Chen Jiunyuan, Chen Chiachung
Africa Industrial Research Center, National Chung Hsing University, 250 Kuokuang Road, Taichung 40227, Taiwan.
Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, 250 Kuokuang Road, Taichung 40227, Taiwan.
Plants (Basel). 2023 May 19;12(10):2031. doi: 10.3390/plants12102031.
orchids are highly economical ornamental potted plants. Controlling their production schedule requires information on the leaf development characteristics of the orchids. leaves affect the plant's photosynthesis, respiration, and transpiration. The leaf growth conditions can serve as a development index for greenhouse management. The use of the growth characteristics of leaves as the basis for greenhouse cultivation and management needs to be studied. The allometry of leaves is worth studying. The goal of this research was to investigate the allometry of leaves and develop prediction models of the total leaf area. Then, these total leaf area models were developed and validated. In this study, five varieties (amabilis, Sin-Yuan beauty, Ruey Lish beauty, Ishin KHM1095, and Sogo F1091) were selected. Each sample had five mature leaves. The lengths, widths, and areas of the sequential leaves were measured, and then the length ratios, width ratios, and area ratios were calculated. The top and bottom models were used to calculate the total leaf areas. The results indicate that no significant differences could be found in the length ratios, width ratios, and area ratios of the sequential leaves from the same variety. However, significant differences were found in these leaf characteristics between different varieties. The observation of leaf growth characteristics can be used to provide useful information for management. Comparing the predictive criteria of the two models, the top model had a better predictive ability than the bottom model. From a practical viewpoint, measuring the top leaf area is easier than measuring the bottom leaf area in a greenhouse operation. Comparing the effects of the sample numbers on the predictive ability of the model, the sample number of 30 was sufficient to ensure the accuracy of the total leaf area measurements. We provide an easy and accurate method to measure the total leaf area of . The calculated values of total leaf areas can be incorporated into decision models for smart management.
兰花是极具经济价值的观赏盆栽植物。控制其生产进度需要了解兰花的叶片发育特征。叶片影响植物的光合作用、呼吸作用和蒸腾作用。叶片生长状况可作为温室管理的发育指标。以叶片生长特征为基础进行温室栽培和管理的应用尚需研究。叶片的异速生长值得研究。本研究的目的是调查叶片的异速生长情况并建立总叶面积预测模型。然后，开发并验证了这些总叶面积模型。本研究选取了五个品种（美丽兜兰、新源美人、瑞丽美人、一心KHM1095和索哥F1091）。每个样本有五片成熟叶片。测量连续叶片的长度、宽度和面积，然后计算长度比、宽度比和面积比。使用顶部模型和底部模型计算总叶面积。结果表明，同一品种连续叶片的长度比、宽度比和面积比无显著差异。然而，不同品种之间的这些叶片特征存在显著差异。观察叶片生长特征可为[植物名称]管理提供有用信息。比较两种模型的预测标准，顶部模型的预测能力优于底部模型。从实际角度来看，在温室操作中测量顶部叶面积比测量底部叶面积更容易。比较样本数量对模型预测能力的影响，30个样本数量足以确保总叶面积测量的准确性。我们提供了一种简单准确的方法来测量[植物名称]的总叶面积。计算得到的总叶面积值可纳入智能管理决策模型。
