SMS-based Smarter Agriculture decision support system for yellow corn farmers in Isabela

Abstract

Agriculture is a major industry in the Philippines with 50% of its work force working in agriculture. Isabela is the number one corn producer in the country, contributing 22.57% of the national production, housing 20.26% of the national area producing corn. Farmers in this area use traditions and superstitions in making farming decisions. While this worked in the past, the recent progression of climate change has prompted the need for technology to provide advice to farmers so that they may take into consideration the big factors that must be considered when farming namely the atmosphere, cultivar, soil and farm management. This paper presents a Smarter Agriculture solution through precision agriculture. This solution leverages on DSSAT 4.5 with Automated Weather Station (AWS) sensors, numerical climate model, numerical weather model, corn cultivar parameters, SMS technology as well as the expert knowledge of the farmers. The solution is designed for yellow corn farmers in Isabela where farmers have limited Internet connection and have difficulty in using smart phones hence, the use of SMS. This paper will focus on how the solution is developed so that farmers may be able to identify the best date to start planting, best date to harvest, optimal water as well as the projected dry yield for the crop, taking into consideration the climate outlook during the planting season. This allows the farmer to query about the weather outlook for short-term farming decisions such as decisions on whether to apply fertilizer or irrigation during the day.