C. Kanchanomai, K. Nakano, D. Naphrom, K. Takizawa, Yating Xiong, Phonkrit Maniwara, S. Ohashi
{"title":"可见波长成像光谱法测定鲜食葡萄品质的实验研究","authors":"C. Kanchanomai, K. Nakano, D. Naphrom, K. Takizawa, Yating Xiong, Phonkrit Maniwara, S. Ohashi","doi":"10.12982/cmjs.2022.0085","DOIUrl":null,"url":null,"abstract":"Imaging and spectroscopy are non-destructive techniques for determining fruit qualities. The qualities of table grapes (Vitis vinifera) such as soluble solids content (SSC), pH, fi rmness and seedlessness are key parameters. This research was focused on comparison between imaging and spectroscopy in laboratory and fi eld. The results of Partial least squares regression (PLSR) showed that the best coeffi cient of determination (R2) for prediction (R2 pred) on SSC for laboratory was 0.8085, for fi eld was 0.8169, and for imaging was 0.7994. The best R2 pred on fi rmness for laboratory was 0.6925, for fi eld was 0.5737, and for imaging was 0.6216. The best R2 pred on pH for laboratory was 0.6820, for fi eld was 0.7101 and for imaging was 0.6494. Partial least squares discriminant analysis (PLS-DA) was analyzed the successful percentage of seedlessness classifi cation: 89.66%, 93.10% and 81.25% for spectroscopy in laboratory, fi eld and imaging, respectively. The results of SSC and seedlessness in fi eld are almost same effi cient as in laboratory. That means farmer can do spectroscopy on SSC and seedlessness anywhere and non-destructively. By the way, we can use both techniques as effi cient non-destructive techniques for determining these key parameters of table grape qualities.","PeriodicalId":9884,"journal":{"name":"Chiang Mai Journal of Science","volume":"139 1","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental Study of Determining Technique for Table Grape Qualities using Visible Wavelength of Imaging and Spectroscopy\",\"authors\":\"C. Kanchanomai, K. Nakano, D. Naphrom, K. Takizawa, Yating Xiong, Phonkrit Maniwara, S. Ohashi\",\"doi\":\"10.12982/cmjs.2022.0085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Imaging and spectroscopy are non-destructive techniques for determining fruit qualities. The qualities of table grapes (Vitis vinifera) such as soluble solids content (SSC), pH, fi rmness and seedlessness are key parameters. This research was focused on comparison between imaging and spectroscopy in laboratory and fi eld. The results of Partial least squares regression (PLSR) showed that the best coeffi cient of determination (R2) for prediction (R2 pred) on SSC for laboratory was 0.8085, for fi eld was 0.8169, and for imaging was 0.7994. The best R2 pred on fi rmness for laboratory was 0.6925, for fi eld was 0.5737, and for imaging was 0.6216. The best R2 pred on pH for laboratory was 0.6820, for fi eld was 0.7101 and for imaging was 0.6494. Partial least squares discriminant analysis (PLS-DA) was analyzed the successful percentage of seedlessness classifi cation: 89.66%, 93.10% and 81.25% for spectroscopy in laboratory, fi eld and imaging, respectively. The results of SSC and seedlessness in fi eld are almost same effi cient as in laboratory. That means farmer can do spectroscopy on SSC and seedlessness anywhere and non-destructively. By the way, we can use both techniques as effi cient non-destructive techniques for determining these key parameters of table grape qualities.\",\"PeriodicalId\":9884,\"journal\":{\"name\":\"Chiang Mai Journal of Science\",\"volume\":\"139 1\",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chiang Mai Journal of Science\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.12982/cmjs.2022.0085\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chiang Mai Journal of Science","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.12982/cmjs.2022.0085","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Experimental Study of Determining Technique for Table Grape Qualities using Visible Wavelength of Imaging and Spectroscopy
Imaging and spectroscopy are non-destructive techniques for determining fruit qualities. The qualities of table grapes (Vitis vinifera) such as soluble solids content (SSC), pH, fi rmness and seedlessness are key parameters. This research was focused on comparison between imaging and spectroscopy in laboratory and fi eld. The results of Partial least squares regression (PLSR) showed that the best coeffi cient of determination (R2) for prediction (R2 pred) on SSC for laboratory was 0.8085, for fi eld was 0.8169, and for imaging was 0.7994. The best R2 pred on fi rmness for laboratory was 0.6925, for fi eld was 0.5737, and for imaging was 0.6216. The best R2 pred on pH for laboratory was 0.6820, for fi eld was 0.7101 and for imaging was 0.6494. Partial least squares discriminant analysis (PLS-DA) was analyzed the successful percentage of seedlessness classifi cation: 89.66%, 93.10% and 81.25% for spectroscopy in laboratory, fi eld and imaging, respectively. The results of SSC and seedlessness in fi eld are almost same effi cient as in laboratory. That means farmer can do spectroscopy on SSC and seedlessness anywhere and non-destructively. By the way, we can use both techniques as effi cient non-destructive techniques for determining these key parameters of table grape qualities.
期刊介绍:
The Chiang Mai Journal of Science is an international English language peer-reviewed journal which is published in open access electronic format 6 times a year in January, March, May, July, September and November by the Faculty of Science, Chiang Mai University. Manuscripts in most areas of science are welcomed except in areas such as agriculture, engineering and medical science which are outside the scope of the Journal. Currently, we focus on manuscripts in biology, chemistry, physics, materials science and environmental science. Papers in mathematics statistics and computer science are also included but should be of an applied nature rather than purely theoretical. Manuscripts describing experiments on humans or animals are required to provide proof that all experiments have been carried out according to the ethical regulations of the respective institutional and/or governmental authorities and this should be clearly stated in the manuscript itself. The Editor reserves the right to reject manuscripts that fail to do so.