干旱区生态环境知识资源中心(Arid): 6种西番莲属(Passiflora)植物叶面积经验模型构建

Arid

	6种西番莲属(Passiflora)植物叶面积经验模型构建
其他题名	Construction of empirical models for leaf area estimation in six Passiflora species
	吴凤婵; 李安定; 蔡国俊; 谭仲廷; 杨瑞
来源期刊	果树学报
ISSN	1009-9980
出版年	2021
卷号	38 期号:9 页码:1600-1610
中文摘要	【目的】构建6种西番莲属植物最优叶面积(LA)经验模型,为这6种西番莲属植物生理生态及栽培技术等方面的研究提供理论基础,初步探讨LA模型构建的一般规律。【方法】以6种西番莲属植物叶片为研究材料,采用计算机图像法测量各树种叶片长(L)、叶片宽(W)、叶片面积(LA),并以LA为因变量,L、W及LL、WW、LW为自变量,选取12种目标模型,分别构建各物种LA经验模型,选取其中2个叶形相似、叶长宽比相近的西番莲属植物合并建模,并对这些模型进行评估以筛选出最优LA经验模型。【结果】6种西番莲属植物的最优LA经验模型分别为:紫果西番莲:LA= 0.529 L~(1.141)W~(0.868);樟叶西番莲:LA=0.828 L~(0.933)W~(1.054);尤卡坦西番莲:LA=0.665 L~(0.665)W~(1.367);西番莲:LA=0.559 L~(1.154)W~(0.797);龙珠果:LA=0.763L~(0.64)W~(1.327);玛格丽特女士西番莲:LA=0.6 L0.213,6种西番莲属植物的最优LA经验模型预测精度范围为91.28%~95.54%,紫果西番莲与玛格丽特女士西番莲合并构建的最优LA模型的预测精度为(92.080.56)%。【结论】构建LA经验模型预测这6种西番莲属植物LA预测精度均在90%以上,说明构建LA经验模型预测这6种西番莲科西番莲属植物的LA是可靠的;2种叶形相似、叶长宽比相近的西番莲属植物合并建模,得到的模型预测精度较高,初步表明叶形相似、叶长宽比相近的植物合并建模预测LA具有一定的可行性。
英文摘要	【Objective】Passiflora belongs to the Passifloraceae, most species of which belong to perennial vines. Edible passionflower is cultivated widely, and is mainly produced abroad in North America, South America, Australia, Malaysia and southern Africa and other countries and regions. Passionflower and the dominant companion species can be mutually beneficial and symbiotic, adapt to the environment, growing rapidly, and have high yield. Cultivating excellent varieties of passionflower as an economic fruit tree in rocky desertification areas can promote the development of local industries. At present, there are few studies on the construction of empirical models for estimation of leaf area of Passiflora plants. The size and distribution of plant leaf area (LA) directly affect the ability of leaves to intercept sunlight, carry out carbon utilization and gain the productivity of plant communities. LA is often used as a basic parameter to measure plant photosynthesis capacity, and is used in plant physiology, pathology, and crop breeding. agriculture and forestry production and management, model estimation, etc. Simple, fast and accurate detection of leaf area is of great significance for guiding the reasonable high-density planting, the adjustment of population structure, variable fertilization and precise sprinkling irrigation to obtain high yield. This paper aimed to construct the optimal leaf area eatimation model for 6 species in Passiflora. The empirical model for leaf area estimation can provide basic parameters for studying the physiological ecology and cultivation techniques for Passifloraceae Passiflora.【Methods 】In this study, six species of Passifloraceae Passiflora, i.e., P. edulis, P. yucatanensis, Lady Margaret, P. foetida, P. caerulea and P. laurifolia served as the research samples and these plants were planted in Kedu Town Passion Fruit Production and Academic Research Base, Guizhou Province Mountain Resources Research Institute in March 2020. In August 2020, sample plants were randomly selected with the same growth vigor from each species, good-growing branches were randomly selected from each tree, and about 200 sample mature leaves with typical characteristics and without pests and diseases were picked up from each tree species on 2th, 4th, 6th, 8th and 10th internodes from the end of the branches. After the sample leaves were collected, they were marked, packaged and brought back to the laboratory. Place the leaf flat on an Epson850 scanner and scan it to obtain the leaf image. Use the Digimizer digital image method to measure the leaf length, width and area. Take the maximum length of the leaf as L, the approximate maximum width of the leaf as W, and the area as LA. Select 12 target models, including linear and non-linear equations, respectively, to construct LA empirical models for each species. Select two species with similar leaf shapes to merge modeling, and screen and evaluate these models, so as to select the basis for the optimal empirical model. The optimal empirical model was selected according to the R2, AIC and RMSE values of each empirical model. The optimal empirical model was selected as the model with the R2 closest to 1, minimum AIC and RMSE values. When the best AIC difference between the first two empirical models is less than 2, the model with the smaller RMSE value is selected as the optimal empirical model. In order to further evaluate the reliability of the empirical model, the predicted value of LA is calculated based on the optimal empirical model, and the distribution of its residuals is analyzed. When the distribution is approximately normal and most residual points fall within 3 times of the standard deviation of the residual average if the empirical model is within the range of the measured value of LA as y and the predicted value as x to test the fitting effect of the regression equation.
中文关键词	西番莲属 ; 叶面积 ; 经验模型 ; 分类拟合
英文关键词	Passiflora Leaf area Empirical model Classified fitting
类型	Article
语种	中文
收录类别	CSCD
WOS类目	Agriculture
CSCD记录号	CSCD:7057874
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/377728
作者单位	吴凤婵, 贵州大学林学院, 贵阳, 贵州 550025, 中国.; 谭仲廷, 贵州大学林学院, 贵阳, 贵州 550025, 中国.; 杨瑞, 贵州大学林学院, 贵阳, 贵州 550025, 中国.; 李安定, 贵州科学院贵州省山地资源研究所;;贵州科学院贵州省生物研究所, ;;, 贵阳;;贵阳, ;; 550001;;550009.; 蔡国俊, 贵州科学院贵州省山地资源研究所, 贵阳, 贵州 550001, 中国.
推荐引用方式 GB/T 7714	吴凤婵,李安定,蔡国俊,等. 6种西番莲属(Passiflora)植物叶面积经验模型构建[J],2021,38(9):1600-1610.
APA	吴凤婵,李安定,蔡国俊,谭仲廷,&杨瑞.(2021).6种西番莲属(Passiflora)植物叶面积经验模型构建.果树学报,38(9),1600-1610.
MLA	吴凤婵,et al."6种西番莲属(Passiflora)植物叶面积经验模型构建".果树学报 38.9(2021):1600-1610.