Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus. This study aims to quantify the rice yield at various phenological stages from hyper-temporal satellite-derived-vegetation indices computed from time series Sentinel-II images. Different vegetation indices (viz. NDVI, EVI, SAVI, and REP) were used to predict paddy yield. The predicted yield was validated through RMSE and ME statistical techniques. The integration of PLSR and sequential time-stamped vegetation indices accurately predicted rice yield (i.e., maximum R2 = 0.84 and minimum RMSE = 0.12 ton ha−1 equal to 3% of the mean rice yield). Moreover, our results also established that optimal time spans for predicting rice yield are late vegetative and reproductive (flowering) stages. The output would be useful for the farmer and decision makers in addressing food security.
CABI’s Plantwise programme runs local plant clinics in 24 countries across Africa, Asia and Latin America where trained ‘plant doctors’ provide on-the-spot diagnosis and advice for farmers who bring samples to the clinics. A database that records each consultation and...
The paper discusses issues related to Design, User experience Usability involved in designing the interface to be used in rural areas. This study analyses the problems based on tests done on the interface in the villages of Punjab, Pakistan. Rural...
Background: Up to now, efforts to help local communities out of the food-insecurity trap were guided by researcher (or other actors)-led decisions on technologies to be implemented by the communities. This approach has proved inefficient because of low adoption of...
Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many...
The purpose of this paper is to compare and analyze agricultural transition periods in order to provide a new framework for agricultural development in Iran. Considering the foreseeable future, an innovative or knowledge-based economy will substitute the obsolete economy. In...