Abiotic factors: Its relationship on the yield of mango ( L.) with science and Mangifera indica technology interventions

The study investigated the impact of abiotic factors on the yield of harvested mangoes before and after Science and Technology (S&T) interventions in five municipalities, namely: President Quirino, Sultan Kudarat, Tulunan, North Cotabato, Tantangan, South Cotabato, Malungon, Sarangani Province, and General Santos City. The study used the simple linear regression model Y=BX + a to determine the extent to which there was a linear. relationship between a dependent variable and one or more independent variables. In simple linear regression, a single independent variable, ie, rainfall or temperature, was used to predict the value of a dependent variable, the yield of mangoes per hectare during the first and second cycle productions of farmer-cooperators in four provinces, namely: Sultan Kudarat, North Cotabato, South Cotabato and General Santos/Sarangani. The results. indicated that the General Santos/Sarangani Province obtained the highest yield in terms of baseline yield after two years of interventions. The derived regression model for rainfall (mm), temperature (°C), relative humidity (%), and soil pH was unable to predict the yield of mangoes in all provinces studied during the second production cycle of the farmer-cooperators. Conversely, the regression model for temperature (°C) and relative humidity (%) statistically predicted the yield of mangoes (t ha") of farmer-cooperators in Sultan Kudarat during the first cycle of production. Additionally, rainfall (mm), temperature (°C), and relative humidity had linear relationships with the yield of mangoes per hectare. However, soil pH showed fluctuating, curvilinear relationships with the yield of mangoes per hectare. Additionally, rainfall (mm), temperature (°C), relative humidity (%), and soil pH did not show significant relationships with the yield of mangoes per hectare.