chickens. Osmotic pumps delivered 8 IU of ACTH in saline/kg of BW/d for 7 d or the same saline volume as used in ACTH at 1 microL/h for 7 d. Blood samples were taken on d 0 (baseline values) and on d 4, 7, and 14 after onset of the infusions.