Performance of a multi-level TDR system exposed to tropical field conditions - A time-space comparison with tensiometry

Time-domain reflectometry (TDR) is an important technique to obtain series of soil water content measurements in the field. Diode-segmented probes represent an improvement in TDR applicability, allowing measurements of the soil water content profile with a single probe. In this paper we explore an extensive soil water content dataset obtained by tensiometry and TDR from internal drainage experiments in two consecutive years in a tropical soil in Brazil. Comparisons between the variation patterns of the water content estimated by both methods exhibited evidences of deterioration of the TDR system during this two year period at field conditions. The results showed consistency in the variation pattern for the tensiometry data, whereas TDR estimates were inconsistent, with sensitivity decreasing over time. This suggests that difficulties may arise for the long-term use of this TDR system under tropical field conditions. (c) 2008 Elsevier B.V. All rights reserved.

Suitability of relative humidity as an estimator of leaf wetness duration

Leaf wetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates. Because LWD is not widely measured, several methods have been developed to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empirical models use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimate LWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained from Ames, IA (USA), Elora, Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sao Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH >= 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH >= 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH >= 90% model performed best, presenting the highest general fraction of correct estimates (F(C)), between 0.87 and 0.92, and the lowest false alarm ratio (F(AR)), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, even when independent data were used; MAE ranged from 1.23 to 1.89 h, which is very similar to errors obtained with published physical models for LWD estimation. Based on these results, we concluded that, if calibrated locally, LWD can be estimated with acceptable accuracy by RH above a specific threshold, and that the EXT_RH method was unsuitable for estimating LWD at the locations used in this study. (C) 2007 Elsevier B.V. All rights reserved.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Peach brown rot incidence related to pathogen infection at different stages of fruit development in an organic peach production system

Brown rot, caused by Monilinia fructicola, is the most widespread disease for organic peach production systems in Brazil. The objective of this study was to determine the favorable periods for latent infection by M. fructicola in organic systems. The field experiment was carried out during 2006, 2007 and 2008 using the cultivar Aurora. After thinning fruits were bagged using white paraffin bags, and the treatments were performed by removing the bags and exposing the fruit for four days to the natural infection during each of seven fruit stages from pit hardening to harvest. Throughout the entire growing season, the conidial density and the weather variables were measured and related to the disease incidence using multiple regression analyses. At the fourth day after harvest in each season, the cumulative disease incidence was assessed, and it ranged from 40 to 98%. The incidence of brown rot on fruit that were exposed during the embryo growing stage was lower than that of unbagged fruit throughout the entire season in 2006 and 2008. The relative humidity and the conidia density were significantly correlated to disease incidence. Based on our results, M. fructicola can infect peaches during any stage of fruit development, and control of the disease must be revised to account for organic peach production systems. (C) 2011 Elsevier Ltd. All rights reserved.

Atmospheric Absorption of Fluoride by Cultivated Species. Leaf Structural Changes and Plant Growth

Fluoride (F) is an air pollutant that causes phytotoxicity. Besides the importance of this, losses of agricultural crops in the vicinity of F polluting industries in Brazil have been recently reported. Injuries caused to plant leaf cell structures by excess F are not well characterized. However, this may contribute to understanding the ways in which plant physiological and biochemical processes are altered. A study evaluated the effects of the atmospheric F on leaf characteristics and growth of young trees of sweet orange and coffee exposed to low (0.04 mol L(-1)) or high (0.16 mol L(-1)) doses of HF nebulized in closed chamber for 28 days plus a control treatment not exposed. Gladiolus and ryegrass were used as bioindicators in the experiment to monitor F exposure levels. Fluoride concentration and dry mass of leaves were evaluated. Leaf anatomy was observed under light and electron microscopy. High F concentrations (similar to 180 mg kg(-1)) were found in leaves of plants exposed at the highest dose of HF. Visual symptoms of F toxicity in leaves of citrus and coffee were observed. Analyses of plant tissue provided evidence that F caused degeneration of cell wall and cytoplasm and disorganization of bundle sheath, which were more evident in Gladiolus and coffee. Minor changes were observed for sweet orange and ryegrass. Increase on individual stomatal area was also marked for the Gladiolus and coffee, and which were characterized by occurrence of opened ostioles. The increased F absorption by leaves and changes at the structural and ultrastructural level of leaf tissues correlated with reduced plant growth.

