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.

Crop yield reduction in the tropics under climate change: Processes and uncertainties

Many modelling studies examine the impacts of climate change on crop yield, but few explore either the underlying bio-physical processes, or the uncertainty inherent in the parameterisation of crop growth and development. We used a perturbed-parameter crop modelling method together with a regional climate model (PRECIS) driven by the 2071-2100 SRES A2 emissions scenario in order to examine processes and uncertainties in yield simulation. Crop simulations used the groundnut (i.e. peanut; Arachis hypogaea L.) version of the General Large-Area Model for annual crops (GLAM). Two sets of GLAM simulations were carried out: control simulations and fixed-duration simulations, where the impact of mean temperature on crop development rate was removed. Model results were compared to sensitivity tests using 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., and Bell, M.J., 1995, A peanut simulation model: I. Model development and testing. Agron. J. 87, 1085-1093]. GLAM simulations were particularly sensitive to two processes. First, elevated vapour pressure deficit (VPD) consistently reduced yield. The same result was seen in some simulations using both other crop models. Second, GLAM crop duration was longer, and yield greater, when the optimal temperature for the rate of development was exceeded. Yield increases were also seen in one other crop model. Overall, the models differed in their response to super-optimal temperatures, and that difference increased with mean temperature; percentage changes in yield between current and future climates were as diverse as -50% and over +30% for the same input data. The first process has been observed in many crop experiments, whilst the second has not. Thus, we conclude that there is a need for: (i) more process-based modelling studies of the impact of VPD on assimilation, and (ii) more experimental studies at super-optimal temperatures. Using the GLAM results, central values and uncertainty ranges were projected for mean 2071-2100 crop yields in India. In the fixed-duration simulations, ensemble mean yields mostly rose by 10-30%. The full ensemble range was greater than this mean change (20-60% over most of India). In the control simulations, yield stimulation by elevated CO2 was more than offset by other processes-principally accelerated crop development rates at elevated, but sub-optimal, mean temperatures. Hence, the quantification of uncertainty can facilitate relatively robust indications of the likely sign of crop yield changes in future climates. (C) 2007 Elsevier B.V. All rights reserved.

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.

Simulation of the impact of high temperature stress on annual crop yields

Brief periods of high temperature which occur near flowering can severely reduce the yield of annual crops such as wheat and groundnut. A parameterisation of this well-documented effect is presented for groundnut (i.e. peanut; Arachis hypogaeaL.). This parameterisation was combined with an existing crop model, allowing the impact of season-mean temperature, and of brief high-temperature episodes at various times near flowering, to be both independently and jointly examined. The extended crop model was tested with independent data from controlled environment experiments and field experiments. The impact of total crop duration was captured, with simulated duration being within 5% of observations for the range of season-mean temperatures used (20-28 degrees C). In simulations across nine differently timed high temperature events, eight of the absolute differences between observed and simulated yield were less than 10% of the control (no-stress) yield. The parameterisation of high temperature stress also allows the simulation of heat tolerance across different genotypes. Three parameter sets, representing tolerant, moderately sensitive and sensitive genotypes were developed and assessed. The new parameterisation can be used in climate change studies to estimate the impact of heat stress on yield. It can also be used to assess the potential for adaptation of cropping systems to increased temperature threshold exceedance via the choice of genotype characteristics. (c) 2005 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.

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.