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.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

Towards developing reliable models of leaf area on grapevines (Vitis vinifera L.)

A field study in three vineyards in southern Queensland (Australia) was carried out to develop predictive models for individual leaf area and shoot leaf area of two cultivars (Cabernet Sauvignon and Shiraz) of grapevines (Vitis Vinifera L.). Digital image analysis was used to measure leaf vein length and leaf area. Stepwise regressions of untransformed and transformed models consisting of up to six predictor variables for leaf area and three predictor variables for shoot leaf area were carried out to obtain the most efficient models. High correlation coefficients were found for log10 transformed individual leaf and shoot leaf area models. The significance of predictor variables in the models varied across vineyards and cultivars, demonstrating the discontinuous and heterogeneous nature of vineyards. The application of this work in a grapevine modeling environment and in a dynamic vineyard management context are discussed. Sample sizes for quantification of individual leaf areas and areas of leaves on shoots are proposed based on target margins of errors of sampled data.

Estimation of leaf area in grapevine cv. Syrah using empirical models

Aiming to obtain empirical models for the estimation of Syrah leaf area a set of 210 fruiting shoots was randomly collected during the 2013 growing season in an adult experimental vineyard, located in Lisbon, Portugal. Samples of 30 fruiting shoots were taken periodically from the stage of inflorescences visible to veraison (7 sampling dates). At the lab, from each shoot, primary and lateral leaves were separated and numbered according to node insertion. For each leaf, the length of the central and lateral veins was recorded and then the leaf area was measured by a leaf area meter. For single leaf area estimation the best statistical models uses as explanatory variable the sum of the lengths of the two lateral leaf veins. For the estimation of leaf area per shoot it was followed the approach of Lopes & Pinto (2005), based on 3 explanatory variables: number of primary leaves and area of the largest and smallest leaves. The best statistical model for estimation of primary leaf area per shoot uses a calculated variable obtained from the average of the largest and smallest primary leaf area multiplied by the number of primary leaves. For lateral leaf area estimation another model using the same type of calculated variable is also presented. All models explain a very high proportion of variability in leaf area. Our results confirm the already reported strong importance of the three measured variables (number of leaves and area of the largest and smallest leaf) as predictors of the shoot leaf area. The proposed models can be used to accurately predict Syrah primary and secondary leaf area per shoot in any phase of the growing cycle. They are inexpensive, practical, non-destructive methods which do not require specialized staff or expensive equipment.

Root:Shoot Ratio and Specific Leaf Area Along an Elevational Gradient in the Peruvian Andes

Andean montane forests are one of the most diverse ecosystems on Earth, but are also highly vulnerable to climate change. Therefore, the link between plant distribution and ecosystem productivity is a critical point to investigate in these ecosystems. Are the patterns in productivity observed in montane forest due to species turnover along the elevational gradients? Methodological constraints keep this question unanswered. Also, despite their importance, belowground biomass remains poorly quantified and understood. I measured two plant functional traits in seedlings, root:shoot ratio and specific leaf area, to identify different strategies in growth and biomass allocation across elevations. A tradeoff in specific leaf area with elevation was found in only one species, and no generalized directional change was detected with elevations for root:shoot ratio. Lack of information for the ontogeny of the measured plant traits could confounding the analysis.

Efeitos da cobertura do solo com filme de polietileno azul no consumo de água da cultura da alface cultivada em estufa

The covering of the soil is an agricultural practice that intends to control the harmful herbs, to reduce the losses of water by evaporation of the soil, and to facilitate the harvest and the commercialization, once the product is cleaner and healthier. However, when the soil is covered important microclimatic parameters are also altered, and consequently the germination of seeds, the growth of roots, the absorption of water and nutrients, the metabolic activity of the plants and the carbohydrates storage. The current trial intended to evaluate the effect of soil covering with blue colored film on consumptive water-use in a lettuce crop (Lactuca sativa, L.). The experiment was carried out in a plastic greenhouse in Araras - São Paulo State, Brazil from March 3rd, 2001 to May 5th, 2001. The consumptive water-use was measured through two weighing lysimeter installed inside the greenhouse. Crop spacing was 0.25 m x 0.25 m and the color of the film above soil was blue. Leaf area index (IAF), was measured six times (7; 14; 21; 28; 35; 40 days after transplant) and the water-use efficiency (EU) was measured at the end. The experimental design was subdivided portions with two treatments, bare soil and covered soil. The average consumptive water-use was 4.17 mm day-1 to the bare soil treatment and 3.11 mm day-1 to the covered soil treatment. The final leaf area index was 25.23 to the bare soil treatment and 24.39 to the covered soil treatment, and there was no statistical difference between then.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

Can intensive management accelerate the restoration of Brazil`s Atlantic forests?

Only 7% of the once extensive forest along the eastern coast of Brazil remains, and much of that is degraded and threatened by agricultural expansion and urbanization. We wondered if methods similar to those developed to establish fast-growing Eucalyptus plantations might also work to enhance survival and growth of rainforest species on degraded pastures composed of highly competitive C(4) grasses. An 8-factor experiment was laid out to contrast the value of different intensities of cultivation, application of fertilizer and weed control on the growth and survival of a mixture of 20 rainforest species planted at two densities: 3 m x 1 m, and 3 m x 2 m. Intensive management increased seedling survival from 90% to 98%, stemwood production and leaf area index (LAI) by similar to 4-fold, and stemwood production per unit of light absorbed by 30%. Annual growth in stem biomass was closely related to LAI alone (r(2) = 0.93, p < 0.0001), and the regression improved further in combination with canopy nitrogen content (r(2) =0.99, p < 0.0001). Intensive management resulted in a nearly closed forest canopy in less than 4 years, and offers a practical means to establish functional forests on abandoned agricultural land. (C) 2009 Elsevier B.V. All rights reserved.

