BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS
This research article aims to give a description of the level of rice production in Albuera, Leyte, Philippines, and determine the statistically significant predictors affecting it. The study used primary and cross-sectional data from small-scale farmers (with 2-hectare rice farms or less) through a...
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| Format: | Article |
| Language: | English |
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University of Agricultural Sciences and Veterinary Medicine, Bucharest
2024-01-01
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| Series: | Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development |
| Online Access: | https://managementjournal.usamv.ro/pdf/vol.24_1/Art15.pdf |
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| author | Leomarich F. CASINILLO Virgelio C. DARGANTES JR. |
| author_facet | Leomarich F. CASINILLO Virgelio C. DARGANTES JR. |
| author_sort | Leomarich F. CASINILLO |
| collection | DOAJ |
| description | This research article aims to give a description of the level of rice production in Albuera, Leyte, Philippines, and determine the statistically significant predictors affecting it. The study used primary and cross-sectional data from small-scale farmers (with 2-hectare rice farms or less) through a face-to-face interview with the aid of a constructed questionnaire. The gathered information was summarized with the assistance of descriptive metrics and presented in a tabular form. In addition, binary logistic modeling was constructed to extract influencing predictors of the level of rice production and tested its significance. Results portrayed that more farmers in Albuera, Leyte are experiencing a low level of rice production. The findings of the study depicted that small-scale farmers do not have enough capital to buy the necessary agricultural inputs due to their high prices in the market. Plus, farmers do not have sufficient credit facilities that they may use for their farming process and it is also shown that farmers are adversely affected by pests and diseases that destroy their rice cultivation. The binary logistic model shows that a married farmer, with a lower monthly income and with a smaller paddy farm tends to have a higher production level. Moreover, another regression model revealed that the presence of pests and diseases, and being provided with solutions by extension agents are significant predictors of high production levels in rice farming. The study suggests that small-scale farmers in rural areas must be supported regarding their capital and farming facilities, and must be guided and facilitated by expert extension agents in solving different problems. |
| format | Article |
| id | doaj-art-cff22ec6a44b40ac9abc1a63f5833f89 |
| institution | Kabale University |
| issn | 2284-7995 2285-3952 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | University of Agricultural Sciences and Veterinary Medicine, Bucharest |
| record_format | Article |
| series | Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development |
| spelling | doaj-art-cff22ec6a44b40ac9abc1a63f5833f892025-08-20T03:45:39ZengUniversity of Agricultural Sciences and Veterinary Medicine, BucharestScientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development2284-79952285-39522024-01-01241157166395BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORSLeomarich F. CASINILLOVirgelio C. DARGANTES JR.This research article aims to give a description of the level of rice production in Albuera, Leyte, Philippines, and determine the statistically significant predictors affecting it. The study used primary and cross-sectional data from small-scale farmers (with 2-hectare rice farms or less) through a face-to-face interview with the aid of a constructed questionnaire. The gathered information was summarized with the assistance of descriptive metrics and presented in a tabular form. In addition, binary logistic modeling was constructed to extract influencing predictors of the level of rice production and tested its significance. Results portrayed that more farmers in Albuera, Leyte are experiencing a low level of rice production. The findings of the study depicted that small-scale farmers do not have enough capital to buy the necessary agricultural inputs due to their high prices in the market. Plus, farmers do not have sufficient credit facilities that they may use for their farming process and it is also shown that farmers are adversely affected by pests and diseases that destroy their rice cultivation. The binary logistic model shows that a married farmer, with a lower monthly income and with a smaller paddy farm tends to have a higher production level. Moreover, another regression model revealed that the presence of pests and diseases, and being provided with solutions by extension agents are significant predictors of high production levels in rice farming. The study suggests that small-scale farmers in rural areas must be supported regarding their capital and farming facilities, and must be guided and facilitated by expert extension agents in solving different problems.https://managementjournal.usamv.ro/pdf/vol.24_1/Art15.pdf |
| spellingShingle | Leomarich F. CASINILLO Virgelio C. DARGANTES JR. BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development |
| title | BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS |
| title_full | BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS |
| title_fullStr | BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS |
| title_full_unstemmed | BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS |
| title_short | BINARY LOGISTIC MODEL FOR THE LEVEL OF RICE PRODUCTION AND ITS SIGNIFICANT PREDICTORS |
| title_sort | binary logistic model for the level of rice production and its significant predictors |
| url | https://managementjournal.usamv.ro/pdf/vol.24_1/Art15.pdf |
| work_keys_str_mv | AT leomarichfcasinillo binarylogisticmodelforthelevelofriceproductionanditssignificantpredictors AT virgeliocdargantesjr binarylogisticmodelforthelevelofriceproductionanditssignificantpredictors |