The Taiwan Agricultural Research Institute said it can now make in-season predictions of harvest yields for rice crops based on satellite imaging technology, and is working on ways to apply the science to other types of crops such as cabbage and lettuce.
The traditional methods of estimating rice yields are conducted by measuring randomly selected patches of rice, the institute said on Thursday last week.
The methods calculate yields by township to estimate a nationwide yield, requiring significant amounts of time and resources, it said, adding that such methods only provide yield estimates for the previous year.
Photo courtesy of the Taiwan Agricultural Research Institute
Climate change and its effects — evidenced by recent water shortages that forced Taiwan to temporarily cease irrigating fields — has demonstrated that the country can no longer rely on previous methods to estimate crop yields, the institute said.
The new analytical methods allow the institute to calculate yields from more than 120,000 hectares of rice paddies across western Taiwan in less than two months, it said, adding that the method is capable of calculating individual yields per paddy.
Institute member Liu Tsang-shen (劉滄棽) said free satellite images released by the EU each week are utilized to make such calculations, adding that the institute is also consulting crop yield data from previous years.
The average growth cycle of a rice crop is about five months from seeding to harvest, and the institute is usually able to estimate the expected yield in the third month, Liu said.
Other algorithms are introduced to factor in the possible loss of crops from pest damage, he added.
The institute is looking to use this method of yield calculation on other crop types, such as lettuce, cabbage, sorghum and corn, he said.
Such analysis from satellite images could be applied to other industries, the institute said.
The system could also be used to develop precision agriculture, such as helping farmers manage different crops, the amount of water the crops need and what kind of fertilizer should be used, along with other suggestions, it said.
The system could also provide important data that could be used by the government to ensure the production of sufficient food crops, allocation of water and management of agricultural ecological systems, it added.
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