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China Pilots 2 and 3

ISSCAS

The CHina Pilots 2 and 3 are managed by ISSCAS. China pilot 1 is affiliated to the Bei'an Administration of Heilongjiang Land Reclamation Bureau and located in Wudalianchi City and Bei'an City, Heilongjiang province, China. China pilot 2 is located in Liuhe district, Nanjing city, Jiangshu Province, China.

PILOT CHALLENGES (CONTEXT)

 

The CHINA Pilot 2 - low level of awareness, lag in variety, over-application of chemical fertilizers. The CHINA Pilot 3 - Small-scale farming, nutrient imbalances, over-application of chemical fertilizers, soil contamination.  

 

PILOT OBJECTIVES

 

China pilot 2 and 3 objectives are as follows:

To improve the farmland information level


To realize crop growth automatic monitoring


To realize the intelligent process and visualization of field data


 


To use deep learning algorithms to optimize the input dosage and timing of water, fertilizer, medicine, and seed, to achieve optimal growth of crops, increase crop production potential, and reduce the use of chemicals


PILOT INNOVATIONS

 

The pilot innovations mainly consist of advanced strategies and technologies, soil quality improvement, and a soil management intelligent service platform that can be customized for multiple terminals.

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Pilot location China
Use Case

CHINA Pilot 2: the Bei'an Administration of Heilongjiang Land Reclamation Bureau and located in Wudalianchi City and Bei'an City, Heilongjiang province, China

CHINA Pilot 3: Liuhe district, Nanjing city, Jiangshu Province, China

Pilot scale

CHINA Pilot 2: The area is 42 hectares.

CHINA Pilot 3: The area is 3.2 hectares.

Land uses (crop types)

CHINA Pilot 2: Major crops are corn and rice with single cultivation.

CHINA Pilot 3: The typical cropping system is a rotation between rice and winter wheat.

Major agricultural and environmental projects

Promote the trial work of farmland rotation and fallow.

Pilot objectives

Improve the farmland information level, realize crop growth automatic monitoring, and realize the intelligent process and visualization of field data. Using deep learning algorithms to optimize the input dosage and timing of water, fertilizer, medicine, and seed, to achieve optimal growth of crops, increase crop production potential, and reduce the use of chemicals.

Forum - China Pilot 2 and 3 - ISSCAS

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