The performance of the EU-Rotate_N model in predicting the growth and nitrogen uptake of rotations of field vegetable crops in a Mediterranean environment

The EU-Rotate_N model was developed as a tool to estimate the growth and nitrogen (N) uptake of vegetable crop rotations across a wide range of European climatic conditions and to assess the economic and environmental consequences of alternative management strategies. The model has been evaluated under field conditions in Germany and Norway and under greenhouse conditions in China. The present work evaluated the model using Italian data to evaluate its performance in a warm and dry environment. Data were collected from four 2-year field rotations, which included lettuce (Lactuca sativa L.), fennel (Foeniculum vulgare Mill.), spinach (Spinacia oleracea L.), broccoli (Brassica oleracea L. var. italica Plenck) and white cabbage (B. oleracea convar. capitata var. alba L.); each rotation used three different rates of N fertilizer (average recommended N1, assumed farmer's practice N2=N1+0·3×N1 and a zero control N0). Although the model was not calibrated prior to running the simulations, results for above-ground dry matter biomass, crop residue biomass, crop N concentration and crop N uptake were promising. However, soil mineral N predictions to 0·6 m depth were poor. The main problem with the prediction of the test variables was the poor ability to capture N mineralization in some autumn periods and an inappropriate parameterization of fennel. In conclusion, the model performed well, giving results comparable with other bio-physical process simulation models, but for more complex crop rotations. The model has the potential for application in Mediterranean environments for field vegetable production

A comparison of two models to predict nitrogen dynamics in organic agricultural systems

Two publicly available crop/soil models were compared. These were the EU-Rotate_N model (www.warwick.ac.uk/go/eurotaten) and the NDICEA model (www.ndicea.nl). Each simulation was also compared to measured data from an organically managed site in the English Midlands. Results showed that, overall, EU-Rotate_N gave a better estimation of soil mineral nitrogen, particularly after the incorporation of a long-term fertility-building crop. This model has a lot of flexibility but is aimed at researchers and requires more work before it is ready to be used by farmers or advisors. The NDICEA model is much simpler to use with a user-friendly interface

Nitrate pollution from horticultural production systems : tools for policy and advice from field to catchment scales

The implementation of the Nitrates Directive has imposed a requirement to restrict N fertiliser and manuring practices on farms across the EU in order to reduce nitrate losses to water. These requirements have since been extended by the more demanding Water Framework Directive, which broadens the focus from the control of farm practices to a consideration of the impacts of pollutants from all sources on water quality at a catchment or larger scale. Together, these Directives set limits for water quality, and identify general strategies for how these might be achieved. However, it is the responsibility of policy makers in each Nation State to design the details of the management practices and environmental protection measures required to meet the objectives of the legislation, to ensure they are appropriate for their specific types of land use and climate. This paper describes various modelling tools for comparing different cropping and land use strategies, and illustrates with examples how they can inform policy makers about the environmental benefits of changing management practices and how to prioritise them. The results can help to provide the specific advice on N fertiliser and land use management required by farmers and growers at a field scale, and by environmental managers at a catchment or larger scale. A further example of how results from multiple catchments can be up-scaled and compared using Geographic Information Systems is also outlined

Improved efficiency of nutrient and water use for high quality field vegetable production using fertigation

Drip-based fertigation may improve the application efficiency of water and nutrients while maintaining or improving marketable yield and quality at harvest and post-harvest. Two plantings of lettuce (Lactuca sativa) were grown in the UK, with six N treatments and two methods of irrigation and N application. The conventional overhead irrigated treatments had all N applied in the base dressing with irrigation scheduled from SMD calculations. The closed loop treatments had nitrogen and irrigation delivered via drip automatically controlled by a sensor and logger system. The work established that water content in the root zone can be monitored in real time using horizontally oriented soil moisture sensors linked to data logging and telemetry, and that these data can be used to automatically trigger drip irrigation for commercially grown field vegetables. When the closed loop irrigation control was combined with fertigation treatments, lettuce crops were grown with savings of up to 60% and 75% of water and nitrogen respectively, compared to standard UK production systems. However, excess supply of N through fertigation rather than solid fertiliser was more detrimental to marketable yield and post harvest quality highlighting that care is needed when selecting N rates for fertigation

Development and critical evaluation of a generic 2-D agro-hydrological model (SMCR_N) for the responses of crop yield and nitrogen composition to nitrogen fertilizer

Models play an important role in optimizing fertilizer use in agriculture to maintain sustainable crop production and to minimize the risk to the environment. In this study, we present a new Simulation Model for Crop Response to Nitrogen fertilizer (SMCR_N). The SMCR_N model, based on the recently developed model EU-Rotate_N for the N-economies of a wide range of crops and cropping systems, includes new modules for the estimation of N in the roots and an associated treatment of the recovery of soil mineral N by crops, for the reduction of growth rates by excessive fertilizer-N, and for the N mineralization from soil organic matter. The validity of the model was tested against the results from 32 multi-level fertilizer experiments on 16 different crop species. For this exercise none of the coefficients or parameters in the model was adjusted to improve the agreement between measurement and simulation. Over the practical range of fertilizer-N levels model predictions were, with few exceptions, in good agreement with measurements of crop dry weight (excluding fibrous roots) and its %N. The model considered that the entire reduction of soil inorganic N during growth was due to the sum of nitrate leaching, retention of N in fibrous roots and N uptake by the rest of the plant. The good agreement between the measured and simulated uptakes suggests that in this arable soil, losses of N from other soil processes were small. At high levels of fertilizer-N yields were dominated by the negative osmotic effect of fertilizer-N and model predictions for some crops were poor. However, the predictions were significantly improved by using a different value for the coefficient defining the osmotic effect for saline sensitive crops. The developed model SMCR_N uses generally readily available inputs, and is more mechanistic than most agronomic models and thus has the potential to be used as a tool for optimizing fertilizer practice

A sensitivity analysis of the prediction of the nitrogen fertilizer requirement of cauliflower crops using the HRI WELL_N computer model

HRI WELL_N is an easy to use computer model, which has been used by farmers and growers since 1994 to predict crop nitrogen (N) requirements for a wide range of agricultural and horticultural crops. A sensitivity analysis was carried out to investigate the model predictions of the N fertilizer requirement of cauliflower crops, and, at that rate, the yield achieved, yield response to the fertilizer applied, N uptake, NO3-N leaching below 30 and 90 cm and mineral N at harvest. The sensitivity to four input factors – soil mineral N before planting, mineralization rate of soil organic matter, expected yield and duration of growth – was assessed. Values of these were chosen to cover ranges between 40% and 160% of values typical for field crops of cauliflowers grown in East Anglia. The assessments were made for three soils – sand, sandy loam and silt – and three rainfall scenarios – an average year and years with 144% or 56% of average rainfall during the growing season. The sensitivity of each output variable to each of the input factors (and interactions between them) was assessed using a unique ‘sequential' analysis of variance approach developed as part of this research project. The most significant factors affecting N fertilizer requirement across all soil types/rainfall amounts were soil mineral N before planting and expected yield. N requirement increased with increasing yield expectation, and decreased with increasing amounts of soil mineral N before planting. The responses to soil mineral N were much greater when higher yields were expected. Retention of N in the rooting zone was predicted to be poor on light soils in the wettest conditions suggesting that to maximize N use, plants needed to grow rapidly and have reasonable yield potential. Assessment of the potential impacts of errors in the values of the input factors indicated that poor estimation of, in particular, yield expectation and soil mineral N before planting could lead to either yield loss or an increased level of potentially leachable soil mineral N at harvest. The research demonstrates the benefits of using computer simulation models to quantify the main factors for which information is needed in order to provide robust N fertilizer recommendations

Paramagnon dispersion in β\beta-FeSe observed by Fe LL-edge resonant inelastic x-ray scattering

We report an Fe $L$-edge resonant inelastic x-ray scattering (RIXS) study of the unusual superconductor $\beta$-FeSe. The high energy resolution of this RIXS experiment ($\approx\,$55$\,$meV FWHM) made it possible to resolve low-energy excitations of the Fe $3d$ manifold. These include a broad peak which shows dispersive trends between 100-200$\,$meV along the $(\pi,0)$ and $(\pi,\pi)$ directions of the one-Fe square reciprocal lattice, and which can be attributed to paramagnon excitations. The multi-band valence state of FeSe is among the most metallic in which such excitations have been discerned by soft x-ray RIXS

Spin resonance in the superconducting state of Li1−x_{1-x}Fex_{x}ODFe1−y_{1-y}Se observed by neutron spectroscopy

We have performed inelastic neutron scattering measurements on a powder sample of the superconductor lithium iron selenide hydroxide Li$_{1-x}$Fe$_{x}$ODFe$_{1-y}$Se ($x \simeq 0.16, y \simeq 0.02$, $T_{\rm c} = 41$\,K). The spectrum shows an enhanced intensity below $T_{\rm c}$ over an energy range $0.64\times2\Delta < E < 2\Delta$, where $\Delta$ is the superconducting gap, with maxima at the wave vectors $Q_1 \simeq 1.46$\,\AA$^{-1}$ and $Q_2 \simeq 1.97$\,\AA$^{-1}$. The behavior of this feature is consistent with the spin resonance mode found in other unconventional superconductors, and strongly resembles the spin resonance observed in the spectrum of the molecular-intercalated iron selenide, Li$_{0.6}$(ND$_{2}$)$_{0.2}$(ND$_{3}$)$_{0.8}$Fe$_{2}$Se$_{2}$. The signal can be described with a characteristic two-dimensional wave vector $(\pi, 0.67\pi)$ in the Brillouin zone of the iron square lattice, consistent with the nesting vector between electron Fermi sheets