A strengthened DA with the capacity and infrastructure to use information technology for a more food secure future.
PRISM’s mission is to support the DA in regional and national decision-making for rice security by:
- using state-of-the-art technologies to generate rice crop information; and
- enhancing the capacity of the DA to collect, analyze, disseminate, and use this information.
Goals and objectives
PRISM aims to:
- map rice areas by season in the Philippines using remote sensing imagery;
- develop and validate methods for estimating rice yields using combined remote sensing and crop modeling approaches;
- characterize production situations and quantify pest risks in farmers’ fields;
- develop a web-based monitoring system that provides accurate estimates of rice area, rice yield, and production loss due to flood or drought;
- improve the capacity for rice crop monitoring and pest surveillance at PhilRice and the DA by conducting training courses;
- and provide farmers and extension workers with a simple and strategic decision tool for pest management in irrigated lowland rice.
How PRISM works
The PRISM project aims to revolutionize the way data and information on how rice crop is collected and used.
PRISM gathers information on rice, such as where it is grown; when it is grown; and what affects the rice crop as it grows through integrating remote sensing and information and communications technology (ICT). Currently, PRISM delivers detailed maps of rice area, seasonality, and yield; and reports on pest injury and disease observations. Graphs and tabular representations of the occurrence of pest injuries and diseases, yield, and farmer inputs that include fertilizers, pesticides and rice variety used, are also offered.
All available information are made accessible to stakeholders and decision-makers anytime and anywhere using any Internet-connected device.
Mapping and monitoring
PRISM derives data on rice area, including planting date estimates, using high-resolution SAR images that can provide a continual source of information, regardless of weather conditions. To validate the rice area products, ground truth surveys are conducted by trained staff from the Department of Agriculture-Regional Field Offices (DA-RFOs), the Philippine Rice Research Institute (PhilRice), and other partner agencies.
SAR images acquired on specific dates throughout the season are also used to estimate rice yields. Processed SAR images together with weather data, variety, soil data, and crop management data are inputted into ORYZA, a crop growth modeling software, to estimate or forecast yields. The yield estimates are validated against crop cut experiments in all rice-producing regions and compared against official statistics from the Philippine Statistical Authority (PSA).
Crop health assessment
Surveys of farmers’ fields are conducted to characterize the production situation in the area (e.g. variety, crop establishment method, nutrient inputs, and pest control methods), to assess injuries caused by diseases, animal pests, and weeds, and to quantify yield. Survey results are then used to produce information that will serve as the basis for stakeholders in prioritizing activities for pest management. Through improved data management and decision support systems, PRISM makes information and recommendations accessible to farmers so they can adopt rational and relevant pest management strategies.
In the recent years, the Philippines has experienced severe flooding that caused damages to rice fields. In the event of these recurring natural calamities, such as flood or drought, PRISM provides accurate information on the extent of damaged rice areas and production loss. Hence, required interventions are immediately identified and rice production shortfalls are easily assessed. PRISM makes it possible to deliver rapid assessment over a wide area using remote sensing.
The PRISM project holds series of training courses to improve the capacity of partner agencies in the Philippines on rice crop monitoring and pest surveillance. For rice crop monitoring, relevant personnel from PhilRice and DA-RFO's are trained on the use of remote sensing and crop modeling. Likewise, their national and regional partners' capacity in management, statistical analysis, and interpretation of data are also enhanced. For pest surveillance, the training includes identification and assessment of injuries caused by diseases, animal pests, and weeds in farmers’ fields; and characterization of production situation using a standardized procedure from IRRI, known as Survey Portfolio to Characterize Yield-Reducing Factors in Rice.
In turn, trained staff are expected to train local partners using the same standard curriculum to ensure maintenance and management of the rice information system.