<b>Automated image analysis of seedlings for vigor evaluation of common bean seeds

Abstract

ABSTRACT. Quickly and precise evaluations of the vigor of seeds are highly desirable for the success of quality control programs applied to the seed industry. The objective of this experiment was to determine the number of days necessary to calculate the vigor index of common bean seeds using an automated system of seedling images (SVIS ® ), and compare its results with the traditional tests of seed vigor. Samples of five seed lots of the IAC Carioca cultivar were submitted to germination, accelerated aging, seedling emergence in sand and electrical conductivity tests. The parameters measured by the Seed Vigor Imaging System (SVIS ® ) were mean seedling length, growth (ratio of the actual seedling growth to the maximum possible growth), uniformity of growth and the vigor indexes 30:70, 40:60, 50:50, 60:40 and 70:30 (based on different growth/uniformity ratios), and computed from scanned images of three-and four-day-old seedlings. Results of SVIS ® analyses were consistent with the physiological potential evaluations provided by the traditional tests of seed vigor. Therefore, the SVIS ® is efficient for detecting differences in vigor among seed lots of common bean (IAC Carioca cultivar) using threeor four-day-old seedlings, independently of the growth/uniformity ratios used to calculate the vigor index.

Use of the software Seed Vigor Imaging System (SVIS®) for assessing vigor of carrot seeds

“…However, the vigor index and seedling growth index enabled the separation of lots at 3 levels of vigor, as did the traditional vigor tests, identifying lots 1 and 2 as having the highest performance, lots 6 and 7 with the lowest, and the remaining lots as having intermediate vigor between these levels. Using SVIS ® , similar results were obtained with seeds of other species, which presented an association between lots showing different vigor levels and the traditional vigor tests such as lettuce (Sako et al, 2001), corn (Otoni and McDonald, 2005), melon (Marcos Filho et al, 2006) and bean (Gomes Júnior et al, 2014).…”

Seedling image analysis and traditional tests to evaluate onion seed vigor

“…After processing, the images provided data on seedling length (SL) in centimeters; growth index (GI), which is the proportion of the current size of the seedling in relation to the maximum possible size on the day evaluated; uniformity (UI), represented by the deviation in relation to the maximum; and vigor (VI), based on the proportion 70:30 of growth/uniformity (Hoffmaster et al, 2003). The values of the growth, uniformity, and vigor indexes can range from 0 to 1000.…”

“…After that, Sako et al (2001) developed an automated system for evaluating the vigor of lettuce seeds through computerized seedling analysis, the Seed Vigor Imaging System (SVIS ® ), which supplies information such as seedling length and indexes of vigor, growth, and uniformity of growth. This software has already been successfully tested on other species, such as melon (Marcos-Filho et al, 2006), soybean (MarcosFilho et al, 2009), maize (Mondo et al, 2011), sweet corn (Alvarenga et al, 2012), cucumber (Chiquito et al, 2012), rattlepod (Silva et al, 2012), okra (Kikuti and Marcos-Filho, 2013), lettuce (Kikuti and Marcos-Filho, 2012), dry edible bean (Gomes Junior et al, 2014), eggplant (Silva and Cícero, 2014a), and tomato (Silva and Cícero, 2014b).…”

Rice Seed Germination Analysis

“…Many researchers [1,3,4,7,8,9,10,11,12,13,14,17,19,20,21,24,26,27,29,30,32,34,35,36,37,38,41,42,43,44,45,48,49,50,51] have applied image processing for rice germination in their studies. This is because using image processing is rapid, economic, consistent, and objective.…”