An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Test Using Image Processing, Curve Fitting and Clustering Method

Abstract

Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The saturated salt accelerated aging (SSAA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from such a method are often imprecise. This paper presents the SV-RICE package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SV-RICE consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor has been classified based on radicle emergence indices, such as maximum radicle emergence (MRET), mean radicle emergence time (MaxRE), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strong negative correlation with the SSAA test. The germination time of 90 hours, at 25°C, was sufficient for effective classification based on SV-RICE, whereas the SSAA test takes approximately 400 hours to complete. The SV-RICE software algorithm was set up to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37%RH in hermetic bag). The study showed that SV-RICE could unambiguously classify 40 Indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared to the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SV-RICE package for automatic seed vigor classification of Oryza sativa seeds; however, it is likely applicable to other species as a viable alternative to current methods that require more time and are less precise.