Skip Navigation Links
CassnumExpand Cassnum
Modified StarchesExpand Modified Starches
Soil Nutrient ManagementExpand Soil Nutrient Management
Tuber Crop StatisticsExpand Tuber Crop Statistics
Fertcalc_CTCRIExpand Fertcalc_CTCRI

Potential yield and yield gap

The tuberous root yield limited only by climate and cultivar is the potential yield of cassava at a particular location. The potential yield can be estimated with the help of cassava growth models such as GUMCAS (Matthews and Hunt, 1994), SIMCAS (Mithra et al.,), the model described by Fukai and Hammer (1987) etc., or by conducting maximum field trials (MYT). In the absence of either of this information, the maximum yield of cassava ever obtained in a location with near optimal growth conditions is considered as the potential yield (Dobermann and Witt, 2004). The productivity of cassava varies widely in the major cassava growing domains of India. The average productivities in the states of Kerala, Tamil Nadu and Andhra Pradesh are 27, 38 and 20 tons per hectare respectively ( The tuberous root yield of cassava limited only by climate and cultivar can be considered as its potential yield. Since no data on potential yield estimated using crop growth models or maximum yield research are available for all the cassava growing environments in India, we used the maximum yield recorded at these locations either in experimental locations or in farmers’ field. Table below gives the potential yield (Ymax) used in our site specific nutrient management (SSNM) experiments conducted for four major cassava domains.

Table. Potential yield (Ymax, t / ha) of tuberous root yield of cassava in major cassava growing domains in India
Location Y max ( t/ha fresh weight ) Remarks
Kerala 75 Based on field experiments
Tamil Nadu 80 Based on field experiments
Andhra Pradesh 70 Based on field experiments
Maharashtra 60 Expert guess and farmers data

From the data on potential yield and present average productivity, it can be seen that there exists a yield gap in the range of 40 to 50 t/ ha. Studies conducted in crops such as rice and wheat clearly show that if we want to increase the yield further, the only way is by exploiting the spatial and temporal variability in soil and plant properties at different locations through site specific nutrient management (SSNM) technology.


Dobermann A. and C. Witt. 2004. The evolution of site specific nutrient management in irrigated rice systems of Asia. In: Dobermann et al. (Eds.). Increasing productivity of intensive rice systems through site specific nutrient management. Enfield, N.H. (USA) and Los Banos, The Philippines. Science Publishers, Inc., and IRRI, The Philippines. pp. 75-99.

Fukai S. and G.L.Hammer. 1987. A simulation model of the growth of the cassava crop and its use in estimating cassava productivity in Northern Australia. Agricultural Systems 23: 237-257.

Matthews R.B. and L.A. Hunt. 1994. GUMCAS: a model describing the growth of cassava (Manihot esculenta L. Crantz). Field Crops Research 36: 69-84.

Mithra V.S.S., K.R. Lakshmi and C.S.Ravindran. A model to simulate cassava growth. Journal of Root Crops. 27(2):

Central Tuber Crops Research Institute
Sreekariyam, Thiruvananthapuram, Kerala - 17