{"id":"https://openalex.org/W7119517751","doi":"https://doi.org/10.1201/9781032659398-5","title":"Basmati Rice Yield Prediction Using Machine Learning Techniques","display_name":"Basmati Rice Yield Prediction Using Machine Learning Techniques","publication_year":2026,"publication_date":"2026-01-08","ids":{"openalex":"https://openalex.org/W7119517751","doi":"https://doi.org/10.1201/9781032659398-5"},"language":"en","primary_location":{"id":"doi:10.1201/9781032659398-5","doi":"https://doi.org/10.1201/9781032659398-5","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781032659398-5","pdf_url":null,"source":{"id":"https://openalex.org/S4306463075","display_name":"CRC Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320584","host_organization_name":"CRC Press","host_organization_lineage":["https://openalex.org/P4310320584","https://openalex.org/P4310320547"],"host_organization_lineage_names":["CRC Press","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Aromatic Basmati Rice","raw_type":"book-chapter"},"volume":{"id":"https://openalex.org/W7119529973","display_name":"Aromatic Basmati Rice"},"type":"book-chapter","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083803094","display_name":"Manik H. Kalubarme","orcid":"https://orcid.org/0000-0002-0977-7671","observed_orcids":["https://orcid.org/0000-0002-0977-7671"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manik H. Kalubarme","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0977-7671","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110282531","display_name":"Dharmesh Verma","orcid":"https://orcid.org/0000-0003-2012-883X","observed_orcids":["https://orcid.org/0000-0003-2012-883X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dharmesh Verma","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2012-883X","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122359919","display_name":"Ritesh Sharma","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ritesh Sharma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103550603","display_name":"A.N. Singh","orcid":"https://orcid.org/0009-0002-0306-9719","observed_orcids":["https://orcid.org/0009-0002-0306-9719"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A.N. Singh","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0002-0306-9719","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"162","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.6133000254631042,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.6133000254631042,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12045","display_name":"Rice Cultivation and Yield Improvement","score":0.25220000743865967,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.06830000132322311,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/basmati-rice","display_name":"basmati rice","score":0.9869999885559082},{"id":"https://openalex.org/keywords/rice-yield-prediction","display_name":"rice yield prediction","score":0.7799999713897705},{"id":"https://openalex.org/keywords/extreme-gradient-boosting","display_name":"extreme gradient boosting","score":0.8769999742507935},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9980000257492065},{"id":"https://openalex.org/keywords/karnal-district","display_name":"Karnal district","score":0.7300000190734863},{"id":"https://openalex.org/keywords/indo-gangetic-plain","display_name":"Indo-Gangetic Plain","score":0.875},{"id":"https://openalex.org/keywords/crop-yield-prediction","display_name":"crop yield prediction","score":0.4869999885559082}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6158000230789185},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.49239999055862427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43630000948905945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4235000014305115},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3361999988555908},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.274399995803833},{"id":"https://openalex.org/C2982736386","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Statistical learning","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.2655999958515167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/9781032659398-5","doi":"https://doi.org/10.1201/9781032659398-5","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781032659398-5","pdf_url":null,"source":{"id":"https://openalex.org/S4306463075","display_name":"CRC Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320584","host_organization_name":"CRC Press","host_organization_lineage":["https://openalex.org/P4310320584","https://openalex.org/P4310320547"],"host_organization_lineage_names":["CRC