CLIMATOLOGICAL HYDRIC BALANCE, EFFECTIVE SOIL WATER STORAGE AND TRANSPIRATION IN COFFEE CULTURE

The climatic water balance is one of the most used tools to assess, indirectly the amount of water present in the soil is capable of meeting the water needs of the plant. This study analyzed the climatologic hydric balance, the effective soil water storage and coffee plant transpiration in dry regimen cultivation. Daily climatologic hydric balance was calculated for coffee from January 2003 to May 2006. It was concluded that even in the most rainy months of the year, there is a hydric deficit in coffee plants grown in a dry regimen; effective soil water storage varied greatly through the years evaluated, and September was the most critical month, when this value remained below 30%; relative transpiration can not be taken as the single evaluation method for yield losses of coffee, grown in a dry regimen.

Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - II. Testing simulation capabilities of wheat growth

To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

Radiation use efficiency increases when the diffuse component of incident radiation is enhanced under shade

Theoretical analyses have shown the radiation use efficiency of maize, soybean, and peanut to increase with a decrease in the level of incident radiation and an increase in the proportion of diffuse radiation. This study compared the growth and radiation use efficiency of Panicum maximum cv. Petrie (green panic) and Bothriochloa insculpta cv. Bisset (creeping bluegrass) beneath shading treatments (birdguard and solarweave shadecloths) with that in full sunlight. A level of incident radiation reduced by 25% under birdguard shadecloth decreased final yield and final leaf area index, but increased canopy leaf nitrogen concentration and radiation use efficiency (19-14%) (compared with the full sun treatment). A similar level of reduced incident radiation under solarweave shadecloth (which provided an increased proportion of diffuse radiation), increased final yield and radiation use efficiency (46-50%). An understanding of the effects of composition of incident radiation on radiation use efficiency of tropical grasses enables more accurate estimation of potential pasture growth in shaded environments. It also has impact upon crop production in glasshouses and greenhouses.

Environmental control of potential yield of sunflower in the subtropics

A simple framework was used to analyse the determinants of potential yield of sunflower (Helianthus annuus L.) in a subtropical environment. The aim was to investigate the stability of the determinants crop duration, canopy light interception, radiation use efficiency (RUE), and harvest index (HI) at 2 sowing times and with 3 genotypes differing in crop maturity and stature. Crop growth, phenology, light interception, yield, prevailing temperature, and radiation were recorded and measured throughout the crop cycle. Significant differences in grain yield were found between the 2 sowings, but not among genotypes within each sowing. Mean yields (0% moisture) were 6 . 02 and 2 . 17 t/ha for the first sowing, on 13 September (S1), and the second sowing, on 5 March (S2), respectively. Exceptionally high yields in S1 were due to high biomass assimilation associated with the high radiation environment, high light interception owing to a greater leaf area index, and high RUE (1 . 47-1 . 62 g/MJ) across genotypes. It is proposed that the high RUE was caused by high levels of available nitrogen maintained during crop growth by frequent applications of fertiliser and sewage effluent as irrigation. In addition to differences in the radiation environment, the assimilate partitioned to grain was reduced in S2 associated with a reduction in the duration of grain-filling. Harvest index was 0 . 40 in S1 and 0 . 25 in S2. It is hypothesised that low minimum temperatures experienced in S2 reduced assimilate production and partitioning, causing premature maturation.

Tillering in grain sorghum over a wide range of population densities: Modelling dynamics of tiller fertility

The prediction of tillering is poor or absent in existing sorghum crop models even though fertile tillers contribute significantly to grain yield. The objective of this study was to identify general quantitative relationships underpinning tiller dynamics of sorghum for a broad range of assimilate availabilities. Emergence, phenology, leaf area development and fertility of individual main calms and tillers were quantified weekly in plants grown at one of four plant densities ranging from two to 16 plants m(-2). On any given day, a tiller was considered potentially fertile (a posteriori) if its number of leaves continued to increase thereafter. The dynamics of potentially fertile tiller number per plant varied greatly with plant density, but could generally be described by three determinants, stable across plant densities: tiller emergence rate aligned with leaf ligule appearance rate; cessation of tiller emergence occurred at a stable leaf area index; and rate of decrease in potentially fertile tillers was linearly related to the ratio of realized to potential leaf area growth. Realized leaf area growth is the measured increase in leaf area, whereas potential leaf area growth is the estimated increase in leaf area if all potentially fertile tillers were to continue to develop. Procedures to predict this ratio, by estimating realized leaf area per plant from intercepted radiation and potential leaf area per plant from the number and type of developing axes, are presented. While it is suitable for modelling tiller dynamics in grain sorghum, this general framework needs to be validated by testing it in different environments and for other cultivars. (C) 2002 Annals of Botany Company.