Precision placement of fertiliser for optimising the early nutrition of vegetable crops: a review of the implications for the yield and quality of crops, and their nutrient use efficiency

The research outlined in this paper highlights the importance of the early nutrition of vegetable crops, and its long-term effects on their subsequent growth and development. Results are also presented to demonstrate how the nutrient supply during the establishment stages of young seedlings and transplants can be enhanced by targeting fertiliser to a zone close to their developing roots. Three different precision fertiliser placement techniques are compared for this purpose: starter, band or side-injected fertiliser. The use of each of these methods consistently produced the same (or greater) yields at lower application rates than those from conventional broadcast applications, increasing the apparent recovery of N, P and K, and the overall efficiency of nutrient use, while reducing the levels of residual nutrients in the soil. Starter fertilisers also advanced the maturity of some crops, and enhanced produce quality by increasing the proportions of the larger and/or more desirable marketable grades. The benefits of the different placement techniques are illustrated with selected examples from research at Warwick HRI using different vegetable crops, including lettuce, onion and carrot.

Climate change and the flowering time of annual crops

Crop production is inherently sensitive to variability in climate. Temperature is a major determinant of the rate of plant development and, under climate change, warmer temperatures that shorten development stages of determinate crops will most probably reduce the yield of a given variety. Earlier crop flowering and maturity have been observed and documented in recent decades, and these are often associated with warmer (spring) temperatures. However, farm management practices have also changed and the attribution of observed changes in phenology to climate change per se is difficult. Increases in atmospheric [CO2] often advance the time of flowering by a few days, but measurements in FACE (free air CO2 enrichment) field-based experiments suggest that elevated [CO2] has little or no effect on the rate of development other than small advances in development associated with a warmer canopy temperature. The rate of development (inverse of the duration from sowing to flowering) is largely determined by responses to temperature and photoperiod, and the effects of temperature and of photoperiod at optimum and suboptimum temperatures can be quantified and predicted. However, responses to temperature, and more particularly photoperiod, at supraoptimal temperature are not well understood. Analysis of a comprehensive data set of time to tassel initiation in maize (Zea mays) with a wide range of photoperiods above and below the optimum suggests that photoperiod modulates the negative effects of temperature above the optimum. A simulation analysis of the effects of prescribed increases in temperature (0-6 degrees C in + 1 degrees C steps) and temperature variability (0% and + 50%) on days to tassel initiation showed that tassel initiation occurs later, and variability was increased, as the temperature exceeds the optimum in models both with and without photoperiod sensitivity. However, the inclusion of photoperiod sensitivity above the optimum temperature resulted in a higher apparent optimum temperature and less variability in the time of tassel initiation. Given the importance of changes in plant development for crop yield under climate change, the effects of photoperiod and temperature on development rates above the optimum temperature clearly merit further research, and some of the knowledge gaps are identified herein.

British Nutrition Foundation annual lecture: chips with everything? Nutritional genomics and the application of diet in disease prevention

The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.

Landscape context and habitat type as drivers of bee diversity in European annual crops

To better understand the dynamics of bee populations in crops, we assessed the effect of landscape context and habitat type on bee communities in annual entomophilous crops in Europe. We quantified bee communities in five pairs of crop-country: buckwheat in Poland, cantaloupe in France, field beans in the UK, spring oilseed rape in Sweden, and strawberries in Germany. For each country, 7-10 study fields were sampled over a gradient of increasing proportion of semi-natural habitats in the surrounding landscape. The CORINE land cover classification was used to characterize the landscape over a 3 km radius around each study field and we used multivariate and regression analyses to quantify the impact of landscape features on bee abundance and diversity at the sub-generic taxonomic level. Neither overall wild bee abundance nor diversity, taken as the number of sub-genera. was significantly affected by the proportion of semi-natural habitat. Therefore, we used the most precise level of the CORINE classification to examine the possible links between specific landscape features and wild bee communities. Bee community composition fell into three distinct groups across Europe: group I included Poland, Germany, and Sweden, group 2 the UK, and group 3 France. Among all three groups, wild bee abundance and sub-generic diversity were affected by 17 landscape elements including some semi-natural habitats (e.g., transitional wood land-shrub), some urban habitats (e.g., sport and leisure facilities) and some crop habitats (e.g., non-irrigated arable land). Some bee taxa were positively affected by urban habitats only, others by semi-natural habitats only, and others by a combination of semi-natural, urban and crop habitats. Bee sub-genera favoured by urban and crop habitats were more resistant to landscape change than those favoured only by semi-natural habitats. In agroecosystems, the agricultural intensification defined as the loss of semi-natural habitats does not necessarily cause a decline in evenness at the local level, but can change community composition towards a bee fauna dominated by common taxa. (C) 2009 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.

Vertical distribution, size and composition of the weed seedbank under various tillage and herbicide treatments in a sequence of industrial crops

Investigations were conducted during the 2003, 2004 and 2005 growing seasons in northern Greece to evaluate effects of tillage regime (mouldboard plough, chisel plough and rotary tiller), cropping sequence (continuous cotton, cotton-sugar beet rotation and continuous tobacco) and herbicide treatment on weed seedbank dynamics. Amaranthus spp. and Portulaca oleracea were the most abundant species, ranging from 76% to 89% of total weed seeds found in 0-15 and 15-30 cm soil depths during the 3 years. With the mouldboard plough, 48% and 52% of the weed seedbank was found in the 0-15 and 15-30 cm soil horizons, while approximately 60% was concentrated in the upper 15 cm soil horizon for chisel plough and rotary tillage. Mouldboard ploughing significantly buried more Echinochloa crus-galli seeds in the 15-30 cm soil horizon compared with the other tillage regimes. Total seedbank (0-30 cm) of P. oleracea was significantly reduced in cotton-sugar beet rotation compared with cotton and tobacco monocultures, while the opposite occurred for E. crus-galli. Total seed densities of most annual broad-leaved weed species (Amaranthus spp., P. oleracea, Solanum nigrum) and E. crus-galli were lower in herbicide treated than in untreated plots. The results suggest that in light textured soils, conventional tillage with herbicide use gradually reduces seed density of small seeded weed species in the top 15 cm over several years. In contrast, crop rotation with the early established sugar beet favours spring-germinating grass weed species, but also prevents establishment of summer-germinating weed species by the early developing crop canopy.

