Nitrogen Deficiency Level Assessment Device for Rice (Oryza sativa L.) and Maize (Zea mays L.) using Classification Algorithm-based Spectrophotometry

Abstract

In this paper, a nitrogen deficiency level assessment device (NDLAD) for rice and maize is presented. The proposed device was based on the functionality of the 4-window panel Leaf Color Chart (LCC) for assessing the nitrogen content of rice and maize plants. The principle of spectrophotometry was implemented using a TCS3200 color sensor module along with a hardware-deployed nearest neighbor algorithm in an Arduino Nano microcontroller for leaf color classification. The objective of the NDLAD is to eliminate the subjective nature of using an LCC in assessing the nitrogen levels in rice and maize. Based on the tests performed, it was revealed that the proposed device can provide a faster and higher detection accuracy rate compared with using an LCC. The performance results make NDLAD a cheaper and promising alternative to other existing electronic crop nutrient assessment tools that are currently available in the market.