Nitrogen Adequacy Measurement in Rice (Oryza sativa L.) by Automated Methods based on Leaf Color Chart (LCC): A Review

Abstract

Rice (Oryza sativa L.) is the staple food for over 50% of the world’s population. For elevated growth yield and quality of product, sufficient delivery of nitrogen (N) is required to the crop. An effortless gadget that can be used to determine the color of the leaves of rice plants for quantifying N fertilizer is the Leaf Color Chart (LCC). However, the difficulty in this LCC is that the tool is still manual and color estimation is done through eye sight. To overcome these difficulties, it is essential to have an automatic classification system of rice leaf color that can facilitate farmers in finding the category of rice plants depending on LCC. Studies have revealed that the color classification system of rice leaves have an accuracy rate of 75%. Customized leaf colour chart (CLCC) based N application enhanced yield by 10.3 to 13.3 % and 9.9 to 10.9 % over conventionally applied urea in direct seeded rice and transplanted rice, respectively. Color classification by these two proposed methods achieved 94.22% accuracy in CNN Model and 91.22% accuracy in the DT classifier. LCC-N management during Thaladi season for ASD 18 revealed that LCC measurement at critical growth stages resulted in the conservation of 70 kg N ha^-1 compared to the blanket N of 150 kg N/ha in three splits. By LCC method average saving in N was 25 kg ha^-1 without any reduction in yield. These, review results clearly reveal the importance of LCC for precision nitrogen management in rice crop.