Classification of Macronutrient Deficiencies in Maize Plant Using Machine Learning

Abstract

<p>Detection of nutritional deficiencies in plants is vital for improving crop productivity. Timely identification of nutrient deficiency through visual symptoms in the plants can help farmers take quick corrective action by appropriate nutrient management strategies. The application of computer vision and machine learning techniques offers new prospects in non-destructive field-based analysis for nutrient deficiency. Color and shape are important parameters in feature extraction. In this work, two different techniques are used for image segmentation and feature extraction to generate two different feature sets from the same image sets. These are then used for classification using different machine learning techniques. The experimental results are analyzed and compared in terms of classification accuracy to find the best algorithm for the two feature sets.</p>

Design of an Intelligent Hydroponics System to Identify Macronutrient Deficiencies in Chili

“…Color feature extraction using HSV values, texture feature extraction using Gray Level Co-occurrence Matrix (GLCM), and shape feature extraction using Canny edge detection with Freeman Chain code. The output of color feature extraction is Mean value in (3), Standard deviation in (4), and skewness in (5) for each H, S, and V [48]. Where μ2 4T is Mean, σ2 4T is Standard Deviation, M is image dimension based ith pixel, N is the total number of j-th, and I ij is value of the jth pixel of the image at the i-th color channel.…”

“…Meanwhile, in the decision layer, two different activation functions are used. A numerical prediction has single node and SoftMax activation function [5]. SoftMax not only maps the outputs to the range [0,1] but also maps each output with the total sum is 1.…”

“…The study of macronutrient identification and estimation has been done from destructive to non-destructive methods [5], [16]. The destructive method is tested in the laboratory but it is costly and time-consuming [27].…”

“…Hydroponics is a farming system that emphasizes the fulfillment of plant nutrients [4]. A plant needs macro and micronutrients to grow and develop [5]. Macronutrients include N, P, K, Ca, Mg, S (> 1000 mg/kg dry matter) and micronutrients include Iron, Mn, Zn, Cu, Cl, B, and Mo (<100 mg/kg dry matter) [6].…”

Labeling of an intra-class variation object in deep learning classification

“…ML has been widely applied in various fields to solve complex problems involving large volumes of events or data and requiring fast optimal decisions. One of the main things about ML is the object classification process [5]- [7]. Deep learning (DL) is a subfield of ML.…”