Abstract
In this study, conventional machine learning and deep leaning approaches were evaluated using X-ray imaging techniques for investigating the internal parameters (endosperm and air space) of three cultivars of watermelon seed. In the conventional machine learning, six types of image features were extracted after applying different types of image preprocessing, such as image intensity and contrast enhancement, and noise reduction. The sequential forward selection (SFS) method and Fisher objective function were used as the search strategy and feature optimization. Three classifiers were tested (linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k-nearest neighbors algorithm (KNN)) to find the best performer. On the other hand, in the transfer learning (deep learning) approaches, simple ConvNet, AlexNet, VGG-19, ResNet-50, and ResNet-101 were used to train the dataset and class prediction of the seed. For the supervised model development (both conventional machine learning and deep learning), the germination test results of the samples were used where the seeds were divided into two classes: (1) normal viable seeds and (2) nonviable and abnormal viable seeds. In the conventional classification, 83.6% accuracy was obtained by LDA using 48 features. ResNet-50 performed better than other transfer learning architectures, with an 87.3% accuracy which was the highest accuracy in all classification models. The findings of this study manifested that transfer learning is a constructive strategy for classifying seeds by analyzing their morphology, where X-ray imaging can be adopted as a potential imaging technique.
Highlights
Watermelon (Citrullus lanatus (Thunb.)) is a popular delicious and refreshing fruit that is consumed all over the world and is a great source of vitamins and minerals
For producing healthy high-quality seedlings, seed quality inspection is a concern for both watermelon growers and and high-quality seedlings, seed quality inspection is a concern for both watermelon growers and seed companies
To inspect the inner components of a seed, X-ray imaging can be imaging can be used as a feasible resource because it is fast, reliable, and nondestructive compared used as a feasible resource because it is fast, reliable, and nondestructive compared to ordinary seed to ordinary seed quality testing methods, such as the tetrazolium test (TZ test), pepper germination quality testing methods, such as the tetrazolium test (TZ test), pepper germination test, and embryo test, and embryo excision test [2,3]
Summary
Watermelon (Citrullus lanatus (Thunb.)) is a popular delicious and refreshing fruit that is consumed all over the world and is a great source of vitamins and minerals. For producing healthy and with the sowing of seeds in the soil and the production of seedlings. A watermelon seed is classified as a dicotyledon seed containing three basic components: (1) a. A watermelon seed is classified as a dicotyledon seed containing three basic components: (1) a seed seed coat, (2) an embryo, and (3) endosperm (Figure 1). The seed coat protects the inner parts of the seed from the outside successful germination. The seed coat protects the inner parts of the seed from the outside environment, environment, the embryo is a tiny plant that grows upwards, and endosperm stores food to provide the embryo is a tiny plant that grows upwards, and endosperm stores food to provide the necessary the necessary nutrients during germination [1]. To inspect the inner components of a seed, X-ray imaging can be imaging can be used as a feasible resource because it is fast, reliable, and nondestructive compared used as a feasible resource because it is fast, reliable, and nondestructive compared to ordinary seed to ordinary seed quality testing methods, such as the tetrazolium test (TZ test), pepper germination quality testing methods, such as the tetrazolium test (TZ test), pepper germination test, and embryo test, and embryo excision test [2,3]
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