Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Root Water Extraction under Combined Water and Osmotic Stress

Using a numerical implicit model for root water extraction by a single root in a symmetric radial flow problem, based on the Richards equation and the combined convection-dispersion equation, we investigated some aspects of the response of root water uptake to combined water and osmotic stress. The model implicitly incorporates the effect of simultaneous pressure head and osmotic head on root water uptake, and does not require additional assumptions (additive or multiplicative) to derive the combined effect of water and salt stress. Simulation results showed that relative transpiration equals relative matric flux potential, which is defined as the matric flux potential calculated with an osmotic pressure head-dependent lower bound of integration, divided by the matric flux potential at the onset of limiting hydraulic conditions. In the falling rate phase, the osmotic head near the root surface was shown to increase in time due to decreasing root water extraction rates, causing a more gradual decline of relative transpiration than with water stress alone. Results furthermore show that osmotic stress effects on uptake depend on pressure head or water content, allowing a refinement of the approach in which fixed reduction factors based on the electrical conductivity of the saturated soil solution extract are used. One of the consequences is that osmotic stress is predicted to occur in situations not predicted by the saturation extract analysis approach. It is also shown that this way of combining salinity and water as stressors yields results that are different from a purely multiplicative approach. An analytical steady state solution is presented to calculate the solute content at the root surface, and compared with the outputs of the numerical model. Using the analytical solution, a method has been developed to estimate relative transpiration as a function of system parameters, which are often already used in vadose zone models: potential transpiration rate, root length density, minimum root surface pressure head, and soil theta-h and K-h functions.

Macroscopic root water uptake distribution using a matric flux potential approach

Hydrological models featuring root water uptake usually do not include compensation mechanisms such that reductions in uptake from dry layers are compensated by an increase in uptake from wetter layers. We developed a physically based root water uptake model with an implicit compensation mechanism. Based on an expression for the matric flux potential (M) as a function of the distance to the root, and assuming a depth-independent value of M at the root surface, uptake per layer is shown to be a function of layer bulk M, root surface M, and a weighting factor that depends on root length density and root radius. Actual transpiration can be calculated from the sum of layer uptake rates. The proposed reduction function (PRF) was built into the SWAP model, and predictions were compared to those made with the Feddes reduction function (FRF). Simulation results were tested against data from Canada (continuous spring wheat [(Triticum aestivum L.]) and Germany (spring wheat, winter barley [Hordeum vulgare L.], sugarbeet [Beta vulgaris L.], winter wheat rotation). For the Canadian data, the root mean square error of prediction (RMSEP) for water content in the upper soil layers was very similar for FRF and PRF; for the deeper layers, RMSEP was smaller for PRF. For the German data, RMSEP was lower for PRF in the upper layers and was similar for both models in the deeper layers. In conclusion, but dependent on the properties of the data sets available for testing,the incorporation of the new reduction function into SWAP was successful, providing new capabilities for simulating compensated root water uptake without increasing the number of input parameters or degrading model performance.

Flow rate sprinkler development for site-specific irrigation

Due to the rapid depletion of water resources, water must be used more efficiently in agriculture to maintain current levels of yield in irrigated areas. The efficiency of irrigation systems can be increased by adjusting the amount of water applied to specific conditions of soil and crop, which may vary in a field. Taking into account spatial and temporal variability, it is evident that an equipment capable of providing different irrigation levels is necessary to meet the water requirement of the soil. This work aims to develop and evaluate a flow rate sprinkler to be used in center pivots or linear moving irrigation systems, with potential for utilization in irrigation scheduling. A prototype was developed by duplicating its calibrations, and discharge coefficient adjustment was carried out in the laboratory. To predict the flow rate, a successful model that represented the operation of the flow rate sprinkler was established. The calibration of the flow rate sprinkler prototype showed satisfactory statistical and technical results. Automation of the prototype was achieved by driving a step motor using communication from the parallel port of a microcomputer, which was controlled by a software developed for this purpose. The results were satisfactory and technically feasible.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

The relationship of flow cytometry results with classical measures of bacterial counts in raw refrigerated milk