Evaluation of GFP Tag as a Screening Reporter in Directed Evolution of a Hyperthermophilic beta-Glucosidase

By applying a directed evolution methodology specific enzymatic characteristics can be enhanced, but to select mutants of interest from a large mutant bank, this approach requires high throughput screening and facile selection. To facilitate such primary screening of enhanced clones, an expression system was tested that uses a green fluorescent protein (GFP) tag from Aequorea victoria linked to the enzyme of interest. As GFP`s fluorescence is readily measured, and as there is a 1:1 molar correlation between the target protein and GFP, the concept proposed was to determine whether GFP could facilitate primary screening of error-prone PCR (EPP) clones. For this purpose a thermostable beta-glucosidase (BglA) from Fervidobacterium sp. was used as a model enzyme. A vector expressing the chimeric protein BglA-GFP-6XHis was constructed and the fusion protein purified and characterized. When compared to the native proteins, the components of the fusion displayed modified characteristics, such as enhanced GFP thermostability and a higher BglA optimum temperature. Clones carrying mutant BglA proteins obtained by EPP, were screened based on the BglA/GFP activity ratio. Purified tagged enzymes from selected clones resulted in modified substrate specificity.

A role for ferritin in the antioxidant system in coffee cell cultures

Iron (Fe) is an essential nutrient for plants, but it can generate oxidative stress at high concentrations. In this study, Coffea arabica L. cell suspension cultures were exposed to excess Fe (60 and 240 mu M) to investigate changes in the gene expression of ferritin and antioxidant enzymes. Iron content accumulated during cell growth, and Western blot analysis showed an increase of ferritin in cells treated with Fe. The expression of two ferritin genes retrieved from the Brazilian coffee EST database was studied. CaFER1, but not CaFER2, transcripts were induced by Fe exposure. Phylogenetic analysis revealed that CaFER1 is not similar to CaFER2 or to any ferritin that has been characterised in detail. The increase in ferritin gene expression was accompanied by an increase in the activity of antioxidant enzymes. Superoxide dismutase, guaiacol peroxidase, catalase, and glutathione reductase activities increased in cells grown in the presence of excess Fe, especially at 60 mu M, while the activity of glutathione S-transferase decreased. These data suggest that Fe induces oxidative stress in coffee cell suspension cultures and that ferritin participates in the antioxidant system to protect cells against oxidative damage. Thus, cellular Fe concentrations must be finely regulated to avoid cellular damage most likely caused by increased oxidative stress induced by Fe. However, transcriptional analyses indicate that ferritin genes are differentially controlled, as only CaFER1 expression was responsive to Fe treatment.

Seed development, yield and quality of two palm species growing in different tropical forest types in SE Brazil: implications for ecological restoration

Natural forest remnants have been set as seed production fields to supply seeds of native tree species for tropical forest restoration, but the effect of different forest types on seed production has not been accessed to date for palm species. In this work, we studied seed development, yield, and quality of two palm species in different tropical forest types in SE Brazil. Seed production of palmiteiro (Euterpe edulis) and queen-palm (Syagrus romanzoffiana), which are largely used in restoration efforts due to their importance for vertebrate frugivores, were studied in natural remnants of Atlantic Rainforest, Restinga Forest, Seasonally Dry Forest, and Cerrado Forest. We studied seed development, yield, size, and germination of seed lots produced in some of these forest types, including seeds harvested in 2008, 2009, and both years. Seed yield and quality, as well as seed dry mass in 2009, were higher for palmiteiro seeds produced in the Atlantic Rainforest, while queen-palm seeds produced at the Restinga Forest showed the higher mass and yield, but the lowest physiological potential. Consequently, these natural differences of seed yield and quality have to be taken into account for establishing standards for seed commercialization and analysis, seed pricing, and seedling production in forest nurseries.

