Remote sensing to track potato productivity in Himachal

By: Ravinder Makhaik

Shimla: As food prices spiral and the government faces flak for being unable to keep essential commodities affordable, the task of forecasting productivity of crops like potato assumes importance for which ground observation coupled with satellite imagery is now being applied.

Explaining the process, SK Pandey, director Central Potato Research Institute (CPRI) says. “Our survey teams are presently making ground truth observations which are then co-related with imagery data collected by ISRO satellites that are processed at Space Application Centre, Ahmadabad and by end of January we would be able to make a forecast of expected potato production of the winter crop in the entire Indo-Gangetic belt.”

Problems of plenty and scarcity plague many perishable crops, says senior scientist PM Govindakrishnan and the objective of forecasting the potato crop, a month before harvest is to provide advance information for all stakeholders to adopt timely interventions in either case.”

Remote sensing for crop assessment has been explored since very beginning of space applications in the country, but since 2006 Forecasting Agricultural output using Space, Agrometeorological and Land based observations (FASAL) concept was devised.

Under FASAL, we are using remote sensing for assessing acreage under winter potato in Punjab, Haryana, UP, Bihar and West Bengal, say the CPRI scientists. As this crop constitutes over 75 % of the total production, which often leads to a glut and distress sales, timely information does help in taking decisions about cold storing a portion of the crop, they add.

Field survey for Punjab has been completed and for other states would be completed soon, says Pandey. The acreage data would be then used in crop growth simulation models to make the expected crop forecast.

The premier institute has not been of the mark for since it started using remote sensing. “The research and development in forecasting potato crops has been fairly accurate, which is well within a margin error 10 percent, says Govindakrishnan.

FASAL concept of using the multi source data and techniques has been successfully demonstrated and taken up to make national level multiple forecast of crops like rice, wheat, cotton, sugarcane, rapeseed/mustard, rabi-sorghum, winter-potato and jute.