Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Use of a crop model ensemble to quantify CO2 stimulation of water-stressed and well-watered crops

Increased atmospheric concentrations of carbon dioxide (CO2) will benefit the yield of most crops. Two free air CO2 enrichment (FACE) meta-analyses have shown increases in yield of between 0 and 73% for C3 crops. Despite this large range, few crop modelling studies quantify the uncertainty inherent in the parameterisation of crop growth and development. We present a novel perturbed-parameter method of crop model simulation, which uses some constraints from observations, that does this. The model used is the groundnut (i.e. peanut; Arachis hypogaea L.) version of the general large-area model for annual crops (GLAM). The conclusions are of relevance to C3 crops in general. The increases in yield simulated by GLAM for doubled CO2 were between 16 and 62%. The difference in mean percentage increase between well-watered and water-stressed simulations was 6.8. These results were compared to FACE and controlled environment studies, and to sensitivity tests on two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., Bell, M.J., 1995. A peanut simulation model. I. Model development and testing. Agron. J. 87, 1085-1093]. The relationship between CO2 and water stress in the experiments and in the models was examined. From a physiological perspective, water-stressed crops are expected to show greater CO2 stimulation than well-watered crops. This expectation has been cited in literature. However, this result is not seen consistently in either the FACE studies or in the crop models. In contrast, leaf-level models of assimilation do consistently show this result. An analysis of the evidence from these models and from the data suggests that scale (canopy versus leaf), model calibration, and model complexity are factors in determining the sign and magnitude of the interaction between CO2 and water stress. We conclude from our study that the statement that 'water-stressed crops show greater CO2 stimulation than well-watered crops' cannot be held to be universally true. We also conclude, preliminarily, that the relationship between water stress and assimilation varies with scale. Accordingly, we provide some suggestions on how studies of a similar nature, using crop models of a range of complexity, could contribute further to understanding the roles of model calibration, model complexity and scale. (C) 2008 Elsevier B.V. All rights reserved.

Adaptation of crops to climate change through genotypic responses to mean and extreme temperatures

The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Diversity of cultivars and other plant resources used at habitation sites in the Llanos de Mojos, Beni, Bolivia: Evidence from macrobotanical remains, starch grains, and phytoliths

Although sparsely populated today, the Llanos de Mojos, Bolivia, sustained large sedentary societies in the Late Holocene (ca. 500 to 1400 AD). In order to gain insight into the subsistence of these people, we undertook macrobotanical and phytolith analyses of sediment samples, and starch grain and phytolith analyses of artifact residues, from four large habitation sites within this region. Macrobotanical remains show the presence of maize (Zea mays), squash (Cucurbita sp.), peanut (Arachis hypogaea), cotton (Gossypium sp.), and palm fruits (Arecaceae). Microbotanical results confirm the widespread use of maize at all sites, along with manioc (Manihot esculenta), squash, and yam (Dioscorea sp.). These integrated results present the first comprehensive archaeobotanical evidence of the diversity of plants cultivated, processed, and consumed, by the pre-Hispanic inhabitants of the Amazonian lowlands of Bolivia.

Efeito sacietogênico de um novo inibidor de tripsina da paçoca do amendoim com aumento plasmático de colecistocinina (cck)

Obesity is increasing, reaching epidemic levels in many regions of the world. Studies have shown that consumption of peanuts influences on weight control and this influence may be due to the action of trypsin inhibitors sacietogênica that condition increased plasma colescistocinina (CCK). Moreover, the peanut has other health benefits, and these assignments are guaranteed to increase their production and consumption of several of its products, including the paçoca peanut. The aim of this study was to identify the presence of a trypsin inhibitor in paçoca peanut and evaluate its effect on food intake, weight gain and histomorphological changes in swiss mice (n = 8) and Wistar rats (n = 6). Experimental diets were prepared based on the AIN-93G and supplemented with tack or peanut trypsin inhibitor partially purified paçoca peanut (AHTI). After each treatment, the animals were anesthetized and euthanized, their bloods were collected by cardiac puncture for the determination of CCK and other biochemical parameters (glucose, triglycerides, total cholesterol, high density lipoprotein, low density lipoprotein, glutamic-pyruvic transaminase, glutamic oxaloacetic transaminase and albumin) and their pancreas removed for histologic and morphometric analysis. The supplementation with paçoca peanut and the AHTI showed a decrease of body weight gain and food intake in both mice and rats, due to the satiety, since the animals showed no evidence of impairment of nutritional status conditioned by consumption the AHTI. There were also observed biochemical or morphological important when compared with controls. However, AHTI led to increased secretion of CCK, a peptide sacietogênico. Thus, these results indicate that AHTI present in paçoca peanut, is able to enhance the secretion of plasma CCK and thereby reduce the weight gain associated with lower food intake of experimenta animals

Adubação e o período anterior à interferência das plantas daninhas na cultura do amendoim

O presente trabalho teve como objetivo determinar o efeito da adubação sobre a comunidade infestante e sobre o período anterior à interferência (PAI) das plantas daninhas na cultura do amendoim, cv. IAC Runner 886, em sistema convencional. Os períodos de convivência estudados foram: 0, 7, 15, 20, 30, 45, 55 e 126 dias após a emergência (DAE), totalizando oito tratamentos, dispostos em blocos casualizados, com quatro repetições, em dois níveis de adubação: 0 e 150 kg ha-1 da formulação 00-20-20 (N-P-K). A adubação não alterou a composição da comunidade infestante, destacando-se Cyperus rotundus, Eleusine indica, Indigofera hirsuta, Portulaca oleraceae e Sida rhombifolia como as espécies de maior importância relativa. Contudo, a densidade de plantas daninhas foi maior na área não adubada, mas sem afetar de modo diferenciado a massa seca acumulada por elas. O cultivar de amendoim IAC Runner 886 pode conviver com essa comunidade com e sem adubação por até 15 e 17 DAE (PAI), respectivamente, sem sofrer perdas significativas na produção. A interferência das plantas daninhas reduziu entre 31 e 34% a produtividade do amendoim para as áreas sem adubação e com adubação, respectivamente.

Efeito do espaçamento entre fileiras de amendoim rasteiro na interferência de plantas daninhas na cultura

Objetivou-se com este trabalho avaliar o efeito da redução do espaçamento entre fileiras nos períodos de interferência e na produtividade do amendoim rasteiro (Arachis hypogaea). O experimento foi instalado no município de Jaboticabal-SP. Os tratamentos constaram de dois espaçamentos entre fileiras (80 e 90 cm), divididos em dois grupos. No primeiro, as plantas daninhas foram controladas desde a emergência até 0 (interferência constante), 30, 45, 60, 82, 97 e 112 dias depois. No segundo, as plantas daninhas conviveram com a cultura pelos mesmos períodos do grupo anterior. O delineamento experimental adotado foi o de blocos casualizados, em arranjo de parcelas subdivididas, com quatro repetições. As principais plantas daninhas presentes na área foram Digitaria sp., Xanthium strumarium, Acanthospermum hispidum e Cenchrus echinatus. Para uma perda tolerável de 5% de produtividade, o período crítico de prevenção à interferência foi dos 27 aos 76 e dos 35 aos 96 dias após a emergência para os espaçamentos de 80 e 90 cm, respectivamente; a queda de produtividade das parcelas mantidas com interferência de plantas daninhas em relação àquelas no limpo foi superior a 80%, independentemente do espaçamento.

Técnica de criação e parâmetros biológicos de Stegasta bosquella em amendoim

Studies with Stegasta bosquella in peanut crop are little explored by researchers, mainly by the need of obtaining, in the field, a large quantity of closed leaflets. Therefore, it was sought a way of rearing in a natural diet that facilitates the attainment of the insect. The research was developed at the Laboratorio de Resistencia de Plantas a Insetos (FCAV/Jaboticabal) (T: 25 +/- 2 degrees C, RH 60 +/- 10% and photophase: 12 hours) (Runner IAC 886). The rearing stock of was carried out by collecting caterpillars from the field and keeping them in flat bottom glass tubes until adult emergence and test performance. Caterpillars were individualized in Petri dish plates, lined with moistened filter paper, which contained closed and early opened leaflets, but closed with paper clips (imitating the closed leaflet). A randomized design with two treatments and 36 repetitions was used. After the pupae formation, they were separated into five couples and the adults were kept in transparent plastic cages containing a peanut stem with leaves for oviposition, and fed with a 10% honey solution. The duration and viability of the larval and pupal periods, male and female longevity with and without food, and fertility were evaluated. The two forms of larvae rearing (closed leaflet and leaflet closed with clips) did not influence on any of the studied parameters. Therefore, the rearing of S. bosquella becomes feasible in natural diet, which means there is no need to use the enclosed leaflets for this purpose, and implies the easiness for rearing.

Avaliação de espécies silvestres e cultivares de amendoim para resistência a Enneothrips flavens Moulton

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação de cultivares de amendoim para resistência a Spodoptera frugiperda

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

ADUBAÇÃO FOSFATADA E ÉPOCAS DE COLHEITA do AMENDOIM: EFEITOS NA PRODUÇÃO DE ÓLEO E DE PROTEÍNA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)