Daniel de Amaral da Silva, Emannuel Diego Gonçalves de Freitas, Haynna Fernandes Abud, Danielo G. Gomes
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引用次数: 0
摘要
种子质量对农作物的生长有很大影响。检查种子质量的传统方法,如看种子发芽的数量或使用一种名为四氮唑测试的化学测试,需要人们仔细观察种子,这需要花费大量的时间和精力。如今,计算机视觉(一种帮助计算机观察和理解图像的技术)在农业中的应用越来越广泛。在这里,我们利用计算机视觉和 X 射线成像技术来帮助专家快速准确地评估种子质量。我们使用 X 射线图像查看了三组不同的种子,并使用 YOLOv8 对其进行了分析。YOLOv8 软件可以测量种子的各个方面,如种子的大小和内部被称为胚乳的部分所占的面积。根据这些信息,我们按照种子胚乳的多少将其分为四组。我们的结果表明,即使数据量很小,YOLOv8 程序也能很好地识别和分离胚乳。我们的方法能够在大约 95.6% 的情况下准确识别胚乳。这意味着我们的方法可以帮助确定种子种植农作物的效果。
Applying YOLOv8 and X-ray Morphology Analysis to Assess the Vigor of Brachiaria brizantha cv. Xaraés Seeds
Seed quality significantly affects how well crops grow. Traditional methods for checking seed quality, like seeing how many seeds sprout or using a chemical test called tetrazolium testing, require people to look at the seeds closely, which takes a lot of time and effort. Nowadays, computer vision, a technology that helps computers see and understand images, is being used more in farming. Here, we use computer vision with X-ray imaging to assist experts in rapidly and accurately assessing seed quality. We looked at three different sets of seeds using X-ray images and used YOLOv8 to analyze them. YOLOv8 software measures different aspects about seeds, like their size and the area taken up by the part inside, called the endosperm. Based on this information, we put the seeds into four groups depending on how much endosperm they have. Our results show that the YOLOv8 program works well in identifying and separating the endosperm, even with a small amount of data. Our method was able to accurately identify the endosperm about 95.6% of the time. This means that our approach can help determine how effective the seeds are to plant crops.