Press","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Aromatic Basmati Rice","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.991100013256073,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4412621716","https://openalex.org/W4402027810","https://openalex.org/W2948819314","https://openalex.org/W4411092853","https://openalex.org/W7142120439","https://openalex.org/W4393197645","https://openalex.org/W4226340062","https://openalex.org/W4399257460","https://openalex.org/W1558806628","https://openalex.org/W4403156154"],"abstract_inverted_index":{"Accurate":[0],"pre-harvest":[1,111],"estimation":[2,113],"of":[3,91,114,120,135,142,159,201,246],"rice":[4,77,116,266],"yield":[5,69,78,112,160,267],"at":[6],"district":[7,119],"and":[8,19,32,46,53,65,82,93,105,139,167,193,225,261,285,297],"state":[9],"levels":[10],"is":[11],"essential":[12],"for":[13,68,110,212,222,233,264],"national":[14],"production":[15],"forecasting,":[16],"evidence-based":[17],"policymaking,":[18],"enhancing":[20],"farmers\u2019":[21],"incomes":[22],"through":[23],"market-aligned":[24],"strategies.":[25],"Traditional":[26],"methods,":[27],"such":[28,274],"as":[29,155,257,275],"field":[30],"surveys":[31],"farmer":[33],"interviews,":[34],"are":[35,39],"widely":[36],"used":[37,81],"but":[38,171],"often":[40],"limited":[41,173],"by":[42,131,174,181,293],"subjectivity,":[43],"high":[44,251],"costs,":[45],"delayed":[47],"outputs.":[48],"Recent":[49],"advancements":[50],"in":[51,117,300],"RS":[52],"GIS\u2013based":[54],"geospatial":[55],"technologies,":[56],"combined":[57],"with":[58,242],"crop":[59],"growth":[60],"models,":[61,96,273],"offer":[62],"scalable,":[63],"cost-effective,":[64],"timely":[66],"alternatives":[67],"forecasting.":[70,268],"This":[71,149],"chapter":[72],"reviews":[73],"different":[74],"rice/aromatic":[75],"Basmati":[76,115,224,240,265],"models":[79],"being":[80],"also":[83],"presents":[84],"a":[85,258],"case":[86],"study":[87],"evaluating":[88],"the":[89,132,136,140,146,156,213],"use":[90],"empirical":[92],"machine":[94],"learning":[95,272],"moderate":[97],"multiple":[98],"linear":[99,176],"regression":[100],"(MMLR),":[101],"random":[102],"forest":[103],"(RF),":[104],"extreme":[106],"gradient":[107],"boosting":[108],"(XGBoost),":[109],"Karnal":[118],"Haryana.":[121],"The":[122],"modelling":[123],"was":[124,172],"based":[125],"exclusively":[126],"on":[127],"weather":[128,152],"variables,":[129],"supported":[130],"agroecological":[133],"uniformity":[134],"Indo-Gangetic":[137],"Plains":[138],"prevalence":[141],"assured":[143],"irrigation":[144],"across":[145,190],"Basmati-growing":[147],"area.":[148],"ensures":[150],"that":[151],"parameters":[153],"serve":[154],"primary":[157],"drivers":[158],"variability.":[161],"MMLR":[162],"delivered":[163],"reasonable":[164],"accuracy":[165,292],"(RMSE":[166],"MAPE":[168],"within":[169],"15%)":[170],"its":[175],"structure.":[177],"RF":[178],"improved":[179],"performance":[180],"capturing":[182,294],"nonlinear":[183],"interactions,":[184],"while":[185],"XGBoost":[186,205,249,256],"consistently":[187],"outperformed":[188],"both,":[189],"long-duration,":[191],"traditional,":[192],"short-duration":[194,239],"varietal":[195],"groups,":[196],"using":[197],"17":[198],"years":[199,245],"(2007\u20132023)":[200],"historical":[202],"data.":[203],"Notably,":[204],"demonstrated":[206],"strong":[207],"generalization,":[208],"accurately":[209],"forecasting":[210],"yields":[211],"unseen":[214],"year":[215],"2024.":[216],"It":[217],"achieved":[218],"optimal":[219],"bias\u2013variance":[220],"trade-offs":[221],"long-duration":[223],"perfect":[226],"Test":[227],"https://www.w3.org/1998/Math/MathML\"":[228],"display=\"inline\">":[229],"R":[230],"2":[231],"values":[232],"traditional":[234],"types.":[235],"For":[236],"recently":[237],"released":[238],"varieties,":[241],"only":[243],"12":[244],"data":[247],"(2012\u20132023),":[248],"maintained":[250],"reliability.":[252],"These":[253],"results":[254],"establish":[255],"robust,":[259],"generalisable,":[260],"climate-resilient":[262],"tool":[263],"Looking":[269],"ahead,":[270],"deep":[271],"long":[276],"short-term":[277],"memory":[278],"(LSTM)":[279],"networks,":[280],"convolutional":[281],"neural":[282],"networks":[283],"(CNNs),":[284],"transformer-based":[286],"architectures,":[287],"may":[288],"further":[289],"enhance":[290],"predictive":[291],"complex,":[295],"nonlinear,":[296],"temporal":[298],"dynamics":[299],"yield-predictor":[301],"relationships.":[302]},"counts_by_year":[],"updated_date":"2026-10-10T09:11:00.788812","created_date":"2026-01-09T00:00:00"}