{"title":"利用Ms Office 2016软件开发锡金地区最优农场匹配预测模型","authors":"Singh Mu","doi":"10.38177/ajast.2020.4208","DOIUrl":null,"url":null,"abstract":"Choice and usage of optimum tractor power and agricultural machinery size is important to decrease cost and complete agricultural operations in available time. Improper size machinery increases the production costs in the farms. Determination of optimum tractor power and machinery size is a tedious and complex procedure that requires many calculations and computational work. In this study, a Microsoft office 2016 software was developed to enable the model and imitate different conditions to determine optimum size of farm machinery and power considering all parameters for selection of farm machinery base on “the least cost method” for Sikkim. The program developed in this study was applied to the representative farm size and crops such as buck wheat, rice, and maize.","PeriodicalId":267570,"journal":{"name":"Agriculture Engineering eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a Model to Predict and Intimate Optimum Farm Matching System for Sikkim Using Ms Office 2016 Software\",\"authors\":\"Singh Mu\",\"doi\":\"10.38177/ajast.2020.4208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Choice and usage of optimum tractor power and agricultural machinery size is important to decrease cost and complete agricultural operations in available time. Improper size machinery increases the production costs in the farms. Determination of optimum tractor power and machinery size is a tedious and complex procedure that requires many calculations and computational work. In this study, a Microsoft office 2016 software was developed to enable the model and imitate different conditions to determine optimum size of farm machinery and power considering all parameters for selection of farm machinery base on “the least cost method” for Sikkim. The program developed in this study was applied to the representative farm size and crops such as buck wheat, rice, and maize.\",\"PeriodicalId\":267570,\"journal\":{\"name\":\"Agriculture Engineering eJournal\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agriculture Engineering eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38177/ajast.2020.4208\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agriculture Engineering eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38177/ajast.2020.4208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a Model to Predict and Intimate Optimum Farm Matching System for Sikkim Using Ms Office 2016 Software
Choice and usage of optimum tractor power and agricultural machinery size is important to decrease cost and complete agricultural operations in available time. Improper size machinery increases the production costs in the farms. Determination of optimum tractor power and machinery size is a tedious and complex procedure that requires many calculations and computational work. In this study, a Microsoft office 2016 software was developed to enable the model and imitate different conditions to determine optimum size of farm machinery and power considering all parameters for selection of farm machinery base on “the least cost method” for Sikkim. The program developed in this study was applied to the representative farm size and crops such as buck wheat, rice, and maize.