Carbon and Nitrogen Dynamics in an Oxisol as Affected by Liming and Crop Residues under No-Till

The short-term effects of surface lime application and black oat (Avena strigosa Schreb.) residues, with or without N fertilization, were evaluated in a long-term no-till (NT) system on a sandy clay loam, a kaolinitic, thermic Typic Hapludox from the state of Parana, Brazil. The main plot treatments were: control and dolomitic lime applied on soil surface at 8 Mg ha(-1). Three treatments with crop residues were evaluated on the subplots: (i) fallow, (ii) black oat residues, and (iii) black oat residues aft er N fertilization at 180 kg ha(-1). Black oat dry biomass was not affected by the treatments during 3 yr. Surface liming increased soil pH, microbial biomass, microbial activity, and bacterial/fungal ratio at the soil surface (0-5 cm), resulting in increased amino acid turnover, water-soluble humic substances formation, and N mineralization and nitrification. While the application of black oat did increase the soil pH, overall it had much less effect on soil biological processes and C and N pools than did lime. We concluded that black oat cannot replace the need for lime to optimize crop production in these tropical NT systems. In the long term, however, black oat should aid in the amelioration of acidity and replenishment of soil organic C pools and should help reduce erosion. Overall, this study suggests that overapplication of inorganic fertilizer N may occur in some tropical NT systems. Further experiments are required in NT systems to investigate the use of slow-release N fertilizers in combination with lime and black oat as a mechanism to reduce acidification and promote sustainability.

Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

Reclaimed wastewater: Impact on soil-plant system under tropical conditions

This study investigated the ionic speciation of reclaimed urban wastewater (RWW), and the impact of increasing RWW irrigation rates on soil properties and plant nutrition under field conditions. Most RWW elements (>66%) are readily available as NH(4)(+), Ca(2+), Mg(2+), K(+), SO(4)(2-), Cl(-), H(3)BO(3), Mn(2+) and Zn(2+), but in imbalanced proportion for plant nutrition. Lead, Cd, Cr and Al in RWW are mostly bounded with DOM or OH. Irrigation with RWW decreased soil acidity, which is beneficial to the acidic tropical soil. Although RWW irrigation builds exchangeable Na(+) up, the excessive Na(+) was leached out of the soil profile after a rainy summer season (>400 mm). Benefits of the disposal of RWW to the soil under tropical conditions were discussed, however, the over irrigation with RWW (>100% of crop evapotranspiration) led to a nutritional imbalance, accumulating S and leading to a plant deficiency of P and K. (C) 2011 Elsevier B.V. All rights reserved.

Characterization of fungal soil communities by F-RISA and arbuscular mycorrhizal fungi from Araucaria angustifolia forest soils after replanting and wildfire disturbances

The Fungal Ribosomal Intergenic Spacer Analysis (F-RISA) was used to characterize soil fungal communities from three ecosystems of Araucaria angustifolia from Brazil: a native forest and two replanted forest ecosystems, one of them with a past history of wildfire. The arbuscular mycorrhizal fungi (AMF) infection was evaluated in Araucaria roots of 18-month-old axenic plants previously inoculated with soils collected from those areas in a greenhouse experiment. The principal component analysis of F-RISA profiles showed different soil fungal community between the three studied areas. Sixty three percent of F-RISA fragments amplified in the soil and the substrate samples presented lengths between 500 and 700 bp. The number of Operational Taxonomic Units (OTUs) was 34 for soil and 38 for substrate, however, more fragments were detected in soil (214) than in substrate (163). An in silico F-RISA analysis to compare our data with ITS1-5.8S-ITS2 sequences from NCBI database showed the presence of Ascomycota, Basidiomycota and Glomeromycota among the soil and substrate fungal communities. AMF infection was higher in plants inoculated with soil from the native forest and the replanted forest with wildfire, both presenting similar chemical characteristics but with different disturbance levels. These results indicate that soil chemical composition may influence the soil fungal community structures rather than the anthropogenic or fire disturbances.

Soil CO(2) emission estimated by different interpolation techniques

Soil CO(2) emissions are highly variable, both spatially and across time, with significant changes even during a one-day period. The objective of this study was to compare predictions of the diurnal soil CO(2) emissions in an agricultural field when estimated by ordinary kriging and sequential Gaussian simulation. The dataset consisted of 64 measurements taken in the morning and in the afternoon on bare soil in southern Brazil. The mean soil CO(2) emissions were significantly different between the morning (4.54 mu mol m(-2) s(-1)) and afternoon (6.24 mu mol m(-2) s(-1)) measurements. However, the spatial variability structures were similar, as the models were spherical and had close range values of 40.1 and 40.0 m for the morning and afternoon semivariograms. In both periods, the sequential Gaussian simulation maps were more efficient for the estimations of emission than ordinary kriging. We believe that sequential Gaussian simulation can improve estimations of soil CO(2) emissions in the field, as this property is usually highly non-Gaussian distributed.