A Literature Review on Image Processing and Classification Techniques for Agriculture Produce and Modeling of Quality Assessment system for Soybean industry Sample
{"title":"A Literature Review on Image Processing and Classification Techniques for Agriculture Produce and Modeling of Quality Assessment system for Soybean industry Sample","authors":"Sachin Sonawane, M. Awasthy, N. Choubey","doi":"10.20431/2349-4050.0602002","DOIUrl":null,"url":null,"abstract":"Soybean is the most admired and favored food in the world. It is readily available in all the countries. Because of richness in protein, it is recommended and consumed in the daily food. Variety of valueadded edible products can be prepared from Soybean including Soya-Milk, Oil, Pulses etc. for human as well as animals. The countries having major share in Soybean production are United States, Brazil, Argentina, China and India [1]. In international food market, the quality of Soybean is a major concerning order to assure the production of best tertiary product by food industry. To ease the trading process the countries like US, Canada have recommended certain criteria and standards to buyers for grading Soybean quality. Thus, the measurement of Soybean quality is essential as well as an equally important requirement in today‟s scenario to protect the buyers from substandard produce [2]. Accordingly, if the Soybean quality assessment is done manually then the chance of error in measurement is significant and in case it is done with the help of a perfectly trained automatic machine then the chance of error would be minimum. On these aspects, this research work is directed towards the modeling of an automated system for the quality measurements of Soybean Sample [3].","PeriodicalId":286316,"journal":{"name":"International Journal of Innovative Research in Electronics and Communications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Research in Electronics and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20431/2349-4050.0602002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Soybean is the most admired and favored food in the world. It is readily available in all the countries. Because of richness in protein, it is recommended and consumed in the daily food. Variety of valueadded edible products can be prepared from Soybean including Soya-Milk, Oil, Pulses etc. for human as well as animals. The countries having major share in Soybean production are United States, Brazil, Argentina, China and India [1]. In international food market, the quality of Soybean is a major concerning order to assure the production of best tertiary product by food industry. To ease the trading process the countries like US, Canada have recommended certain criteria and standards to buyers for grading Soybean quality. Thus, the measurement of Soybean quality is essential as well as an equally important requirement in today‟s scenario to protect the buyers from substandard produce [2]. Accordingly, if the Soybean quality assessment is done manually then the chance of error in measurement is significant and in case it is done with the help of a perfectly trained automatic machine then the chance of error would be minimum. On these aspects, this research work is directed towards the modeling of an automated system for the quality measurements of Soybean Sample [3].