Coffee yield forecasting using climate indices based agrometeorological model in Kerala
نویسنده
چکیده
Climate plays important role in production of coffee. Adequate quantum and timely receipt of blossom rainfall for flowering and subsequent backing showers influence the berry set and yield of coffee. Harvesting of Arabica coffee in Kerala State with humid tropical climate in India is done by December-January and harvesting of Robusta coffee is taken up during January-February. In this paper, attempt was made to develop agrometeorological models to forecast the yield of these two varieties coffee by utilising monthly climate variables from January to December. Long term data from 1991-92 to 2012-13 on coffee yield and weather data from 1991-2012 recorded at Regional Coffee Research Station, Chundale located in Wayanad district of Kerala State was used to develop agrometeorological model. Statistical regression model between climate indices and yield of Arabica and Robusta coffee was developed and the model was validated using crop and climate data for 2013 and 2014. The model demonstrated that climate indices based agrometeological model is able to forecast the yield of coffee in Kerala.
منابع مشابه
Wheat yield prediction through agrometeorological indices for Hamedan, Iran
Yield prediction before harvesting is one of the tools in order to planning food production supply in future.Yield prediction was carried out for Wheat(Triticum aestivum) using different meteorological variables with agrometeorological indices in Hamedan district during 2003-04 and 2004-05. According to correlation coefficients, standard error of estimate as well as relative deviation of predic...
متن کاملDo Agrometeorological Data Improve Optical Satellite-Based Estimations of the Herbaceous Yield in Sahelian Semi-Arid Ecosystems?
Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been widely used to assess Sahelian plant productivity for ...
متن کاملProbabilistic Yield Forecast Based on Aproduction Process Model
A method for probabilistic forecast of agricultural yield depending on meteorological variability, i.e. forecast of agrometeorological resources, is discussed. Forecast is based on the category of meteorologically possible yield (MPY)–the maximum possible yield for a given variety in the existing meteorological conditions. The forecasting process is realized by a potato production process model...
متن کاملAssessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale
Crop yield forecasting plays a vital role in coping with the challenges of the impacts of climate change on agriculture. Improvements in the timeliness and accuracy of yield forecasting by incorporating near real-time remote sensing data and the use of sophisticated statistical methods can improve our capacity to respond effectively to these challenges. The objectives of this study were (i) to ...
متن کاملAgrometeorology and sustainable agriculture
Current concerns with the sustainability of agroecosystems in different parts of the world have hightened the awareness for careful use of the natural resource base on which agriculture depends. For proper and efficient use of soils and plant/animal genetic material, knowledge of the role of climate is an essential precondition. Several elements of the chapters in Agenda 21, a global plan of ac...
متن کامل