Enhancement of the prediction of the openness of fresh-cut roses with an improved YOLOv8s model validated by an automatic Grading Machine.

IF 4.1 2区生物学 Q1 PLANT SCIENCES Frontiers in Plant Science Pub Date : 2025-03-25 eCollection Date: 2025-01-01 DOI:10.3389/fpls.2025.1546503

Qinghui Lai, Zhanwei Yang, Wei Su, Chuang Yan, Qinghui Zhao, Yu Tan, Yu Que, Jing Zheng

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Abstract

Introduction: The openness grading of fresh-cut roses relies heavily on manual work, which can be inefficient and inconsistent.

Methods: In this study, an improved YOLOv8s model is proposed for openness grading in conjunction with a newly developed automatic grading machine for fresh-cut roses. The model identifies unopened inner petals and classifies openness into five levels: degree 1, degree 2, degree 3, degree 4, and deformity. To enhance detection accuracy while reducing the model complexity and computation, the backbone network of YOLOv8s is replaced by MobileNetV3. Additionally, an Efficient Multi-scale Attention (EMA) module is introduced to enhance focus on critical features, and a Wise-IoU loss function is incorporated to accelerate convergence.

Results: Field experiments revealed that the openness predictions made by the automatic fresh-cut roses grader had errors of 6.9%, 9.1%, 10.0%, 6.5%, and 12.6%, respectively, compared to manual predictions.

Discussion: Therefore, the improved YOLOv8s-F model effectively meets the requirements of fresh-cut rose openness grading.

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改进的YOLOv8s模型对鲜切玫瑰开度预测的增强作用，并经自动分级机验证。

介绍：鲜切花的开放度分级很大程度上依赖于手工作业，这可能是低效和不一致的。方法：本研究提出了一种改进的YOLOv8s模型，并结合新开发的鲜切玫瑰自动分级机进行开放性分级。该模型识别未打开的内花瓣，并将开放程度分为5个级别：1度、2度、3度、4度和畸形。为了提高检测精度，同时降低模型复杂度和计算量，将YOLOv8s的骨干网替换为MobileNetV3。此外，还引入了高效多尺度注意（EMA）模块，以增强对关键特性的关注，并集成了Wise-IoU损失函数以加速收敛。结果：现场实验表明，与人工预测相比，自动鲜切花分级机的开放性预测误差分别为6.9%、9.1%、10.0%、6.5%和12.6%。讨论：因此，改进的YOLOv8s-F模型有效地满足了鲜切月季开放性分级的要求。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Plant Science PLANT SCIENCES-

CiteScore

7.30

自引率

14.30%

发文量

4844

审稿时长

14 weeks

期刊介绍： In an ever changing world, plant science is of the utmost importance for securing the future well-being of humankind. Plants provide oxygen, food, feed, fibers, and building materials. In addition, they are a diverse source of industrial and pharmaceutical chemicals. Plants are centrally important to the health of ecosystems, and their understanding is critical for learning how to manage and maintain a sustainable biosphere. Plant science is extremely interdisciplinary, reaching from agricultural science to paleobotany, and molecular physiology to ecology. It uses the latest developments in computer science, optics, molecular biology and genomics to address challenges in model systems, agricultural crops, and ecosystems. Plant science research inquires into the form, function, development, diversity, reproduction, evolution and uses of both higher and lower plants and their interactions with other organisms throughout the biosphere. Frontiers in Plant Science welcomes outstanding contributions in any field of plant science from basic to applied research, from organismal to molecular studies, from single plant analysis to studies of populations and whole ecosystems, and from molecular to biophysical to computational approaches. Frontiers in Plant Science publishes articles on the most outstanding discoveries across a wide research spectrum of Plant Science. The mission of Frontiers in Plant Science is to bring all relevant Plant Science areas together on a single platform.