Estimation of rice yield using multivariate analysis techniques based on meteorological parameters.
Estimation
Multivariate analysis
RMSE and MAPE
Rice yield
Weather parameters
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
01 Jun 2024
01 Jun 2024
Historique:
received:
31
01
2024
accepted:
30
05
2024
medline:
2
6
2024
pubmed:
2
6
2024
entrez:
1
6
2024
Statut:
epublish
Résumé
This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980-81 to 2020-21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.
Identifiants
pubmed: 38824223
doi: 10.1038/s41598-024-63596-6
pii: 10.1038/s41598-024-63596-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
12626Informations de copyright
© 2024. The Author(s).
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