Water and nitrogen footprint in an irrigated crop under mineral and organic fertilization

In order to establish rational nitrogen (N) application and reduce groundwater contamination, a clearer understanding of the N distribution through the growing season and its balance is crucial. Excessive doses of N and/or water applied to fertigated crops involve a substantial risk of aquifer contamination by nitrate; but knowledge of N cycling and availability within the soil could assist in avoiding this excess. In central Spain, the main horticultural fertigated crop is the melon type ?piel de sapo¿ and it is cultivated in vulnerable zones to nitrate pollution (Directive 91/676/CEE). However, until few years ago there were not antecedents related to the optimization of nitrogen fertilization together with irrigation. Water and N footprint are indicators that allow assessing the impact generated by different agricultural practices, so they can be used to improve the management strategies in fertigated crop systems. The water footprint distinguishes between blue water (sources of water applied to the crop, like irrigation and precipitation), green water (water used by the crop and stored in the soil), and it is furthermore possible to quantify the impact of pollution by calculating the grey water, which is defined as the volume of polluted water created from the growing and production of crops. On the other hand, the N footprint considers green N (nitrogen consumed by the crops and stored in the soil), blue N (N available for crop, like N applied with mineral and/or organic fertilizers, N applied with irrigation water and N mineralized during the crop period), whereas grey N is the amount of N-NO3- washed from the soil to the aquifer. All these components are expressed as the ratio between the components of water or N footprint and the yield (m3 t-1 or kg N t-1 respectively). The objetives of this work were to evaluate the impact derivated from the use of different fertilizer practices in a melon crop using water and N footprint.

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

The impact of soil salinity on the yield, composition and physiology of the bioenergy grass Miscanthus × giganteus

Funded by OPTIMA Biotechnology & Biological Sciences Research Council (BBSRC) Institute Strategic Programme Energy Grasses & Biorefining. Grant Number: BBS/E/W/10963A01 Defra GIANT LINK

Plant genetic resources: What can they contribute toward increased crop productivity?

To feed a world population growing by up to 160 people per minute, with >90% of them in developing countries, will require an astonishing increase in food production. Forecasts call for wheat to become the most important cereal in the world, with maize close behind; together, these crops will account for ≈80% of developing countries’ cereal import requirements. Access to a range of genetic diversity is critical to the success of breeding programs. The global effort to assemble, document, and utilize these resources is enormous, and the genetic diversity in the collections is critical to the world’s fight against hunger. The introgression of genes that reduced plant height and increased disease and viral resistance in wheat provided the foundation for the “Green Revolution” and demonstrated the tremendous impact that genetic resources can have on production. Wheat hybrids and synthetics may provide the yield increases needed in the future. A wild relative of maize, Tripsacum, represents an untapped genetic resource for abiotic and biotic stress resistance and for apomixis, a trait that could provide developing world farmers access to hybrid technology. Ownership of genetic resources and genes must be resolved to ensure global access to these critical resources. The application of molecular and genetic engineering technologies enhances the use of genetic resources. The effective and complementary use of all of our technological tools and resources will be required for meeting the challenge posed by the world’s expanding demand for food.

Ecological intensification of cereal production systems: Yield potential, soil quality, and precision agriculture

Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70–80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.

Oats in Minnesota, acreage, yield, production by counties, 1921-1959.

Mode of access: Internet.

Corn: acreage, yield, and production of all corn, corn for grain, corn for silage, and acreage for forage, by States, 1866-1943.

Cover title.

Sweetpotatoes, estimated in hundredweight : by states, 1868-1953 : acreage, yield, production, price, value, farm disposition /

Mode of access: Internet.

Corn and soybeans, acreage, yield, and production, Illinois by counties /

Description based on: 1967; title from caption.

Yield response of rice (Oryza sativa L.) genotypes to drought under rainfed lowlands 4. Vegetative stage screening in the dry season

Screening for drought resistance of rainfed lowland rice using drought score (leaf death) as a selection index has a long history of use in breeding programs. Genotypic variation for drought score during the vegetative stage in two dry season screens was examined among 128 recombinant inbred lines from four biparental crosses. The genotypic variation detected for drought score in the dry season was used to examine the reliability of the dry season screening method to estimate relative grain yield of genotypes under different types of drought stress in the wet season. Large genotypic variation for drought score existed in two experiments (A and B). However, there was no relationship between the drought scores of genotypes determined in these two experiments. Different patterns of development and severity of drought stress in these two experiments, i.e. slow development and mild plant water deficit in experiment A and fast development and severe plant water deficit in experiment B, were identified as the major factors contributing to the genotypes responding differently. Larger drought score in the dry season experiments was associated with lower grain yield under specific drought stress conditions in the wet season, but the association was weak to moderate and significant only in particular drought conditions. In most cases, a significant phenotypic and moderate genetic correlation between drought score in the dry season and grain yield in the wet season existed only when both drought score and grain yield of genotypes were affected by similar patterns and severity of drought stress in their respective experimental environments. The dry season environments used to measure genotypic variation for drought score should be managed to correspond to relevant types of drought environment that are frequent in the wet season. The efficiency of using the drought score as an indirect selection criterion for improving grain yield for drought conditions was lower than the direct selection for grain yield, and hence wet season screening with grain yield as a selection criterion would be more efficient. However, using drought score as a selection index, a larger number of genotypes can be evaluated than for wet season grain yield. Therefore, it is possible to apply higher selection intensities using the drought score system, and the selected lines can be further tested for grain yield in the wet season. (C) 2004 Elsevier B.V. All rights reserved.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Three putative types of El Nino revealed by spatial variability in impact on Australian wheat yield

The El Nino-Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Nino events are often associated with severe drought conditions. However, El Nino events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Nino are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (footprints) found in the El Nino impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean-atmosphere dynamics identifies three types of El Nino differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of individual El Nino events on agricultural systems.

Effects of sodium on potassium nutrition in three tropical root crop species

The potassium (K) nutrition and high K requirement of tropical root crops may be affected by their sodium (Na) status, as has been observed in a number of plant species. Solution culture was used to study the effects of K and Na supplies in tannia [Xanthosoma sagittifolium (L.) Schott.], sweetpotato [Ipomoea batatas (L.) Lam.] and taro [Colocasia esculenta (L.) Schott]. At low K supply, Na ameliorated symptoms of K deficiency and increased growth in tannia, and to a lesser extent in sweetpotato, but not in taro. None of the species responded to Na at adequate K supply. Differences in response to Na were attributed to differences in Na translocation to plant tops. At maximum Na supply, the Na concentration in index leaves averaged 1.82% in tannia, 0.205% in sweetpotato, and 0.0067% in taro. An increase in the supply of Na resulted in a shift in the critical K concentration for deficiency (i.e., 90% of maximum yield) in index leaves from 2.9% to 1.2% in tannia, and from 4.8% to 2.5% in sweetpotato. The critical K concentration in taro was 3.3%, irrespective of Na supply. To overcome the problem in tannia and sweetpotato of determining the critical concentration relevant to a leaf sample of unknown K status, a relationship was established for each species relating the critical K concentration to the concentration of Na in the index leaves.

Grain yield components of pearl millet under optimum conditions can be used to identify germplasm with adaptation to and zones

There is evidence that high-tillering, small-panicled pearl millet landraces are better adapted to the severe, unpredictable drought stress of the and zones of NW India than are low-tillering, large-panicled modern varieties, which significantly outyield the landraces under favourable conditions. In this paper, we analyse the relationship of and zone adaptation with the expression, under optimum conditions, of yield components that determine either the potential sink size or the ability to realise this potential. The objective is to test whether selection under optimal conditions for yield components can identify germplasm with adaptation to and zones in NW India, as this could potentially improve the efficiency of pearl millet improvement programs targeting and zones. We use data from an evaluation of over 100 landraces from NW India, conducted for two seasons under both severely drought-stressed and favourable conditions in northwest and south India. Trial average grain yields ranged from 14 g m(-2) to 182 g m(-2). The landraces were grouped into clusters, based on their phenology and yield components as measured under well-watered conditions in south India. In environments without pre-flowering drought stress, tillering type had no effect on potential sink size, but low-tillering, large-panicled landraces yielded significantly more grain, as they were better able to realise their potential sink size. By contrast, in two low-yielding and zone environments which experienced pre-anthesis drought stress, low-fillering, large-panicled landraces yielded significantly less grain than high-tillering ones with comparable phenology, because of both a reduced potential sink size and a reduced ability to realise this potential. The results indicate that the high grain yield of low-tillering, large-panicled landraces under favourable conditions is due to improved partitioning, rather than resource capture. However, under severe stress with restricted assimilate supply, high-tillering, small-panicled landraces are better able to produce a reproductive sink than are large-panicled ones. Selection under optimum conditions for yield components representing a resource allocation pattern favouring high yield under severe drought stress, combined with a capability to increase grain yield if assimilates are available, was more effective than direct selection for grain yield in identifying germplasm adapted to and zones. Incorporating such selection in early generations of variety testing could reduce the reliance on random stress environments. This should improve the efficiency of millet breeding programs targeting and zones. (c) 2005 Elsevier B.V. All rights reserved.