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.

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.

Impacts of climate changes on crop physiology and food quality

Carbon emissions related to human activities have been significantly contributing to the elevation of atmospheric [CO(2)] and temperature. More recently, carbon emissions have greatly accelerated, thus much stronger effects on crops are expected. Here, we revise literature data concerning the physiological effects of CO(2) enrichment and temperature rise on crop species. We discuss the main advantages and limitations of the most used CO(2)-enrichment technologies, the Open-Top Chambers (OTCs) and the Free-Air Carbon Enrichment (FACE). Within the conditions expected for the next few years, the physiological responses of crops suggest that they will grow faster, with slight changes in development, such as flowering and fruiting, depending on the species. There is growing evidence suggesting that C(3) crops are likely to produce more harvestable products and that both C(3) and C(4) crops are likely to use less water with rising atmospheric [CO(2)] in the absence of stressful conditions. However, the beneficial direct impact of elevated [CO(2)] on crop yield can be offset by other effects of climate change, such as elevated temperatures and altered patterns of precipitation. Changes in food quality in a warmer, high-CO(2) world are to be expected, e.g., decreased protein and mineral nutrient concentrations, as well as altered lipid composition. We point out that studies related to changes in crop yield and food quality as a consequence of global climatic changes should be priority areas for further studies, particularly because they will be increasingly associated with food security. (c) 2009 Elsevier Ltd. All rights reserved.

The Relationship between Population Structure and Aluminum Tolerance in Cultivated Sorghum

Background: Acid soils comprise up to 50% of the world's arable lands and in these areas aluminum (Al) toxicity impairs root growth, strongly limiting crop yield. Food security is thereby compromised in many developing countries located in tropical and subtropical regions worldwide. In sorghum, SbMATE, an Al-activated citrate transporter, underlies the Alt(SB) locus on chromosome 3 and confers Al tolerance via Al-activated root citrate release. Methodology: Population structure was studied in 254 sorghum accessions representative of the diversity present in cultivated sorghums. Al tolerance was assessed as the degree of root growth inhibition in nutrient solution containing Al. A genetic analysis based on markers flanking Alt(SB) and SbMATE expression was undertaken to assess a possible role for Alt(SB) in Al tolerant accessions. In addition, the mode of gene action was estimated concerning the Al tolerance trait. Comparisons between models that include population structure were applied to assess the importance of each subpopulation to Al tolerance. Conclusion/Significance: Six subpopulations were revealed featuring specific racial and geographic origins. Al tolerance was found to be rather rare and present primarily in guinea and to lesser extent in caudatum subpopulations. Alt(SB) was found to play a role in Al tolerance in most of the Al tolerant accessions. A striking variation was observed in the mode of gene action for the Al tolerance trait, which ranged from almost complete recessivity to near complete dominance, with a higher frequency of partially recessive sources of Al tolerance. A possible interpretation of our results concerning the origin and evolution of Al tolerance in cultivated sorghum is discussed. This study demonstrates the importance of deeply exploring the crop diversity reservoir both for a comprehensive view of the dynamics underlying the distribution and function of Al tolerance genes and to design efficient molecular breeding strategies aimed at enhancing Al tolerance.

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.

Benzylglucosinolate, Benzylisothiocyanate, and Myrosinase Activity in Papaya Fruit during Development and Ripening

Papaya is a climacteric fruit that has high amounts of benzylglucosinolates (BG) and benzylisothiocyanates (BITC), but information regarding levels of BG or BITC during fruit development and ripening is limited. Because BG and BITC are compounds of importance from both a nutritional and a crop yield standpoint, the aim of this work was to access data on the distribution and changes of BG and BITC levels during fruit development and ripening. BG and BITC levels were quantified in peel, pulp, and seeds of papaya fruit. Volatile BITC was also verified in the internal cavity of the fruit during ripening. The influence of the ethylene in BG and BITC levels and mirosinase activity was tested by exposing mature green fruits to ethylene and 1-methylcyclopropene (1-MCP). The highest BG levels were detected in seeds, followed by the peel and pulp being decreased in all tissues during fruit development. Similarly, the levels of BITC were much higher in the seeds than the peel and pulp. The levels of BG for control and ethylene-treated fruit were very similar, increasing in the pulp and peel during late ripening but not changing significantly in seeds. On the other hand, fruit exposed to 1-MCP showed a decrease in BG amount in the pulp and accumulation in seed. The treatments did not result in clear differences regarding the amount of BITC in the pulp and peel of the fruit. According to the results, ethylene does not have a clear effect on BITC accumulation in ripening papaya fruit. The fact that BG levels in the pulp did not decrease during ripening, regardless of the treatment employed, and that papaya is consumed mainly as fresh fruit, speaks in favor of this fruit as a good dietary source for glucosinolate and isothiocyanates.

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

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.

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.

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.

The impact of El Nino Southern Oscillation phases on off-season maize yield for a subtropical region of Brazil

In recent years, maize has become one of the main alternative crops for the autumn winter growing season in the central-western and southeastern regions of Brazil. However, water deficits, sub-optimal temperatures and low solar radiation levels are common problems that are experienced during this growing season by local farmers. One methodology to assess the impact of variable weather conditions on crop production is the use of crop simulation models. The goal of this study was to evaluate the effect of climate variability on maize yield for a subtropical region of Brazil. Specific objectives for this study were (1) to analyse the effect of El Nino Southern Oscillation (ENSO) on precipitation and air temperature for four locations in the state of Sao Paulo and (2) to analyse the impact of ENSO on maize grown off-season for the same four locations using a crop simulation model. For each site, historical weather data were categorised as belonging to one of three phases of ENSO: El Nino (warm sea surface temperature anomalies in the Pacific), La Nina (cool sea surface temperature anomalies) or neutral, based on an index derived from observed sea surface temperature anomalies. During El Nino, there is a tendency for an increase in the rainfall amount during May for the four selected locations, and also during April, mainly in three of the locations, resulting in an increase in simulated maize yield planted between February 15 and March 15. In general, there was a decrease in the simulated yield for maize grown off-season during neutral years. This study showed how a crop model can be used to assess the impact of climate variability on the yield of maize grown off-season in a subtropical region of Brazil. The outcomes of this study can be very useful for both policy makers and local farmers for agricultural planning and decision making. Copyright (C) 2009 Royal Meteorological Society

Yield loss caused by huanglongbing in different sweet orange cultivars in So Paulo, Brazil

Citrus huanglongbing (HLB) reduces an affected orchard`s economic life. This work aimed to characterize yield loss due to HLB for different sweet orange cultivars and determine the relationship between disease severity and yield. Disease severity and yield were assessed on 949 individual trees distributed in 11 different blocks from sweet orange cultivars Hamlin, Westin, Pera and Valencia. In each block, plants showing a range of HLB severity levels and asymptomatic plants were selected. Total yield (weight of harvested fruit), mean weight of asymptomatic and symptomatic fruit, relative yield (symptomatic tree yield/mean yield of asymptomatic trees from the same block) and relative number of fruits (fruit number from symptomatic tree/mean number of fruits from asymptomatic trees from the same block) were determined. The weight of symptomatic fruit was lower than the weight of asymptomatic fruit, but the weights of asymptomatic and symptomatic fruit were not correlated with disease severity, indicating that the effects of HLB were restricted to symptomatic branches. The relationship of the relative yield with HLB severity can be satisfactorily described by a negative exponential model. The rates of yield decrease as a function of disease severity were similar for all assessed cultivars. A relative yield (up to 19%) was observed even for trees where disease severity was 100%. The strong linear relationship between relative number of fruits per tree and the relative yield per tree suggested that the yield reduction was due primarily to early fruit drop or lack of fruit set on affected branches.

Analysis of genomic and functional RFLP derived markers associated with sucrose content, fiber and yield QTLs in a sugarcane (Saccharum spp.) commercial cross

Expressed sequence tags derived markers have a great potential to be used in functional map construction and QTL tagging. In the present work, sugarcane genomic probes and expressed sequence tags having homology to genes, mostly involved in carbohydrate metabolism were used in RFLP assays to identify putative QTLs as well as their epistatic interactions for fiber content, cane yield, pol and tones of sugar per hectare, at two crop cycles in a progeny derived from a bi-parental cross of sugarcane elite materials. A hundred and twenty marker trait associations were found, of which 26 at both crop cycle and 32 only at first ratoon cane. A sucrose synthase derived marker was associated with a putative QTL having a high negative effect on cane yield and also with a QTL having a positive effect on Pol at both crop cycles. Fifty digenic epistatic marker interactions were identified for the four traits evaluated. Of these, only two were observed at both crop cycles.

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.

Genomic Analysis of Wild Tomato Introgressions Determining Metabolism- and Yield-Associated Traits

With the aim of determining the genetic basis of metabolic regulation in tomato fruit, we constructed a detailed physical map of genomic regions spanning previously described metabolic quantitative trait loci of a Solanum pennellii introgression line population. Two genomic libraries from S. pennellii were screened with 104 colocated markers from five selected genomic regions, and a total of 614 bacterial artificial chromosome (BAC)/cosmids were identified as seed clones. Integration of sequence data with the genetic and physical maps of Solanum lycopersicum facilitated the anchoring of 374 of these BAC/cosmid clones. The analysis of this information resulted in a genome-wide map of a nondomesticated plant species and covers 10% of the physical distance of the selected regions corresponding to approximately 1% of the wild tomato genome. Comparative analyses revealed that S. pennellii and domesticated tomato genomes can be considered as largely colinear. A total of 1,238,705 bp from both BAC/cosmid ends and nine large insert clones were sequenced, annotated, and functionally categorized. The sequence data allowed the evaluation of the level of polymorphism between the wild and cultivated tomato species. An exhaustive microsynteny analysis allowed us to estimate the divergence date of S. pennellii and S. lycopersicum at 2.7 million years ago. The combined results serve as a reference for comparative studies both at the macrosyntenic and microsyntenic levels. They also provide a valuable tool for fine-mapping of quantitative trait loci in tomato. Furthermore, they will contribute to a deeper understanding of the regulatory factors underpinning metabolism and hence defining crop chemical composition.