Bulk milk was collected from 100 farms throughout the year and analysed after storage for either 24, 48 or 72 h, using flow cytometry. The total bacterial counts obtained by two methods - flow cytometry and standard plate count were compared and the conversion relationship between them was assessed: the results showed no effect of the age of the samples relationship between these two methods.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Multiphase flow in the vascular system of wood: From microscopic exploration to 3-D Lattice Boltzmann experiments

This paper provides insights into liquid free water dynamics in wood vessels based on Lattice Boltzmann experiments. The anatomy of real wood samples was reconstructed from systematic 3-D analyses of the vessel contours derived from successive microscopic images. This virtual vascular system was then used to supply fluid-solid boundary conditions to a two-phase Lattice Boltzmann scheme and investigate capillary invasion of this hydrophilic porous medium. Behavior of the liquid phase was strongly dependent on anatomical features, especially vessel bifurcations and reconnections. Various parameters were examined in numerical experiments with ideal vessel bifurcations, to clarify our interpretation of these features. (c) 2010 Elsevier Ltd. All rights reserved.

Large-scale ecological restoration of high-diversity tropical forests in SE Brazil

The complex interactions among endangered ecosystems, landowners` interests, and different models of land tenure and use, constitute an important series of challenges for those seeking to maintain and restore biodiversity and augment the flow of ecosystem services. Over the past 10 years, we have developed a data-based approach to address these challenges and to achieve medium and large-scale ecological restoration of riparian areas on private lands in the state of Sao Paulo, southeastern Brazil. Given varying motivations for ecological restoration, the location of riparian areas within landholdings, environmental zoning of different riparian areas, and best-practice restoration methods were developed for each situation. A total of 32 ongoing projects, covering 527,982 ha, were evaluated in large sugarcane farms and small mixed farms, and six different restoration techniques have been developed to help upscale the effort. Small mixed farms had higher portions of land requiring protection as riparian areas (13.3%), and lower forest cover of riparian areas (18.3%), than large sugarcane farms (10.0% and 36.9%, respectively for riparian areas and forest cover values). In both types of farms, forest fragments required some degree of restoration. Historical anthropogenic degradation has compromised forest ecosystem structure and functioning, despite their high-diversity of native tree and shrub species. Notably, land use patterns in riparian areas differed markedly. Large sugarcane farms had higher portions of riparian areas occupied by highly mechanized agriculture, abandoned fields, and anthropogenic wet fields created by siltation in water courses. In contrast, in small mixed crop farms, low or non-mechanized agriculture and pasturelands were predominant. Despite these differences, plantations of native tree species covering the entire area was by far the main restoration method needed both by large sugarcane farms (76.0%) and small mixed farms (92.4%), in view of the low resilience of target sites, reduced forest cover, and high fragmentation, all of which limit the potential for autogenic restoration. We propose that plantations should be carried out with a high-diversity of native species in order to create biologically viable restored forests, and to assist long-term biodiversity persistence at the landscape scale. Finally, we propose strategies to integrate the political, socio-economic and methodological aspects needed to upscale restoration efforts in tropical forest regions throughout Latin America and elsewhere. (C) 2010 Elsevier BA/. All rights reserved.

EVALUATION OF RED CURRANTS (RIBES RUBRUM L.), BLACK CURRANTS (RIBES NIGRUM L.), RED AND GREEN GOOSEBERRIES (RIBES UVA-CRISPA) FOR POTENTIAL MANAGEMENT OF TYPE 2 DIABETES AND HYPERTENSION USING IN VITRO MODELS

Red currants (Ribes rubrum L.), black currants (Ribes nigrum L.), red and green gooseberries (Ribes uva-crispa) were evaluated for the total phenolics, antioxidant capacity based on 2, 2-diphenyl-1-picrylhydrazyl radical scavenging assay and functionality such as in vitro inhibition of alpha-amylase, alpha-glucosidase and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. The total phenolics content ranged from 3.2 (green gooseberries) to 13.5 (black currants) mg/g fruit fresh weight. No correlation was found between total phenolics and antioxidant activity. The major phenolic compounds were quercetin derivatives (black currants and green gooseberries) and chlorogenic acid (red currants and red gooseberries). Red currants had the highest alpha-glucosidase, alpha-amylase and ACE inhibitory activities. Therefore red currants could be good dietary sources with potential antidiabetes and antihypertension functionality to compliment overall dietary management of early stages of type 2 diabetes.

