Thermal analysis and artificial vision of laser irradiation on corn
- PDF / 2,898,586 Bytes
- 8 Pages / 595.276 x 790.866 pts Page_size
- 74 Downloads / 196 Views
Thermal analysis and artificial vision of laser irradiation on corn H. Cisneros‑Carrillo1 · C. Hernandez‑Aguilar1 · A. Dominguez‑Pacheco1 · A. Cruz‑Orea2 · R. Zepeda‑Bautista1 Received: 4 October 2019 / Accepted: 21 August 2020 © Springer Nature Switzerland AG 2020
Abstract Currently evaluation of agricultural product quality is of great importance, in order to guarantee a consumption free of contaminants. In different research areas several techniques are used to evaluate food attributes, related to its quality. Among the techniques used to characterize food stuffs, photothermal techniques have shown versatility to obtain different physical parameters of foods. In the present investigation, the temperature variation effects of different varieties of corn kernels, when excited by laser light during 60 s, were obtained from digital and thermal images, which were analyzed by using artificial vision for characteristic color patterns and geometric measurements to observe the thermal effects, respectively. From these images it was possible to observe variations in temperature, through differences in digital and thermal images of corn samples. Also photoacoustic (PA) spectra were obtained in a wavelength range from 300 to 750 nm, for each variety of corn kernels. Different behaviors of both, image analysis and the PA spectra, showing that one variety of corn kernels present a greater response in both techniques compared to the other varieties. The information obtained could be used in food production areas to identify, classify and determine attributes of grains and seeds of different types of crops. Keywords Corn · Thermal techniques · Photoacoustic spectroscopy · Thermal images · Artificial vision
1 Introduction There is evidence that maize (Zea mays L.) originated in Latin America, especially in Mexico, 7000 years ago [1]. This product is grown in almost all parts of the world due to its nutritional qualities for the generation of animal protein, human consumption and industrial use [1, 2]. In 2017, its global production was 1134.7 million tons, ranking first in the world cereal production, leaving in second and third place wheat and rice, with 771.7 and 769.6 million tons, respectively [3]. In this sense, it is necessary to keep a check and carry out an inspection to guarantee the quality of maize seeds that allows their pollutant-free consumption [4–6]. Normally, these activities are realized by specialists and it takes a long time [5]. So, an automation
is necessary in this field to reduce human risks, pollution, pesticides and agrochemicals [7, 8]. Quality assessment techniques for agricultural products play an important role in this sector, where they have been shown to provide useful information for analysis. Among the several techniques to characterize different materials, ranging from homogeneous to non-homogeneous ones, the photothermal techniques (PT) stand out because are nondestructive. One of the PT techniques is the photoacoustic spectroscopy (PAS), used to study the optical and reflectance
Data Loading...
