Non-destructive, accurate, user-friendly and low-cost approaches to determining crop\nleaf area (LA) are a key tool in many agronomic and physiological studies, as well as in current\nagricultural management. Although there are models that estimate cut rose LA in the literature, they\nare generally designed for a specific stage of the crop cycle, usually harvest. This study aimed to\nestimate the LA of cut ââ?¬Å?Red Naomiââ?¬Â rose stems in several phenological phases using morphological\ndescriptors and allometric measurements derived from image processing. A statistical model was\ndeveloped based on the ââ?¬Å?multiple stepwise regressionââ?¬Â technique and considered the stem height,\nthe number of stem leaves, and the stage of the flower bud. The model, based on 26 stems (232 leaves)\ncollected at different developmental stages, explained 95% of the LA variance (R2 = 0.95, n = 26,\np < 0.0001). The mean relative difference between the observed and the estimated LA was 8.2%.\nThe methodology had a high accuracy and precision in the estimation of LA during crop development.\nIt can save time, effort, and resources in determining cut rose stem LA, enhancing its application in\nresearch and production contexts.
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