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.

Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change

Estimates of the response of crops to climate change rarely quantify the uncertainty inherent in the simulation of both climate and crops. We present a crop simulation ensemble for a location in India, perturbing the response of both crop and climate under both baseline (12 720 simulations) and doubled-CO2 (171720 simulations) climates. Some simulations used parameter values representing genotypic adaptation to mean temperature change. Firstly, observed and simulated yields in the baseline climate were compared. Secondly, the response of yield to changes in mean temperature was examined and compared to that found in the literature. No consistent response to temperature change was found across studies. Thirdly, the relative contribution of uncertainty in crop and climate simulation to the total uncertainty in projected yield changes was examined. In simulations without genotypic adaptation, most of the uncertainty came from the climate model parameters. Comparison with the simulations with genotypic adaptation and with a previous study suggested that the relatively low crop parameter uncertainty derives from the observational constraints on the crop parameters used in this study. Fourthly, the simulations were used, together with an observed dataset and a simple analysis of crop cardinal temperatures and thermal time, to estimate the potential for adaptation using existing cultivars. The results suggest that the germplasm for complete adaptation of groundnut cultivation in western India to a doubled-CO2 environment may not exist. In conjunction with analyses of germplasm and local management

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.

Drought, pod yield, pre-harvest Aspergillus infection and aflatoxin contamination on peanut in Niger

Soil moisture and soil temperature affect pre-harvest infection with Aspergillus flavus and production of aflatoxin. The objectives of our field research in Niger, West Africa, were to: (i) examine the effects of sowing date and irrigation treatments on pod yield, infection with A. flavus and aflatoxin concentration; and (ii) to quantify relations between infection, aflatoxin concentration and soil moisture stress. Seed of an aflatoxin susceptible peanut cv. JL24 was sown at two to four different sowing dates under four irrigation treatments (rainfed and irrigation at 7, 14 and 21 days intervals) between 1991 and 1994, giving 40 different 'environments'. Average air and soil temperatures of 28-34 degrees C were favourable for aflatoxin contamination. CROPGRO-peanut model was used to simulate the occurrence of moisture stress. The model was able to simulate yields of peanut well over the 40 environments (r(2) = 0.67). In general, early sowing produced greater pod yields, as well as less infection and lower aflatoxin concentration. There were negative linear relations between infection (r(2) = 0.62) and the average simulated fraction of extractable soil water (FESW) between flowering and harvest, and between aflatoxin concentration (r(2) = 0.54) and FESW in the last 25 days of pod-filling. This field study confirms that infection and aflatoxin concentration in peanut can be related to the occurrence of soil moisture stress during pod-filling when soil temperatures are near optimal for A. flavus. These relations could form the basis of a decision-support system to predict the risk of aflatoxin contamination in peanuts in similar environments. (c) 2005 Elsevier B.V. All rights reserved.

Effect of plant density and initial crown size on growth, development and yield in strawberry cultivars Elsanta and Bolero

The effects of density (plant spacing) and initial plant size on vegetative growth, flowering and fruiting were studied in the strawberry cultivars Elsanta and Bolero in their first and second years of cropping. The influence of these factors on light use and dry-matter partitioning was investigated. The size of planting material in 'Elsanta' and 'Bolero' slightly affected plant growth and yield, but this effect was not consistent and radiation use efficiency (RUE) and harvest index were unaltered. Plant spacing did not significantly affect the early stages of crop growth, but was important in determining growth and yield later in the season, this effect being more significant in the second year of cropping. Plant growth and yield per plant increased as plant spacing increased from 20 to 30 cm in both 'Elsanta' and 'Bolero', but the highest harvest index and yield per square metre were obtained at the closest spacing. Increased plant spacing also resulted in a greater leaf area and leaf area index. However, light was used less efficiently resulting in a lower RUE and lower harvest index (HI).

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

The survival advantage of milk and dairy consumption: An overview of evidence from cohort studies of vascular diseases, diabetes and cancer

Objectives: To conduct it detailed evaluation, with meta-analyses, of the published evidence on milk and dairy consumption and the incidence of vascular diseases and diabetes. Also to summarise the evidence on milk and dairy consumption and cancer reported by the World Cancer Research Fund and then to consider the relevance of milk and dairy consumption to survival in the UK, a typical Western community. Finally, published evidence on relationships with whole milk and fat-reduced milks was examined. Methods: Prospective cohort studies of vascular disease and diabetes with baseline data on milk or dairy consumption and a relevant disease outcome were identified by searching MEDLINE, and reference lists in the relevant published reports. Meta-analyses of relationships in these reports were conducted. The likely effect of milk and dairy consumption on survival was then considered, taking into account the results of published overviews of relationships of these foods with cancer. Results: From meta-analysis of 15 studies the relative risk of stroke and/or heart disease in subjects with high milk or dairy consumption was 0.84 (95% CI 0.76, 0,93) and 0.79 (0.75, 0.82) respectively, relative to the risk in those with low consumption. Four studies reported incident diabetes as an outcome, and the relative risk in the Subjects with the highest intake of milk or diary foods was 0.92 (0.86, 0.97). Conclusions: Set against the proportion of total deaths attributable to the life-threatening diseases in the UK, vascular disease, diabetes and cancer, the results of meta-analyses provide evidence of an overall survival advantage from the consumption of milk and dairy foods.

Impact on CVD risk of modifying milk fat to decrease intake of SFA and increase intake of cis-MUFA

Despite the acknowledged benefits of reducing SFA intake few countries within the EU meet recognised targets. Milk and dairy products represent the single largest source of dietary SFA in most countries, yet epidemiological evidence indicates that milk has cardioprotective properties such that simply reducing consumption of dairy foods to meet SFA targets may not be a sound public health approach. The present paper explores the options for replacing some of the SFA in milk fat with cis-MUFA through alteration of the diet of the dairy cow, and the evidence that such changes can improve the indicators for CHD and CVD in general for the consumer. In addition, the outcome of such changes on risk factors for CHD and CVD at the population level is examined in the light of a modelling exercise involving data for eleven EU member states. Given the current and projected costs of health care, the results indicate that urgent consideration should be given to such a strategy.

Impact on CVD risk of modifying milk fat to decrease intake of SFA and increase intake of cis-MUFA

Despite the acknowledged benefits of reducing SFA intake few countries within the EU meet recognised targets. Milk and dairy products represent the single largest source of dietary SFA in most countries, yet epidemiological evidence indicates that milk has cardioprotective properties such that simply reducing consumption of dairy foods to meet SFA targets may not be a sound public health approach. The present paper explores the options for replacing some of the SFA in milk fat with cis-MUFA through alteration of the diet of the dairy cow, and the evidence that such changes can improve the indicators for CHD and CVD in general for the consumer. In addition, the outcome of such changes on risk factors for CHD and CVD at the population level is examined in the light of a modelling exercise involving data for eleven EU member states. Given the current and projected costs of health care, the results indicate that urgent consideration should be given to such a strategy.

Enhancing the selenium content of bovine milk through alteration of the form and concentration of selenium in the diet of the dairy cow

Since estimated dietary selenium intake in the UK has declined steadily from around 60 mug day(-1) in 1975 to 34 mug day(-1) in 1997, there is a need to increase selenium intake from staple foods such as milk and milk products. An experiment was therefore done to investigate the relationship between dietary source and concentration of selenium and the selenium content of bovine milk. In a 3 x 3 factorial design, 90 mid-lactation Holstein dairy cows were supplemented over 8 weeks with either sodium selenite (S), a chelated selenium product (Selenium Metasolate(TM)) (C) or a selenium yeast (Sel-plex(TM)) (Y) at three different dietary inclusion levels of 0.38 (L), 0.76 (M) and 1.14 (H) mg kg(-1) dry matter (DM). Significant increases in milk selenium concentration were observed for all three sources with increasing inclusion level in the diet, but Y gave a much greater response (up to +65 mug l(-1)) than the other two sources of selenium (S and C up to +4 and +6 mug l(-1) respectively). The Y source also resulted in a substantially higher apparent efficiency of transfer of selenium from diet to milk than S or C. Feeding Y at the lowest dietary concentration, and thus within the maximum level permitted under EU regulations, resulted in milk with a selenium concentration of 28 mug l(-1). If the selenium concentration of milk in the UK was increased to this value, it would, at current consumption rates, provide an extra 8.7 mug selenium day(-1), or 11 and 14% of daily recommended national intake for men and women respectively. (C) 2004 Society of Chemical Industry.

Effect of replacing calcium salts of palm oil distillate with rapeseed oil, milled or whole rapeseeds on milk fatty-acid composition in cows fed maize silage-based diets

Inclusion of rapeseed feeds in dairy cow diets has the potential to reduce milk fat saturated fatty acid (SFA) and increase cis-monounsaturated fatty acid (cis-MUFA) content but effectiveness may depend on the form in which the rapeseed is presented. Four mid-lactation Holstein dairy cows were allocated to four maize silage-based dietary treatments according to a 4 x 4 Latin Square design, with 28-day experimental periods. Treatments consisted of a control diet (C containing 49 g/kg dry matter (DM) of calcium salts of palm oil distillate (CPO), or 49 g/kg DM of oil supplied as whole rapeseeds (WR), rapeseeds milled with wheat (MR) or rapeseed oil (RO). Replacing CPO with rapeseed feeds had no effect (P > 0.05) on milk fat and protein content, while milk yields were higher (P < 0.05) for RO and MR compared with WR (37.1, 38.1 and 34.3 kg/day, respectively). Substituting CPO with RO or MR reduced (P < 0.05) milk fat total SFA content (69.6, 55.6, 71.7 and 61.5 g/100g fatty acids for C, RO, WR and MR, respectively) and enhanced (P < 0.05) milk cis-9 18:1 MUFA concentrations (corresponding values 18.6, 24.3, 17.0 and 23.0 g/100g fatty acids) compared with C and WR. Treatments RO and MR also increased (P < 0.05) milk trans-MUFA content (4.4, 6.8, 10.5 g/100g fatty acids, C MR and RO, respectively). A lack of significant changes in milk fat composition when replacing CPO with WR suggests limited bioavailability of fatty acids in intact rapeseeds. In conclusion, replacing a commercial palm oil-based fat supplement in the diet with milled rapeseeds or rapeseed oil represented an effective strategy to alter milk fatty acid composition with the potential to improve human health. Inclusion of processed rapeseeds offered a good compromise for reducing milk SFA and increasing cis-MUFA, whilst minimising milk trans-MUFA and negative effects on animal performance.