Estimativa da área foliar de plantas daninhas: poaia-branca

A poaia-branca (Richardia brasiliensis Gomez) é uma das principais plantas que infestam espontaneamente os agroecossistemas na América do Sul e, com freqüência, atingem elevadas densidades populacionais, provocando sérios prejuízos aos agricultores. Nos estudos envolvendo a biologia e o controle de plantas daninhas, a área foliar é uma das mais importantes características a serem avaliadas, mas tem sido pouco estudada porque sua determinação exige equipamentos sofisticados ou utiliza técnica destrutiva. Visando obter equações que permitissem a estimativa da área foliar desta planta daninha utilizando características lineares do limbo foliar, facilmente mensuráveis em plantas no campo, foram estudadas correlações entre a área foliar real e as seguintes características das folhas: comprimento ao longo da nervura principal (C), largura máxima do limbo (L) e o produto CxL. Para tanto, foram mensurados os limbos de 500 folhas coletadas em diversas épocas, locais e culturas, em plantas que apresentavam bom aspecto sanitário e nutricional. Todas as equações, lineares simples, geométricas e exponenciais, permitiram boa estimativa da área foliar (AF) da poaia-branca. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto Cx L, a qual apresentou o menor QM Resíduo. Assim, a estimativa da área folia r de R. brasiliensis pode ser efetuada pela equação AF= 0.5899 (CxL), com coeficiente de determinação (R2) de valor 0.9886 .

Estimativas da área da folha de figueiras 'Roxo de Valinhos' usando dimensões lineares do limbo foliar

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

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.

Phosphorus nutrition and tolerance of cotton to water stress: II. Water relations, free and bound water and leaf expansion rate

In previous experiments, increased leaf-Phosphorus (P) content with increasing P supply enhanced the individual leaf expansion and water content of fresh cotton leaves in a severely drying soil. In this paper, we report on the bulk water content of leaves and its components, free and bound water, along with other measures of plant water status, in expanding cotton leaves of various ages in a drying soil with different P concentrations. The bound water in living tissue is more likely to play a major role in tolerance to abiotic stresses by maintaining the structural integrity and/or cell wall extensibility of the leaves, whilst an increased amount of free water might be able to enhance solute accumulation, leading to better osmotic adjustment and tolerance to water stress, and maintenance of the volumes of sub-cellular compartments for expansive leaf growth. There were strong correlations between leaf-P%, leaf water (total, free and bound water) and leaf expansion rate (LER) under water stress conditions in a severely drying soil. Increased soil-P enhanced the uptake of P from a drying soil, leading to increased supply of osmotically active inorganic solutes to the cells in growing leaves. This appears to have led to the accumulation of free water and more bound water, ultimately leading to increased leaf expansion rates as compared to plants in low P soil under similar water stress conditions. The greater amount of bound and free water in the high-P plants was not necessarily associated with changes in cell turgor, and appears to have maintained the cell-wall properties and extensibility under water stressed conditions in soils that are nutritionally P-deficient.

Leaf trait co-ordination in relation to construction cost, carbon gain and resource-use efficiency in exotic invasive and native woody vine species

Background and Aims: Success of invasive plant species is thought to be linked with their higher leaf carbon fixation strategy, enabling them to capture and utilize resources better than native species, and thus pre-empt and maintain space. However, these traits are not well-defined for invasive woody vines. Methods: In a glass house setting, experiments were conducted to examine how leaf carbon gain strategies differ between non-indigenous invasive and native woody vines of south-eastern Australia, by investigating their biomass gain, leaf structural, nutrient and physiological traits under changing light and moisture regimes. Key Results: Leaf construction cost (CC), calorific value and carbon : nitrogen (C : N) ratio were lower in the invasive group, while ash content, N, maximum photosynthesis, light-use efficiency, photosynthetic energyuse efficiency (PEUE) and specific leaf area (SLA) were higher in this group relative to the native group. Trait plasticity, relative growth rate (RGR), photosynthetic nitrogen-use efficiency and water-use efficiency did not differ significantly between the groups. However, across light resource, regression analyses indicated that at a common (same) leaf CC and PEUE, a higher biomass RGR resulted for the invasive group; also at a common SLA, a lower CC but higher N resulted for the invasive group. Overall, trait co-ordination (using pair-wise correlation analyses) was better in the invasive group. Ordination using 16 leaf traits indicated that the major axis of invasive-native dichotomy is primarily driven by SLA and CC (including its components and/or derivative of PEUE) and was significantly linked with RGR. Conclusions: These results demonstrated that while not all measures of leaf resource traits may differ between the two groups, the higher level of trait correlation and higher revenue returned (RGR) per unit of major resource need (CC) and use (PEUE) in the invasive group is in line with their rapid spread where introduced.

