Analysis of Factors Influencing Robusta Coffee (Coffea canephora) Productivity in Sultan Kudarat Province, Mindanao, Philippines

Abstract This research examines the factors affecting the productivity of Robusta coffee in Sultan Kudarat province. Utilizing quantitative data from personal interviews with farmers, the study employs multiple linear regression analysis (MLRA) to identify key determinants of productivity. The findings indicate that factors such as capital, age of trees, frequency of extension visits, number of coffee trees, and access to credit significantly impact productivity levels. The study suggests that farmers should adopt innovative farming techniques, such as rejuvenation, to enhance yields. Additionally, it recommends that the provincial government play a more active role in promoting productivity by partnering with private organizations to disseminate advanced coffee production methods. This collaboration could help bridge knowledge gaps, provide better access to resources, and ultimately improve the overall productivity and sustainability of Robusta coffee farming in the region. KEYWORDS: Robusta coffee, Productivity, Sultan Kudarat

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-22
DOI
https://doi.org/10.5281/zenodo.14910831
Primary Topic
Global trade, sustainability, and social impact
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Factors Influencing Robusta Coffee (Coffea canephora) Productivity in Sultan Kudarat Province, Mindanao, Philippines

Zenodo (CERN European Organization for Nuclear Research)
Global trade, sustainability, and social impact
article

Analysis of Factors Influencing Robusta Coffee (Coffea canephora) Productivity in Sultan Kudarat Province, Mindanao, Philippines

article en

Abstract

Abstract This research examines the factors affecting the productivity of Robusta coffee in Sultan Kudarat province. Utilizing quantitative data from personal interviews with farmers, the study employs multiple linear regression analysis (MLRA) to identify key determinants of productivity. The findings indicate that factors such as capital, age of trees, frequency of extension visits, number of coffee trees, and access to credit significantly impact productivity levels. The study suggests that farmers should adopt innovative farming techniques, such as rejuvenation, to enhance yields. Additionally, it recommends that the provincial government play a more active role in promoting productivity by partnering with private organizations to disseminate advanced coffee production methods. This collaboration could help bridge knowledge gaps, provide better access to resources, and ultimately improve the overall productivity and sustainability of Robusta coffee farming in the region. KEYWORDS: Robusta coffee, Productivity, Sultan Kudarat

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 39%
Global trade, sustainability, and social impact
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Analysis of Factors Influencing Robusta Coffee (Coffea canephora) Productivity in Sultan Kudarat Province, Mindanao, Philippines · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS