Cultivares de batata para sistemas orgânicos de produção

Informações a respeito de cultivares adaptadas ao sistema de cultivo orgânico são escassas. O objetivo deste estudo foi avaliar, sob sistema de cultivo orgânico, genótipos nacionais e estrangeiros desenvolvidos para o cultivo convencional, quanto ao potencial produtivo, em condições de campo. O experimento foi conduzido em 2008, no Pólo APTA Leste Paulista, em Monte Alegre do Sul-SP. O delineamento experimental foi em blocos ao acaso, com 18 tratamentos e quatro repetições. Cada parcela foi constituída por 80 batatas-semente, dispostas em quatro linhas de 5 m de comprimento, espaçadas de 80 cm, com 25 cm entre tubérculos. Os genótipos avaliados foram Agata, Asterix, Caesar, Cupido, Éden, Melody, Novella e Vivaldi, de origem estrangeira; e Apuã, Aracy, Catucha, IAC Aracy Ruiva, Itararé, Monte Alegre 172, IAC 6090, APTA 16.5, APTA 15.20 e APTA 21.54, nacionais. Foram avaliadas as características de produtividade total e comercial de tubérculos, massa média total e comercial de tubérculos, teor de matéria seca e severidade da pinta-preta (Alternaria solani). Os clones APTA 16.5, APTA 21.54 e IAC 6090, e as cultivares Cupido, Apuã, Itararé e Monte Alegre 172 foram os mais produtivos. 'APTA 21.54' superou os demais em relação a produtividade comercial (18,07 t ha-1), sendo que 'APTA 16.5', 'Cupido', 'IAC 6090' e 'Itararé' formaram o segundo grupo. As maiores massas médias de tubérculos foram apresentadas pelas cultivares Itararé e Cupido. O clone IAC 6090 e as cultivares Aracy e Aracy Ruiva foram as que apresentaram maiores teores de matéria seca, com valor médio de 22,91%. 'APTA 16.5', 'Apuã', 'Aracy', 'Aracy Ruiva', 'Éden', 'Ibituaçú' e 'Monte Alegre 172' apresentaram alto nível de resistência à pinta-preta. As cultivares Itararé, Apuã e Cupido são adaptadas ao cultivo orgânico, e os clones avançados APTA 16.5, APTA 21.54 e IAC 6090 apresentam potencial de cultivo no sistema orgânico.

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.

Genetic diversity of turmeric germplasm (Curcuma longa; Zingiberaceae) identified by microsatellite markers

Turmeric (Curcuma longa) is a triploid, vegetatively propagated crop introduced early during the colonization of Brazil. Turmeric rhizomes are ground into a powder used as a natural dye in the food industry, although recent research suggests a greater potential for the development of drugs and cosmetics. In Brazil, little is known about the genetic variability available for crop improvement. We examined the genetic diversity among turmeric accessions from a Brazilian germplasm collection comprising 39 accessions collected from the States of Goias, Mato Grosso do Sul, Minas Gerais, Sao Paulo, and Para. For comparison, 18 additional genotypes were analyzed, including samples from India and Puerto Rico. Total DNA was extracted from lyophilized leaf tissue and genetic analysis was performed using 17 microsatellite markers (single-sequence repeats). Shannon-Weiner indexes ranged from 0.017 (Minas Gerais) to 0.316 (Sao Paulo). Analyses of molecular variance (AMOVA) demonstrated major differences between countries (63.4%) and that most of the genetic diversity in Brazil is found within states (75.3%). Genotypes from Sao Paulo State were the most divergent and potentially useful for crop improvement. Structure analysis indicated two main groups of accessions. These results can help target future collecting efforts for introduction of new materials needed to develop more productive and better adapted cultivars.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Economic viability of doses and split-applications of nitrogen fertilization in corn crop in a eutrophic Red Latosol

Nitrogen is the nutrient that is most absorbed by the corn crop, with the most complex management, and has the highest share on the cost of corn production. The objective of this work was to evaluate the economic viability of different rates and split-applications of nitrogen fertilization, as such as urea, in the corn crop in a eutrophic Red Latosol (Oxisol). The study was carried out in the Experimental Station of the Regional Pole of the Sao Paulo Northwest Agribusiness Development (APTA), in Votuporanga, State of Sao Paulo, Brazil. The experimental design was randomized complete blocks with nine treatments and four replications, consisting of five N rates: 0, 55, 95, 135 and 175 kg ha(-1), 15 kg ha-l applied in the seeding and the remainder in top dressing: 40 and 80 kg ha(-1) N at forty days after seeding (DAS), or 1/2 + 1/2 at 20 and 40 DAS; 120 kg ha-1 N split in 1/2 + 1/2 or 1/3 + 1/3 + 1/3 at 20, 40 or 60 DAS; 160 kg ha(-1) N split in 1/4 + 3/8 + 3/8 or 114 + 1/4 + 1/4 + 1/4 at 20, 40, 60 and 80 DAS. The application of 135 kg ha-l of N split in three times provided the best benefit/cost ratio. The non-application of N provided the lowest economic return, proving to be unviable.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Cyclone washer adapted from an American-type cyclone separator

A modified cyclone washer was designed, fabricated, and its collection efficiency evaluated. This equipment consists of an American-type cyclone separator with a triple cone and a spray nozzle was introduced into its cylindrical body. The study consisted of an experimental evaluation of the operating conditions at ambient and higher than ambient temperatures, varying chimney height and water flow rate, with the purpose of humidifying the dust. The collection efficiency of the cyclone washer was evaluated particles of micronized quartz with an average diameter of 7.48 mu m and a density of 2.650 g/cm(3). The amount of particles varied from 20-100 mg/m(3) of air. An average efficiency of 97.07 +/- 1.03 % was obtained with four spray nozzles, a chimney height of 0.645 m and 0.358 m(3)/s of gas.

Leaching of nutrients from a sugarcane crop growing on an Ultisol in Brazil

Leaching is disadvantageous, both for economical and environmental reasons since it may decrease the ecosystem productivity and may also contribute to the contamination of surface and ground water. The objective of this paper was to quantify the loss of nitrogen and sulfur by leaching, at the depth of 0.9 m, in an Ultisol in Sao Paulo State (Brazil) with high permeability, Cultivated with sugarcane during the agricultural cycle of crop plant. The following ions were evaluated: nitrite, nitrate, ammonium, and sulfate. Calcium, magnesium, potassium, and phosphate were also evaluated at the same depth. The sugarcane was planted and fertilized in the furrows with 120 log ha(-1) of N-urea. In order to find out the fate of N-fertilizer, four microplots with (15)N-enriched fertilizer were installed. Input and output of the considered ions at the depth of 0.9 m were quantified from the flux density of water and the concentration of the elements in the soil solution at this soil depth: tensiometers, soil water retention curve and soil solution extractors were used for this quantification. The internal drainage was 205 mm of water, with a total loss of 18 kg ha(-1) of N and 10 kg ha(-1) of S. The percentage of N in the soil solution derived from the fertilizer (%NSSDF) was 1.34, resulting in only 25 g ha(-1) of N fertilizer loss by leaching during all agricultural cycle. Under the experimental conditions of this crop plant, that is, high demand of nutrients and high incorporation of crop residues, the leached N represented 15% of applied N and S leaching were not considerable; the higher amount of leached N was native nitrogen and a minor quantity from N fertilizer; and the leached amount of Ca, Mg, K and P did not exceed the applications performed in the crop by lime and fertilization. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

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.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation A field study conducted over three consecutive years, on a farm using crop rotation system under center-pivot and infested with the nematodes Pratylenchus brachyurus, P. zeae, Meloidogyne incognita, Paratrichodorus minor, Helicotylenchus dihystera, Mesocriconema ornata and M. onoense, demonstrated that intensive crop systems provide conditions for the maintenance of high densities of polyphagous phytonematodes. Of the crops established on the farm (cotton, maize, soybean and cowpea), cotton and soybean suffered the most severe crop losses, caused respectively by M. incognita and P. brachyurus. Since maize is a good host for both nematodes, but tolerant of M. incognita, its exclusion from cropping system would be favorable to the performance of cotton, soybean and cowpea. Results from experiments carried out in controlled conditions confirmed the pathogenicity of P. brachyurus on cotton. Additional management with genetic resistance was useful in fields infested with M. incognita, although the soybean performance was affected by low resistance of the cultivars used for P. brachyurus. In conclusion, crop rotation must be carefully planned in areas infested with polyphagous nematodes, specifically in the case of occurrence of two or more major pathogenic nematodes.

Water use and crop coefficient for hybrid DKB 390

Water use and crop coefficient for hybrid DKB 390. This work aims to characterize the water use of maize hybrid DKB 390 under suitable conditions of irrigation for both sufficient and below-optimal situations of nitrogen supply. Crop coefficient values for different stages are also presented as a result, in order to provide the basis for crop water budget and management throughout the cycle. A field experiment was carried Out during the main season, in which biomass, soil moisture, leaf area, climate data and light transmittance were evaluated. These have allowed deriving water balance, use and efficiency. The mentioned genotype requires around 600 nun for high yield targets, being less efficient when led under below-optimal nitrogen fertilization.

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.

Chemical composition of whole body and carcass of Bos indicus and tropically adapted Bos taurus breeds

Relationships between the chemical composition of the 9th- to 11th-rib section and the chemical composition of the carcass and empty body were evaluated for Bos indicus (108 Nellore and 36 Guzerah; GuS) and tropically adapted Bos taurus (56 Caracu; CaS) bulls, averaging 20 to 24 mo of age at slaughter. Nellore cattle were represented by 56 animals from the selected herd (NeS) and 52 animals from the control herd (NeC). The CaS and GuS bulls were from selected herds. Selected herds were based on 20 yr of selection for postweaning BW. Carcass composition was obtained after grinding, homogenizing, sampling, and analyzing soft tissue and bones. Similarly, empty body composition was obtained after grinding, homogenizing, sampling, analyzing, and combining blood, hide, head + feet, viscera, and carcass. Bulls were separated into 2 groups. Group 1 was composed of 36 NeS, 36 NeC, 36 CaS, and 36 GuS bulls and had water, ether extract (EE), protein, and ash chemically determined in the 9th- to 11th-rib section and in the carcass. Group 2 was composed of 20 NeS, 16 NeC, and 20 CaS bulls and water, EE, protein, and ash were determined in the 9th-to 11th-rib section, carcass, and empty body. Linear regressions were developed between the carcass and the 9th-to 11th-rib section compositions for group 1 and between carcass and empty body compositions for group 2. The 9th-to 11th-rib section percentages of water (RWt) and EE (RF) predicted the percentages of carcass water (CWt) and carcass fat (CF) with high precision: CWt, % = 29.0806 + 0.4873 x RWt, % (r(2) = 0.813, SE = 1.06) and CF, % = 10.4037 + 0.5179 x RF, % (r(2) = 0.863, SE = 1.26), respectively. Linear regressions between percentage of CWt and CF and empty body water (EBWt) and empty body fat (EBF) were also predicted with high precision: EBWt, % = -9.6821 + 1.1626 x CWt, % (r(2) = 0.878, SE = 1.43) and EBF, % = 0.3739 + 1.0386 x CF, % (r(2) = 0.982, SE = 0.65), respectively. Chemical composition of the 9th-to 11th-rib section precisely estimated carcass percentages of water and EE. These regressions can accurately predict carcass and empty body compositions for Nellore, Guzerah, and Caracu breeds.