Measures of Plant Surface-areas for Eurasian Watermilfoil and Water Stargrass

Plant surface areas were measured from samples of two common submersed aquatics with widely diverging morphologies: Eurasian watermilfoil ( Myriophyllum spicatum L.) and water stargrass ( Heteranthera dubia (Jacq.) MacM.). Measures for the highly dissected leaves of Eurasian watermilfoil involved development of a regression equation relating leaf length to direct measures of a subsample of leaf parts. Measures for the simple leaves of the stargrass were sums of measured triangles. Stem surfaces for both species were calculated as measured cylinders. Though the means of the stem length and leaf length were larger for stargrass samples, their mean surface area was 95 cm 2 which was less than the 108 cm 2 recorded for Eurasian watermilfoil samples. Relating surface area to dry weight for the stargrass was straightforward, with 1 mg of dry weight yielding an average 0.678 cm 2 of surface area. Biomass measures for the water milfoil were confounded by the additional weight of epiphytic algae persisting on cleaned samples. The results suggest that a lesstime consuming method for surface area measures of plants with highly dissected leaves and a caveat for using biomass measures to estimate surface area in such plants.

PsT-1: A new Tryptophyllin peptide from the skin secretion of Waxy Monkey Leaf Frog, Phyllomedusa sauvagei

The Waxy Monkey Leaf Frog, Phyllomedusa sauvagei, has been extensively-studied for many years, and a broad spectrum of bioactive peptides has been found in its skin secretions. Here we report the discovery of a novel tryptophyllin (TPH) peptide, named PsT-1, from this frog species. Skin secretions from specimens of P. sauvagei were collected by mild electrical stimulation. Peptides were identified and characterized by transcriptome cloning, and the structure was confirmed by MALDI-TOF mass spectrometry and automated Edman degradation. This novel peptide was encoded by a single precursor of 61 amino acid residues, whose primary structure was deduced from cloned skin cDNA. Analysis of different amphibian tryptophyllins revealed that PsT-1 exhibited a high degree of primary structural similarity to its homologues, PdT-1 and PdT-2, from the Mexican giant leaf frog, Pachymedusa dacnicolor. A synthetic replicate of PsT-1 was found to inhibit bradykinin-induced vasorelaxation of phenylephrine pre-constricted rat tail artery smooth muscle. It was also found that PsT-1 had an anti-proliferative effect on three different human prostate cancer cell lines (LNCaP/PC3/DU145), by use of an MTT assay coupled with direct cell counting as measures of cell growth. These data indicate that PsT-1 is a likely bradykinin receptor antagonist and its biological effects are probably mediated through bradykinin receptors. As a BK antagonist, PST-1, with antagonistic effects on BK in artery smooth muscle, inhibition of proliferation in prostate cancer cells and lack of undesirable side effects, may have potential in cardiovascular, inflammatory and anticancer therapy.

Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Building binary-tree-based multiclass classifiers using separability measures

Various popular machine learning techniques, like support vector machines, are originally conceived for the solution of two-class (binary) classification problems. However, a large number of real problems present more than two classes. A common approach to generalize binary learning techniques to solve problems with more than two classes, also known as multiclass classification problems, consists of hierarchically decomposing the multiclass problem into multiple binary sub-problems, whose outputs are combined to define the predicted class. This strategy results in a tree of binary classifiers, where each internal node corresponds to a binary classifier distinguishing two groups of classes and the leaf nodes correspond to the problem classes. This paper investigates how measures of the separability between classes can be employed in the construction of binary-tree-based multiclass classifiers, adapting the decompositions performed to each particular multiclass problem. (C) 2010 Elsevier B.V. All rights reserved.

Efficiency and soil contamination during underground application of insecticides: control of leaf-cutting ants with thermal foggers

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

Morphological patterns and community organization in leaf-litter ant assemblages

We present a new approach to determine the number and composition of guilds, using the hyperdiverse leaf-litter ant fauna as a model, based on appropriate morphological variables and species co-occurrence null models to describe the complex assemblages of interacting Species Community structure at the 1-m(2) scale. We obtained 18 linear morphometric measures from 949 workers of 171 leaf-litter ant species (18762 measurements) surveyed in four Atlantic Forest localities to test whether the assemblages are morphologically structured; the morphological characters were selected to indicate diet and foraging habits. Principal components analysis was used to characterize the morphospace and to describe the guild structure (number of species and composition). The guild proportionality assembly rule (significant tendency toward constant proportion of species in guilds) was assessed at the 1-m(2) scale. Our analysis indicates that the division of leaf-litter ants into guilds is based mainly on microhabitat distribution in the leaf-litter, body size and shape, eye size, and phylogeny. The same guild scheme applied to four more sites shows that different Atlantic Forest areas have the same leaf-fitter ant guilds. The guild proportionality assembly rule was confirmed for most guilds, Suggesting that there are guild-specific limitations on species coexistence within assemblages; on the other hand, in a few cases the variance in guild proportion was greater than expected under the null assumptions. Other studies on ant functional group classification are partially supported by our quantitative morphological analysis. Our results, however, imply that there are more compartments than indicated in previous models, particularly among cryptic species (confined to soil and litter) and tropical climate specialists. We argue that a general null model for the analysis of species association based oil morphology can reveal objectively defined groups and may thus contribute to a robust theory to explain community structure in general and have important consequences on studies of litter ant community ecology in particular.

