Estimating the Leaf Area of Cut Roses in Different Growth Stages Using Image Processing and Allometrics
TL;DR: A statistical model based on the “multiple stepwise regression” technique and based on 26 stems collected at different developmental stages explained 95% of the LA variance and can save time, effort, and resources in determining cut rose stem LA, enhancing its application in research and production contexts.
Abstract: Non-destructive, accurate, user-friendly and low-cost approaches to determining crop leaf area (LA) are a key tool in many agronomic and physiological studies, as well as in current agricultural management. Although there are models that estimate cut rose LA in the literature, they are generally designed for a specific stage of the crop cycle, usually harvest. This study aimed to estimate the LA of cut “Red Naomi” rose stems in several phenological phases using morphological descriptors and allometric measurements derived from image processing. A statistical model was developed based on the “multiple stepwise regression” technique and considered the stem height, the number of stem leaves, and the stage of the flower bud. The model, based on 26 stems (232 leaves) collected at different developmental stages, explained 95% of the LA variance (R2 = 0.95, n = 26, p < 0.0001). The mean relative difference between the observed and the estimated LA was 8.2%. The methodology had a high accuracy and precision in the estimation of LA during crop development. It can save time, effort, and resources in determining cut rose stem LA, enhancing its application in research and production contexts.
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TL;DR: Both lab and outdoor measurements of leaf parameters showed that the developed method and the standard method were highly correlated, and the results of different mobile phone measurements were not significantly different.
Abstract: Automatic and efficient plant leaf geometry parameter measurement offers useful information for plant management. The objective of this study was to develop an efficient and effective leaf geometry parameter measurement system based on the Android phone platform. The Android mobile phone was used to process and measure geometric parameters of the leaf, such as length, width, perimeter, and area. First, initial leaf images were pre-processed by some image algorithms, then distortion calibration was proposed to eliminate image distortion. Next, a method for calculating leaf parameters by using the positive circumscribed rectangle of the leaf as a reference object was proposed to improve the measurement accuracy. The results demonstrated that the test distances from 235 to 260 mm and angles from 0 to 45 degrees had little influence on the leafs’ geometric parameters. Both lab and outdoor measurements of leaf parameters showed that the developed method and the standard method were highly correlated. In addition, for the same leaf, the results of different mobile phone measurements were not significantly different. The leaf geometry parameter measurement system based on the Android phone platform used for this study could produce high accuracy measurements for leaf geometry parameters.
19 citations
Cites background from "Estimating the Leaf Area of Cut Ros..."
...Leaf geometric parameters are not only an important indicator of plant growth and development, yield formation, and a variety of other characteristics, but also provide important data support for the cultivation and management of crops, and the monitoring of pests and diseases [2]....
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TL;DR: The USP-Leaf software, a new software system aimed at processing images of samples composed of multiple leaves without any requirements of manual pre-processing of the images, was developed and provided accurate estimates of leaf area.
13 citations
TL;DR: In this article, the performance of the Adaptive Neural-Based Fuzzy Inference System (ANFIS) in predicting the LA of 61 plant species (C) was investigated.
Abstract: Leaf Area (LA) is a key index of plant productivity and growth. A multiple linear regression technique is commonly applied to estimate LA as a non-destructive and quick method, but this technique is limited under the realistic situation. Thus, it is indispensable to elaborate new models for estimation. In this research, the performance of the Adaptive Neural-Based Fuzzy Inference System (ANFIS) in predicting the LA of 61 plant species (C) was investigated. Four parameters including leaf length (L), leaf width (W), C, and specific coefficient (K) for each plant were selected as input data to the ANFIS model and the LA as the output. Seven different ANFIS models including different combinations of input data were constructed to reveal the sensitivity analysis of the models. The normalized root mean square error (NRMSE), mean residual error (MRE), and linear regression were applied between observed LA and estimated LA by the models. The results indicated that ANFIS4-K2min which employed all input dat...
