Predicting germination of Medicago sativa and Onobrychis viciifolia seeds by using image analysis

Abstract

Image analysis is an accessible method that can convert qualitative variables to quantitative ones. Computer imaging has been used in seed biology in various ways, including seed vigor testing and seed identification. In this paper, the seeds of 2 species, Medicago sativa and Onobrychis viciifolia, were studied. Laboratory tests and a computerized experiment were conducted to evaluate the effects of accelerated aging on the seed vigor of both species. We measured the rate of germination using a factorial and completely randomized design, with 10 treatment combinations replicated 3 times. The main factors were accelerated aging (6, 12, 18, 24, and 30 h) and species (Medicago sativa and Onobrychis viciifolia). A CCD color camera and microscope were used to record images of seeds in top views. The images were processed by a computer to generate numerical red-green-blue (RGB) density values. The density value of image analysis was significantly correlated with germination and the results could be used as a measure of seed vigor. Different statistics (root mean square error, coefficient of residual mass, model efficiency, and coefficient of correlation) indicated that selective models did a fair job of predicting germination for M. sativa and O. viciifolia seeds under varying color density. We conclude that the RGB values of density-imaged seeds are nondestructive, practical, and accurate determinants of M. sativa and O. viciifolia seed quality and can distinguish between high- and poor-quality seed lots.