Multi-modal Bio-metrics Evaluation for Non-destructive Age States Determination of Tomato Plants (Solanum lycopersicum)

Abstract

Every plant has unique morphological features, and can be used for its characteristics identity, such as age. When the plants grow, their morphological features may change, observable visually or by optical equipment. These various morphology transformations were categorized as multi-modal Bio-metrics. In this study, tomatoes from local cultivar were grown in a net house, in west Sumatra. The growth medium comprised of soil, husk, and manures with the composition of 1: 1: 1 respectively. For best growth, plants were watered regularly, and protect from pests and weeds. The observations were performed on 21st, 42nd, and 63rd day after sowing (DAS). The samples were the leaflets of the primary compound leaves of the plants. The leaflets were cut and digitized using a high-resolution colour scanner. The imaging performed at 300 dpi resolution, and the recorded image subsequently processed by the image processing software. Image segmentation performed to remove background from the object. Furthermore, the greenish of leaf object in the image were measured in RGB colour space. The leaf dimensions and area were quantified by the software, as well as the length of the leaflet main vein at central axis. Two secondary leaflet's blades were selected manually, and the angle formed between the blades and the main vein was measured. A Statistical engineering program was used to identify the principal morphology characteristics of the leaf, by means of Principal component analysis (PCA). Mathematical models were developed based on the principal component values and leaflets position to determine the plants age and state. Results showed all model have coefficient of correlation higher than 0.99 indicating acceptable accuracy.

Development of Aerial Online Intelligent Plant Monitoring System for Oil Palm (Elaeis guineensis Jacq.) Performance to External Stimuli

“…Extractions and analyses methods [32]- [40] were used to compare every plant vegetation indices, from its crown images. A rotational-pivot chart created based on the features data to explain the image texture for further analyses [33], [36]- [38]. The changes in crowns' image textures are used to understand how each individual plant copes with stimulation caused by the bio-pores introductions.…”

Non-destructive Evaluation of Monosaccharides from Two Local Rice Varieties Using NIR Spectroscopy for Disease Prevention Through Dietary Mitigation

“…On the other hand, rapid evaluation methods by means of spectroscopy had been successfully developed for evaluation of chemical properties of fruits and vegetables [25]- [35], as well as grains [36]. Recent developments in machine vision technologies have enabled opportunities for rapid and robust analysis to provide useful and advanced capabilities in a number of important sectors.…”