Tillage and herbicide treatments with inter-row cultivation influence weed densities and yield of three industrial crops

Field experiments were conducted in northern Greece in 2003 and 2004 to evaluate effects of tillage regimes (moldboard plowing, chisel plowing, and rotary tilling), cropping sequences(continuous cotton, cotton-sugar beet rotation,and continuous tobacco) and herbicide treatments with inter-row hand hoeing on weed population densities. Total weed densities were not affected by tillage treatment except that of barnyardgrass (Echinochloa crus-galli), which increased only in moldboard plowing treated plots during 2003. Redroot pigweed (Amaranthus retroflexus)and black nightshade (Solanum nigrum) densities were reduced in continuous cotton, while purple nutsedge (Cyperus rotundus), E. crus-galli, S. nigrum, and johnsongras(Sorghum halepense) densities were reduced in tobacco. A. retroflexus and S. nigrum were effectively controlled by all herbicide treatments with inter-row hand hoeing,whereas E. crus-galli was effectively reduced by herbicides applied to cotton and tobacco. S. halepense density reduction was a result of herbicide applied to tobacco with inter-row hand hoeing. Yield of all crops was higher under moldboard plowing and herbicide treatments. Pre-sowing and pre-emergence herbicide treatments in cotton and pre-transplant in tobacco integrated with inter-row cultivation resulted in efficient control of annual weed species and good crop yields. These observations are of practical relevance to crop selection by farmers in order to maintain weed populations at economically acceptable densities through the integration of various planting dates, sustainable herbicide use and inter-row cultivation; tools of great importance in integrated weed management systems. Keywords: cropping sequence, herbicide, integrated weed management, inter-row cultivation,tillage.

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.

Quantitative response of the longevity of seed of twelve crops to temperature and moisture in hermetic storage

Seeds of 39 seed lots of a total of twelve different crops were stored hermetically in a wide range of air-dry environments (2-25% moisture content at 0-50 degrees C), viability assessed periodically, and the seed viability equation constants estimated. Within a species, estimates of the constants which quantify absolute longevity (K-E) and the relative effects on longevity of moisture content (C-W) and temperature (C-H and C-Q) did not differ (P >0.05 to P >0.25) among lots. Comparison among the 12 crops provided variant estimates of K-E and C-W (P< 0.01), but common values of C-H and C-Q (0.0322 and 0.000454, respectively, P >0.25). Maize (Zea mays) provided the greatest estimate of K-E (9.993, s.e.= 0.456), followed by sorghum (Sorghum bicolor) (9.381, s.e. 0.428), pearl millet (Pennisetum typhoides) (9.336, s.e.= 0.408), sugar beet (Beta vulgaris) (8.988, s.e.= 0.387), African rice (Oryza glaberrima) (8.786, s.e.= 0.484), wheat (Triticum aestivum) (8.498, s.e.= 0.431), foxtail millet (Setaria italica) (8.478, s.e.= 0.396), sugarcane (Saccharum sp.) (8.454, s.e.= 0.545), finger millet (Eleusine coracana) (8.288, s.e.= 0.392), kodo millet (Paspalum scrobiculatum) (8.138, s.e.= 0.418), rice (Oryza sativa) (8.096, s.e.= 0.416) and potato (Solanum tuberosum) (8.037, s.e.= 0.397). Similarly, estimates of C-W were ranked maize (5.993, s.e.= 0.392), pearl millet (5.540, s.e.= 0.348), sorghum (5.379, s.e.=0.365), potato (5.152, s.e.= 0.347), sugar beet (4.969, s.e.= 0.328), sugar cane (4.964, s.e.= 0.518), foxtail millet (4.829, s.e.= 0.339), wheat (4.836, s.e.= 0.366), African rice (4.727, s.e.= 0.416), kodo millet (4.435, s.e.= 0.360), finger millet (4.345, s.e.= 0.336) and rice (4.246, s.e.= 0.355). The application of these constants to long-term seed storage is discussed.

Nutrition of chicks and layers

When formulating least-cost poultry diets, ME concentration should be optimised by an iterative procedure, not entered as a fixed value. This iteration must calculate profit margins by taking into account the way in which feed intake and saleable outputs vary with ME concentration. In the case of broilers, adjustment of critical amino acid contents in direct proportion to ME concentration does not result in birds of equal fatness. To avoid an increase in fat deposition at higher energy levels, it is proposed that amino acid specifications should be adjusted in proportion to changes in the net energy supplied by the feed. A model is available which will both interpret responses to amino acids in laying trials and give economically optimal estimates of amino acid inputs for practical feed formulation. Flocks coming into lay and flocks nearing the end of the pullet year have bimodal distributions of rates of lay, with the result that calculations of requirement based on mean output will underestimate the optimal amino acid input for the flock. Chick diets containing surplus protein can lead to impaired utilisation of the first-limiting amino acid. This difficulty can be avoided by stating amino acid requirements as a proportion of the protein.

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.