11 citations
TL;DR: In this paper, the authors developed a model for estimating the leaf area (LA) of maize, considering the entire growth cycle, based on non-destructive allometric measurements, including the number of leaves per plant and the product of major leaf length per major leaf width of the greater leaf.
Abstract: The literature points out the need for leaf area (LA) calibration models that are suitable for specific varieties (variety-specific). These models should be capable of coping with different crop conditions, growth stages, and agronomic practices. The objective of the current study was to develop a model for estimating the LA of ​​maize (Zea mays L.), considering the entire growth cycle, based on non-destructive allometric measurements. The proposed model was derived from a multiple regression analysis of LA data obtained from digital image processing, including the number of leaves per plant (NL) and the product of major leaf length per major leaf width of the greater leaf (MLL × MLW). A high percent of data variability in the LA of maize plants was explained by the model, both in the calibration and validation phases (R2 = 0.90; n = 30). Overall, the selected model presented good performance in the estimation of LA of maize, variety PAN 53, cultivated under the conditions of the present study area. Additionally, the model enabled the estimation of LA at different stages of the crop cycle. The results indicated a positive potential for using the developed model to support several maize cultural practices.
Key words: Allometry, non-destructive measurement, modelling, Zea mays.
6 citations
Cites background or result from "Estimating the Leaf Area of Cut Ros..."
...According to Costa et al. (2016), the flexibility of LA models for use at different crop development stages is an important feature to support, throughout the crop cycle, different agricultural practices of high agronomic, economic and environmental importance, such as management of crop water…...
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...Previous studies have shown reasonable results of LA estimations using Image J software and other image processing software (Costa et al., 2016)....
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TL;DR: In this paper, the authors determined mathematical equations that estimate the leaf area of Artocarpus heterophyllus in an easy and non-destructive way based on linear dimensions.
Abstract: The objective of this study was to determine mathematical equations that estimate the leaf area of jackfruit (Artocarpus heterophyllus) in an easy and non-destructive way based on linear dimensions. In this way, 300 leaves of different sizes and in good sanitary condition of adult plants were collected at the Federal Institute of Espirito Santo, Campus Itapina, located in Colatina, municipality north of the State of Espirito Santo, Brazil. Were measured The length (L) along the midrib and the maximum leaf width (W), observed leaf area (OLA), besides the product of the multiplication of length with width (LW), length with length (LL) and width with width (WW). The models of linear equations of first degree, quadratic and power and their respective R2 were adjusted using OLA as dependent variable in function of L, W and LW, LL and WW as independent variable. The data were validated and the estimated leaf area (ELA) was obtained. The means of ELA and OLA were compared by Student’s t test (5% probability) and were evaluated by the mean absolute error (MAE) and root mean square error (RMSE) criteria. The choice of the best model was based on non-significant comparative values of ELA and OLA, in addition to the closest values of zero of EAM and RQME. The jackfruit leaf area estimate can be determined quickly, accurately and non-destructively by the linear first-order model with LW as the independent variable by equation ELA = 1.07451 + 0.71181(LW).
4 citations
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Book•
01 Dec 1981
TL;DR: In this paper, the authors propose a simple linear regression model with variable selection and multicollinearity for robust regression, and validate the model using regression analysis and validation of regression models.
Abstract: Preface. Introduction. Simple Linear Regression. Multiple Linear Regression. Model Adequacy Checking. Transformations and Weighting to Correct Model Inadequacies. Diagnostics for Leverage and Influence. Polynomial Regression Models. Indicator Variables. Variable Selection and Model Building. Multicollinearity. Robust Regression. Introduction to Nonlinear Regression. Generalized Linear Models. Other Topics in the Use of Regression Analysis. Validation of Regression Models. Appendix A. Statistical Tables. Appendix B. Data Sets for Exercises. Appendix C. Supplemental Technical Material. References. Index.
5,664 citations
TL;DR: It is suggested that the use of a digital camera with high dynamic range has the potential to overcome a number of described technical problems related to indirect LAI estimation.
1,396 citations
"Estimating the Leaf Area of Cut Ros..." refers background or methods in this paper
...Direct methods are more accurate but have the disadvantages of being very time-consuming, not user-friendly, and having constraints regarding equipment acquisition, price, and operation [4]....
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...Considering the advantages of indirect methods, they are now assuming a particular relevance when compared with direct methods [4]....
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...Direct methods include planimetric or gravimetric analyses of leaves, harvested directly or indirectly [3,4]....
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TL;DR: The accuracy, sampling strategy and spatial validity of theLAI measurements have to be assessed for quality assurance of both the measurement and the modelling purposes of all the LAI-dependent ecophysiological and biophysical processes of canopies.
Abstract: Leaf area index (LAI) is the total one-sided area of leaf tissue per unit ground surface area. It is a key parameter in ecophysiology, especially for scaling up the gas exchange from leaf to canopy level. It characterizes the canopy‐atmosphere interface, where most of the energy fluxes exchange. It is also one of the most difficult to quantify properly, owing to large spatial and temporal variability. Many methods have been developed to quantify LAI from the ground and some of them are also suitable for describing other structural parameters of the canopy. This paper reviews the direct and indirect methods, the required instruments, their advantages, disadvantages and accuracy of the results. Analysis of the literature shows that most cross-validations between direct and indirect methods have pointed to a significant underestimation of LAI with the latter techniques, especially in forest stands. The two main causes for the discrepancy, clumping and contribution of stem and branches, are discussed and some recent theoretical or technical solutions are presented as potential improvements to reduce bias or discrepancies. The accuracy, sampling strategy and spatial validity of the LAI measurements have to be assessed for quality assurance of both the measurement and the modelling purposes of all the LAI-dependent ecophysiological and biophysical processes of canopies.
1,252 citations
"Estimating the Leaf Area of Cut Ros..." refers methods in this paper
...Direct methods include planimetric or gravimetric analyses of leaves, harvested directly or indirectly [3,4]....
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TL;DR: A dynamic simulation model for tomato crop growth and development, TOMSIM, is evaluated, showing that global radiation, CO 2 concentration, specific leaf area (SLA) and the developmental stage of a vegetative unit at leaf pruning had a large influence on crop growth rate, whereas temperature, number of fruits per truss, sink strength of a vegetarian unit and plant density were less important.
184 citations
"Estimating the Leaf Area of Cut Ros..." refers background in this paper
...Consequently, LA measurements along the crop cultural cycle are often not possible, although they have been empirically simulated in complex crop-specific growth models when available [20]....
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TL;DR: The millimeter graph paper method can be used for estimating leaf area in lieu of leaf area meter, and can estimate accurately the leaf area of plants in many experiments without the use of any expensive instruments.
Abstract: Easy, accurate, inexpensive, and nondestructive methods to determine individual leaf area of plants are a useful tool in physiological and agronomic studies. This paper introduces a cost-effective alternative (called here millimeter graph paper method) for standard electronic leaf area meter, using a millimeter graph paper. Investigations were carried out during August–October, 2009-2010, on 33 species, in the Botanical garden of the Banaras Hindu University at Varanasi, India. Estimates of leaf area were obtained by the equation, leaf area (cm2) = , where is the weight (g) of the area covered by the leaf outline on a millimeter graph paper, and is the weight of one cm2 of the same graph paper. These estimates were then compared with destructive measurements obtained through a leaf area meter; the two sets of estimates were significantly and linearly related with each other, and hence the millimeter graph paper method can be used for estimating leaf area in lieu of leaf area meter. The important characteristics of this cost-efficient technique are its easiness and suitability for precise, non-destructive estimates. This model can estimate accurately the leaf area of plants in many experiments without the use of any expensive instruments.
177 citations
"Estimating the Leaf Area of Cut Ros..." refers background in this paper
...Radiation and photosynthetic efficiency, crop transpiration, crop water use, and nutrient use are some of the processes impacted by the LA of a crop [1,2]....
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