Deep learning-driven automatic counting of petal number in cut chrysanthemum inflorescence.

Both cultivars exhibited highly significant differences between the control and high-temperature groups (p < 0.001), with positive t-statistics in both cases, further confirming that high-temperature stress exerts a statistically significant inhibitory effect on petal number. 4 Discussion This study presents an improved approach combining deep learning and machine learning for predicting petal numbers in cut chrysanthemum inflorescences and validates its effectiveness through comprehensive experiments.

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