An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs

Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976-1981). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was similar to 6%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage. (C) 2008 Elsevier B.V. All rights reserved.

Leaf area prediction models for Zinnia elegans Jacq., Zinnia haageana regel and 'profusion cherry'

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determination of Merremia cissoides leaf area using the linear measures of the leaflets

O conhecimento da área foliar de plantas daninhas pode auxiliar o estudo das relações de interferência entre elas e as culturas agrícolas. O objetivo desta pesquisa foi determinar uma equação matemática que estime a área foliar de Merremia cissoides, a partir da relação entre as dimensões lineares dos limbos foliares. Folhas da espécie foram coletadas de diferentes locais na Universidade Estadual Paulista, Jaboticabal, Estado de São Paulo, Brasil, medindo-se o comprimento (C), a largura máxima (L) e a área foliar de três tipos de folíolos. Foram estimadas equações lineares Y = a x (X) para cada tipo de folíolo. Houve sobreposição dos intervalos de confiança das equações dos folíolos primário e secundário, por isso considerou-se uma única equação da média desses folíolos, além da equação do folíolo principal, para caracterização da área foliar de M. cissoides. Assim, a área foliar dessa espécie pode ser estimada pelo somatório das áreas dos limbos foliares dos folíolos principal e primário + secundário, por meio da equação AFnest = 0,501 x (X) + 2,181 x (Z), em que X indica C x L do folíolo principal e Z indica C x L médios dos folíolos primário + secundário, respectivamente.

A simple and non-destructive model for individual leaf area estimation in citrus

Introduction. Leaf area is often related to plant growth, development, physiology and yield. Many non-destructive models have been proposed for leaf area estimation of several plant genotypes, demonstrating that leaf length, leaf width and leaf area are closely correlated. Thus, the objective of our study was to develop a reliable model for leaf area estimation from linear measurements of leaf dimensions for citrus genotypes. Materials and methods. Leaves of citrus genotypes were harvested, and their dimensions (length, width and area) were measured. Values of leaf area were regressed against length, width, the square of length, the square of width and the product (length x width). The most accurate equations, either linear or second-order polynomial, were regressed again with a new data set; then the most reliable equation was defined. Results and discussion. The first analysis showed that the variables length, width and the square of length gave better results in second-order polynomial equations, while the linear equations were more suitable and accurate when the width and the product (length x width) were used. When these equations were regressed with the new data set, the coefficient of determination (R(2)) and the agreement index 'd' were higher for the one that used the variable product (length x width), while the Mean Absolute Percentage Error was lower. Conclusion. The product of the simple leaf dimensions (length x width) can provide a reliable and simple non-destructive model for leaf area estimation across citrus genotypes.

A model for optimal chemical control of leaf area damaged by fungi population - Parameter dependence

We present a model to study a fungi population submitted to chemical control, incorporating the fungicide application directly into the model. From that, we obtain an optimal control strategy that minimizes both the fungicide application (cost) and leaf area damaged by fungi population during the interval between the moment when the disease is detected (t = 0) and the time of harvest (t = t(f)). Initially, the parameters of the model are considered constant. Later, we consider the apparent infection rate depending on the time (and the temperature) and do some simulations to illustrate and to compare with the constant case.

Influence of potassium and sodium nutrition on leaf area components in Eucalyptus grandis trees

Background and Aims: Recent studies showed a positive tree response to Na addition in K-depleted tropical soils. Our study aimed to gain insight into the effects of K and Na fertilizations on leaf area components for a widely planted tree species. Methods: Leaf expansion rates, as well as nutrient, polyol and soluble sugar concentrations, were measured from emergence to abscission of tagged leaves in 1-year-old Eucalyptus grandis plantations. Leaf cell size and water status parameters were compared 1 and 2 months after leaf emergence in plots with KCl application (+K), NaCl application (+Na) and control plots (C). Results: K and Na applications enhanced tree leaf area by increasing both leaf longevity and the mean area of individual leaves. Higher cell turgor in treatments +K and +Na than in the C treatment resulting from higher concentrations of osmotica contributed to increasing both palisade cell diameters and the size of fully expanded leaves. Conclusions: Intermediate total tree leaf area in treatment +Na compared to treatments C and +K might result from the capacity of Na to substitute K in osmoregulatory functions, whereas it seemed unable to accomplish other important K functions that contribute to delaying leaf senescence. © 2013 Springer Science+Business Media Dordrecht.

Non-destructive equations to estimate the leaf area of Styrax pohlii and Styrax ferrugineus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

TANZANIA GRASS STRUCTURE GRAZED BY GOATS MANAGED WITH DIFFERENT RESIDUAL LEAF AREA INDEX UNDER INTERMITTENT STOCKING

The objective of this study was to evaluate the structure of Tanzania grassland grazed by goats managed with different residue leaf area index (RLAI) under intermittent stocking. The experiment was carried out from February to August, 2008. The treatments consisted of three different targets RLAI (0.8, 1.6 and 2.4) and 95% light interception (LI) criterion determined the rest period. Forage samples were collected at average height sampling points and weighed. Subsequently, a smaller sample was removed to separate the morphological components (leaf, stem and dead material) and to determine the structural and productive features. The canopy architecture was evaluated by the method of inclined point quadrat. The pre-grazing height in the paddocks were significantly different among treatments. RLAI influenced dry matter contents of green forage, leaf, stem and total, with the exception of dry matter of dead material, where the lowest values were observed for 0.8 RLAI. Thus, RLAI modifies canopy structure and is sensitive to canopy height changes throughout the year. Pasture regrowth is not compromised by residual leaf area indexes between 0.8 and 2.4, when climatic factors are not limiting.

Non-destructive linear model for leaf area estimation in Vernonia ferruginea Less

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.

(Table 3) Leaf area and leaf nitrogen for deciduous, evergreen, forb and graminoid species at Barrow, Svalbard and Zackenberg

Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub-Arctic tundra are leaf area index (LT) and total foliar nitrogen (NT). LT and NT have been shown to be tightly coupled across PFTs in sub-Arctic tundra vegetation, which simplifies up-scaling by allowing quantification of the main drivers of P from remotely sensed LT. Our objective was to test the LT-NT relationship across multiple Arctic latitudes and to assess LT as a predictor of P for the pan-Arctic. Including PFT-specific parameters in models of LT-NT coupling provided only incremental improvements in model fit, but significant improvements were gained from including site-specific parameters. The degree of curvature in the LT-NT relationship, controlled by a fitted canopy nitrogen extinction co-efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (NM), and we show for the first time that LT-NT coupling is achieved across latitudes via canopy-scale trade-offs between NM and leaf mass per unit leaf area (LM). Site-specific parameters provided small but significant improvements in models of P based on LT and moss cover. Our results suggest that differences in LT-NT coupling between sites could be used to improve pan-Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.

Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions

The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine’s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.

Ground cover and leaf area index relationship in a grass, legume and crucifer crop

Canopy characterization is essential for describing the interaction of a crop with its environment. The goal of this work was to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop, and to assess the feasibility of using these relationships as well as LAI-2000 readings to estimate LAI. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. Linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI mayor que 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley.