A universal agro-hydrological model for water and nitrogen cycles in the soil-crop system SMCR_N: critical update and further validation

Agro-hydrological models have widely been used for optimizing resources use and minimizing environmental consequences in agriculture. SMCRN is a recently developed sophisticated model which simulates crop response to nitrogen fertilizer for a wide range of crops, and the associated leaching of nitrate from arable soils. In this paper, we describe the improvements of this model by replacing the existing approximate hydrological cascade algorithm with a new simple and explicit algorithm for the basic soil water flow equation, which not only enhanced the model performance in hydrological simulation, but also was essential to extend the model application to the situations where the capillary flow is important. As a result, the updated SMCRN model could be used for more accurate study of water dynamics in the soil-crop system. The success of the model update was demonstrated by the simulated results that the updated model consistently out-performed the original model in drainage simulations and in predicting time course soil water content in different layers in the soil-wheat system. Tests of the updated SMCRN model against data from 4 field crop experiments showed that crop nitrogen offtakes and soil mineral nitrogen in the top 90 cm were in a good agreement with the measured values, indicating that the model could make more reliable predictions of nitrogen fate in the crop-soil system, and thus provides a useful platform to assess the impacts of nitrogen fertilizer on crop yield and nitrogen leaching from different production systems. (C) 2010 Elsevier B.V. All rights reserved.

Toward a combined seasonal weather and crop productivity forecasting system: Determination of the working spatial scale

A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

A critical assessment of a desk study comparing crop production systems: The example of the 'system of rice intensification' versus 'best management practice'

When assessing hypotheses, the possibility and consequences of false-positive conclusions should be considered along with the avoidance of false-negative ones. A recent assessment of the system of rice intensification (SRI) by McDonald et al. [McDonald, A.J., Hobbs, P.R., Riha, S.J., 2006. Does the system of rice intensification outperform conventional best management? A synopsis of the empirical record. Field Crops Res. 96, 31-36] provides a good example where this was not done as it was preoccupied with avoiding false-positives only. It concluded, based on a desk study using secondary data assembled selectively from diverse sources and with a 95% level of confidence, that 'best management practices' (BMPs) on average produce 11% higher rice yields than SRI methods, and that, therefore, SRI has little to offer beyond what is already known by scientists.

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop-soil system: validation and application

Models for water transfer in the crop-soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop-soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop-soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. (c) 2009 Elsevier B.V. All rights reserved.

Examining the interaction of growing crops with local climate using a coupled crop-climate model

This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

The potential of combining Pasteuria penetrans and neem (Azadirachta indica) formulations as a management system for root-knot nematodes on tomato

Initial applications of 10(4) spores g(-1) of Pasteuria penetrans, and dried neem cake and leaves at 3 and 2% w:w, respectively, were applied to soil in pots. Juveniles of Meloidogyne javanica were added immediately to the pots (500, 5,000 or 10,000) before planting 6-week-old tomato seedlings. The tomatoes were sampled after 64 days; subsequently a second crop was grown for 59 days and a third crop for 67 days without further applications of P. penetrans and neem. There was significantly less root-galling in the P. penetrans combined with neem cake treatment at the end of the third crop and this treatment also had the greatest effect on the growth of the tomato plants. At the end of the third crop, 30% of the females were infected with P. penetrans in those treatments where spores had been applied at the start of the experiment. The effects of neem leaves and neem cake on the nematode population did not persist through the crop sequences but the potential for combining the amendments with a biological control agent such as P. penetrans is worthy of further evaluation.

Development and assessment of a coupled crop-climate model

It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.

Aggregation of parasitism risk in an aphid-parasitoid system: Effects of plant patch size and aphid density

Few studies have linked density dependence of parasitism and the tritrophic environment within which a parasitoid forages. In the non-crop plant-aphid, Centaurea nigra-Uroleucon jaceae system, mixed patterns of density-dependent parasitism by the parasitoids Aphidius funebris and Trioxys centaureae were observed in a survey of a natural population. Breakdown of density-dependent parasitism revealed that density dependence was inverse in smaller colonies but direct in large colonies (>20 aphids), suggesting there is a threshold effect in parasitoid response to aphid density. The CV2 of searching parasitoids was estimated from parasitism data using a hierarchical generalized linear model, and CV2>1 for A. funebris between plant patches, while for T. centaureae CV2>1 within plant patches. In both cases, density independent heterogeneity was more important than density-dependent heterogeneity in parasitism. Parasitism by T. centaureae increased with increasing plant patch size. Manipulation of aphid colony size and plant patch size revealed that parasitism by A. funebris was directly density dependent at the range of colony sizes tested (50-200 initial aphids), and had a strong positive relationship with plant patch size. The effects of plant patch size detected for both species indicate that the tritrophic environment provides a source of host density independent heterogeneity in parasitism, and can modify density-dependent responses. (c) 2007 Gessellschaft fur Okologie. Published by Elsevier GmbH. All rights reserved.

Effects of cultural system (organic and conventional) on growth, photosynthesis and yield components of sweet corn (zea mays L.) under semi-arid environment

Organic sweet maize consists of a new industrial crop product. Field experiment was conducted to determine the effects of cultural systems on growth, photosynthesis and yield components of sweet maize crop (Zea mays L. F-1 hybrid 'Midas'). A randomized complete block design was employed with four replicates per treatment (organic fertilization: cow manure (5, 10 and 20 t ha(-1)), poultry manure (5, 10 and 20 t ha(-1)) and barley mulch (5, 10 and 20 t ha(-1)), synthetic fertilizer (240 kg N ha(-1)): 21-0-0 and control). The lowest dry weight, height and leaf area index and sod organic matter were measured in the control treatment. Organic matter content was proportionate to the amount of manure applied. The control plots had the lowest yield (1593 kg ha(-1)) and the double rate cow manure plots the had,greatest one. (6104 kg ha(-1)). High correlation between sweet corn yield and organic matter was registered. Moreover, the lowest values of 1000-grain weight were obtained with control plot. The fertilizer plot gave values which were similar to the full rate cow manure treatment. The photosynthetic race of the untreated control was significantly lower than that of the other treatments. The phorosynthetic rate increased as poultry manure and barley mulch ram decreased and as cow manure increased. Furthermore the untreated control had the lowest stomatal conductance and chlorophyll content. Our results indicated that sweet corn growth and yield in the organic plots was significantly higher than those in the conventional plots.

PGR forum: serving the crop wild relative user community

The Euro-Mediterranean region is an important centre for the diversity of crop wild relatives. Crops, such as oats (Avena sativa), sugar beet (Beta vulgaris), apple (Malus domestica), annual meadow grass (Festuca pratensis), white clover (Trifolium repens), arnica (Arnica montana), asparagus (Asparagus officinalis), lettuce (Lactuca sativa), and sage (Salvia officinalis) etc., all have wild relatives in the region. The European Community funded project, PGR Forum (www.pgrforum.org) is building an online information system to provide access to crop wild relative data to a broad user community; including plant breeders, protected area managers, policy-makers, conservationists, taxonomists and the wider public. The system will include data on uses, geographical distribution, biology, population and habitat information, threats (including IUCN Red List assessments) and conservation actions. This information is vital for the continued sustainable utilisation and conservation of crop wild relatives. Two major databases have been utilised as the backbone to a Euro-Mediterranean crop wild relative catalogue, which forms the core of the information system: Euro+Med PlantBase (www.euromed.org.uk) and Mansfeld’s World Database of Agricultural and Horticultural Crops (http://mansfeld.ipk-gatersleben.de). By matching the genera found within the two databases, a preliminary list of crop wild relatives has been produced. Around 20,000 of the 30,000+ species listed in Euro+Med PlantBase can be considered crop wild relatives, i.e. those species found within the same genus as a crop. The list is currently being refined by implementing a priority ranking system based on the degree of relatedness of taxa to the associated crop.

Conservation and sustainable use of crop wild relatives

Conservation of crop wild relatives (CWRs) is a complex interdisciplinary process that is being addressed by various national and international initiatives, including two Global Environment Facility projects ('In situ Conservation of Crop Wild Relatives through Enhanced Information Management and Field Application' and 'Design, Testing and Evaluation of Best Practices for in situ Conservation of Economically Important Wild Species'), the European Community-funded project 'European Crop Wild Relative Diversity Assessment and Conservation Forum (PGR Forum)' and the European 'In situ and On Farm Network'. The key issues that have arisen are: (1) the definition of what constitutes a CWR, (2) the need for national and regional information systems and a global system, (3) development and application of priority-determining mechanisms, (4) the incorporation of the conservation of CWRs into existing national, regional and international PGR programmes, (5) assessment of the effectiveness of conservation actions, (6) awareness of the importance of CWRs in agricultural development at local, national and international levels both for the scientific and lay communities and (7) policy development and legal framework. The above issues are illustrated by work on the conservation of a group of legumes known as grasspea chicklings, vetchlings, and horticultural ornamental peas (Lathyrus spp.) in their European and Mediterranean centre of diversity. (c) 2007 Published by Elsevier B.V.

The transformation of earth-system observations into information of socio-economic value in GEOSS

The Group on Earth Observations System of Systems, GEOSS, is a co-ordinated initiative by many nations to address the needs for earth-system information expressed by the 2002 World Summit on Sustainable Development. We discuss the role of earth-system modelling and data assimilation in transforming earth-system observations into the predictive and status-assessment products required by GEOSS, across many areas of socio-economic interest. First we review recent gains in the predictive skill of operational global earth-system models, on time-scales of days to several seasons. We then discuss recent work to develop from the global predictions a diverse set of end-user applications which can meet GEOSS requirements for information of socio-economic benefit; examples include forecasts of coastal storm surges, floods in large river basins, seasonal crop yield forecasts and seasonal lead-time alerts for malaria epidemics. We note ongoing efforts to extend operational earth-system modelling and assimilation capabilities to atmospheric composition, in support of improved services for air-quality forecasts and for treaty assessment. We next sketch likely GEOSS observational requirements in the coming decades. In concluding, we reflect on the cost of earth observations relative to the modest cost of transforming the observations into information of socio-economic value.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.