Potential of Ginkgo biloba L. leaves in the management of hyperglycemia and hypertension using in vitro models

Leaves from four different Ginkgo biloba L. trees (1 and 2 - females; 3 and 4 - males), grown at the same conditions, were collected during a period of 5 months (from June to October, 2007). Water and 12% ethanol extracts were analyzed for total phenolics content, antioxidant activity, phenolic profile, and the potential in vitro inhibitory effects on alpha-amylase, alpha-glucosidase, and Angiotensin I-Converting Enzyme (ACE) enzymes related to the management of diabetes and hypertension. The results indicated a significant difference among the trees in all functional benefits evaluated in the leaf extracts and also found important seasonal variation related to the same functional parameters. In general, the aqueous extracts had higher total phenolic content than the ethanolic extracts. Also, no correlation was found between total phenolics and antioxidant activity. In relation to the ACE inhibition, only ethanolic extracts had inhibitory activity. (C) 2009 Elsevier Ltd. All rights reserved.

Functionality of bioactive compounds in Brazilian strawberry (Fragaria x ananassa Duch.) cultivars: Evaluation of hyperglycemia and hypertension potential using in vitro models

Fruits of seven fully ripened strawberry cultivars grown in Brazil (Dover, Camp Dover, Camarosa, Sweet Charlie, Toyonoka, Oso Grande, and Piedade) were evaluated for total phenolics, antioxidant activity based on DPPH radical scavenging assay, and functionality such as inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potentially managing hyperglycemia and hypertension. The total phenolics content ranged from 966 to 1571 mu g of gallic acid/g of fruit fresh weight for Toyonoka and Dover, respectively. No correlation was found between total phenolics and antioxidant activity. The major phenolic compounds in aqueous extracts of strawberries were ellagic acid, quercetin, and chlorogenic acid. Strawberries had high alpha-glucosidase inhibitory activity. However, alpha-amylase inhibitory activity was very low in all cultivars. This suggested that strawberries could be considered as a potential dietary source with anti-hyperglycemic potential. The evaluated cultivars had no significant ACE inhibitory activity, reflecting low anti-hypertensive potential.

Two physically, functionally, and developmentally distinct peritoneal macrophage subsets

The peritoneal cavity (PerC) is a unique compartment within which a variety of immune cells reside, and from which macrophages (Mempty set) are commonly drawn for functional studies. Here we define two Mempty set subsets that coexist in PerC in adult mice. One, provisionally called the large peritoneal Mempty set (LPM), contains approximately 90% of the PerC Mempty set in unstimulated animals but disappears rapidly from PerC following lipopolysaccharide (LPS) or thioglycolate stimulation. These cells express high levels of the canonical Mempty set surface markers, CD11b and F4/80. The second subset, referred to as small peritoneal Mempty set (SPM), expresses substantially lower levels of CD11b and F4/80 but expresses high levels of MHC-II, which is not expressed on LPM. SPM, which predominates in PerC after LPS or thioglycolate stimulation, does not derive from LPM. Instead, it derives from blood monocytes that rapidly enter the PerC after stimulation and differentiate to mature SPM within 2 to 4 d. Both subsets show clear phagocytic activity and both produce nitric oxide (NO) in response to LPS stimulation in vivo. However, their responses to LPS show key differences: in vitro, LPS stimulates LPM, but not SPM, to produce NO; in vivo, LPS stimulates both subsets to produce NO, albeit with different response patterns. These findings extend current models of Mempty set heterogeneity and shed new light on PerC Mempty set diversity, development, and function. Thus, they introduce a new context for interpreting (and reinterpreting) data from ex vivo studies with PerC Mempty set.