Tree Species Composition and Harvest Intensity Affect Herbivore Density and Leaf Damage on Beech, Fagus sylvatica, in Different Landscape Contexts

Most forests are exposed to anthropogenic management activities that affect tree species composition and natural ecosystem processes. Changes in ecosystem processes such as herbivory depend on management intensity, and on regional environmental conditions and species pools. Whereas influences of specific forest management measures have already been addressed for different herbivore taxa on a local scale, studies considering effects of different aspects of forest management across different regions are rare. We assessed the influence of tree species composition and intensity of harvesting activities on arthropod herbivores and herbivore-related damage to beech trees, Fagus sylvatica, in 48 forest plots in three regions of Germany. We found that herbivore abundance and damage to beech trees differed between regions and that – despite the regional differences - density of tree-associated arthropod taxa and herbivore damage were consistently affected by tree species composition and harvest intensity. Specifically, overall herbivore damage to beech trees increased with increasing dominance of beech trees – suggesting the action of associational resistance processes – and decreased with harvest intensity. The density of leaf chewers and mines was positively related to leaf damage, and several arthropod groups responded to beech dominance and harvest intensity. The distribution of damage patterns was consistent with a vertical shift of herbivores to higher crown layers during the season and with higher beech dominance. By linking quantitative data on arthropod herbivore abundance and herbivory with tree species composition and harvesting activity in a wide variety of beech forests, our study helps to better understand the influence of forest management on interactions between a naturally dominant deciduous forest tree and arthropod herbivores.

Simple measures of climate, soil properties and plant traits predict national-scale grassland soil carbon stocks

Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. Using data from an extensive national survey of English grasslands, we show that surface soil (0–7 cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. Soil C stocks in the largest pool, of intermediate particle size (50–250 μm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0·45–50 μm), was explained by soil pH and the community abundance-weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N-rich vegetation. The C stock in the small active fraction (250–4000 μm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. Synthesis and applications. Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1–100 000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Midday measurements of leaf water potential and stomatal conductance are highly correlated with daily water use of Thompson Seedless grapevines

A study was conducted to determine the relationship between midday measurements of vine water status and daily water use of grapevines measured with a weighing lysimeter. Water applications to the vines were terminated on August 24th for 9 days and again on September 14th for 22 days. Daily water use of the vines in the lysimeter (ETLYS) was approximately 40 L vine−1 (5.3 mm) prior to turning the pump off, and it decreased to 22.3 L vine−1 by September 2nd. Pre-dawn leaf water potential (ΨPD) and midday Ψl on August 24th were −0.075 and −0.76 MPa, respectively, with midday Ψl decreasing to −1.28 MPa on September 2nd. Leaf g s decreased from ~500 to ~200 mmol m−2 s−1 during the two dry-down periods. Midday measurements of g s and Ψl were significantly correlated with one another (r = 0.96) and both with ETLYS/ETo (r = ~0.9). The decreases in Ψl, g s, and ETLYS/ETo in this study were also a linear function of the decrease in volumetric soil water content. The results indicate that even modest water stress can greatly reduce grapevine water use and that short-term measures of vine water status taken at midday are a reflection of daily grapevine water use

LiDAR simulation in modelled orchards to optimise the use of terretrial laser scanners and derived vegetative measures

Light detection and ranging (LiDAR) technology is beginning to have an impact on agriculture. Canopy volume and/or fruit tree leaf area can be estimated using terrestrial laser sensors based on this technology. However, the use of these devices may have different options depending on the resolution and scanning mode. As a consequence, data accuracy and LiDAR derived parameters are affected by sensor configuration, and may vary according to vegetative characteristics of tree crops. Given this scenario, users and suppliers of these devices need to know how to use the sensor in each case. This paper presents a computer program to determine the best configuration, allowing simulation and evaluation of different LiDAR configurations in various tree structures (or training systems). The ultimate goal is to optimise the use of laser scanners in field operations. The software presented generates a virtual orchard, and then allows the scanning simulation with a laser sensor. Trees are created using a hidden Markov tree (HMT) model. Varying the foliar structure of the orchard the LiDAR simulation was applied to twenty different artificially created orchards with or without leaves from two positions (lateral and zenith). To validate the laser sensor configuration, leaf surface of simulated trees was compared with the parameters obtained by LiDAR measurements: the impacted leaf area, the impacted total area (leaves and wood), and th impacted area in the three outer layers of leaves.