Crop–weather model for turmeric yield forecasting for Coimbatore district, Tamil Nadu, India

• Published in: Agricultural and forest meteorology Vol. 112; no. 3; pp. 133 - 137
• Main Authors: Kandiannan, K, Chandaragiri, K.K, Sankaran, N, Balasubramanian, T.N, Kailasam, C
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 31.10.2002; Oxford Elsevier; New York, NY
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agronomy. Soil science and plant productions; Biological and medical sciences; Climatic models of plant production; Crop–weather model; Curcuma domestica; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities. Techniques. Climatology. Meteorology. Climatic models of plant production; Turmeric; Yield prediction; Asia; Tamil Nadu; India; Turmeric; Crop–weather model; Curcuma domestica; Yield prediction; Irrigation; Monocotyledones; Tropical zone; Time series; Model study; Water balance; Forecast model; Tropical climate; Angiospermae; Flavoring crop; Environmental effect; Spermatophyta; Agrometeorology; Yield; Atmospheric precipitation; Zingiberaceae
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/S0168-1923(02)00125-9

Turmeric is native to India and its successful husbandry depends on the monsoon climate and the availability of irrigation. Yield forecasting in advance is required for export planning and policy decisions. A method to forecast turmeric yield from a time series of meteorological and yield data was developed and tested, using 20-year dataset of dry turmeric yield and monthly climatic variables for the crop’s 9-month growing season. The variables, which had a significant correlation with yield were second month total rainfall ( r=0.60), third month mean evaporation ( r=−0.49), fourth month mean wind speed ( r=0.61), fifth, eighth and ninth month mean minimum temperature ( r=0.45, 0.51 and 0.65, respectively) and ninth month mean minimum relative humidity ( r=0.66). Ten years (1979–1980 to 1988–1989) dataset were used for model building and remaining 10 years (1989–1990 to 1998–1999) data were used for testing the model. A multiple regression model was developed giving a forecast of the dry turmeric yield with a coefficient of determination of r 2=89%.