Application of Spectrophotometer and Photocolorimetric Method from Mobile Phone for Soybean Meal Rawness Measurement
Authors:   Faculty of Animal Sciences and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Nopparatmaitree Manatsanun , Kongsabai Nuttamon ,   Faculty of Animal Sciences and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Sukkee Yada ,   Faculty of Animal Sciences and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Chotnipat Soranot ,   Faculty of Animal Sciences and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Pootaeng-on Yupa ,   Faculty of Animal Sciences and Agricultural Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Thongnum Atichat ,   Department of Animal science and Fishery, Faculty of Sciences and Agricultural Technology,  Rajamangala University of Technology Lanna (Phitsanulok Campus) Phitsanulok, Thailand, 65000, Glinubon Jinda ,   Department of Animal Science, Faculty of Agriculture, Ubon Ratchatani University, Warin Chamrap, Ubon Ratchathani, 34190, Arkaphati Chanchai ,   Faculty of Information and Communication Technology, Silpakorn University, Phetchaburi IT Campus, Cha-am, Phetchaburi, 76120, Chaowalit Orawan ,   Department of Computing, Faculty of Sciences, Silpakorn University, Sanam Chandra Palace Campus, Nakhon Pathom, 73000
Published: September 2023

This study aimed to create a detection method for measuring rawness of soybean meals using a spectrophotometer and photocolorimetric method. A relationship between the percentage of the rawness of soybeans was studied by the detection of urease content using phenol red as an indicator. Absorbance values from the spectrophotometer, and color values generated by the Adobe Photoshop software from the picture of IOS and Android mobile phones were then measured. The results showed that the percentage of the rawness of soybeans was positively correlated with absorbance values from the spectrophotometer (r = 0.942) (P < 0.01) with the form of the linear regression equation, y = 33.738x - 13.236 (R² = 0.886). In addition, the percentage of the rawness of soybeans was negatively correlated with the yellow (b*) values from IOS (r = -0.955) (P < 0.01) with the form of the linear regression equation, y = -0.3001x + 12.645 (R² = 0.912). Furthermore, the percentage of the rawness of soybeans was negatively correlated with the green (G) values from Android (r = -0.964) (P < 0.01) with the form of the linear regression equation, y = -0.1119x + 18.395 (R² = 0.929). Moreover, the percentage of the rawness of soybeans was negatively correlated with the green (G) values from Mobile (r = -0.941) (P < 0.01) with the form of the linear regression equation, y = -0.1093x + 17.727 (R² = 0.886). The rawness of soybeans by spectrophotometer and photocolorimetric methods were then compared. This experimental design was a completely randomized design (CRD) consisting of 4 treatments (spectrophotometer analysis and photocolorimetric method from IOS Android, and mobile phones), and divided into 10 replications per treatment. The results showed a statistically significant difference between a method for determining rawness in soybean meal based on spectrophotometer analysis and a photocolorimetric method (P < 0.01). The results from the spectrophotometer analysis method for measuring the rawness of soybean meal produced were close to the actual rawness value and can be used to inspect the quality of soybean meal.