Yield, nutrient utilization and soil properties in a melon crop amended with wine-distillery waste

In Spain, large quantities of wine are produced every year (3,339,700 tonnes in 2011) (FAO, 2011) with the consequent waste generation. During the winemaking process, solid residues like grape stalks are generated, as well as grape marc and wine lees as by-products. According to the Council Regulation (EC) 1493/1999 on the common organization of the wine market, by-products coming from the winery industry must be sent to alcohol-distilleries to generate exhausted grape marc and vinasses. With an adequate composting treatment, these wastes can be applied to soils as a source of nutrients and organic matter. A three-year field experiment (2011, 2012 and 2013) was carried out in Ciudad Real (central Spain) to study the effects of wine-distillery waste compost application in a melon crop (Cucumis melo L.). Melon crop has been traditionally cultivated in this area with high inputs of water and fertilizers, but no antecedents of application of winery wastes are known. In a randomized complete block design, four treatments were compared: three compost doses consisted of 6.7 (D1), 13.3 (D2) and 20 t compost ha-1 (D3), and a control treatment without compost addition (D0). The soil was a shallow sandy-loam (Petrocalcic Palexeralfs) with a depth of 0.60 m and a discontinuous petrocalcic horizon between 0.60 and 0.70 m, slightly basic (pH 8.4), poor in organic matter (0.24%), rich in potassium (410 ppm) and with a medium level of phosphorus (22.1 ppm). During each growing period four harvests were carried out and total and marketable yield (fruits weighting <1 kg or visually rotten were not considered), fruit average weight and fruit number per plant were determined. At the end of the crop cycle, four plants per treatment were sampled and the nutrient content (N, P and K) was determined. Soil samplings (0-30 cm depth) were carried before the application of compost and at the end of each growing season and available N and P, as well as exchangeable K content were analyzed. With this information, an integrated analysis was carried out with the aim to evaluate the suitability of this compost as organic amendment.

Ground and airborne level optical sensors: is it possible to estimate maize crop N status?

Adjusting N fertilizer application to crop requirements is a key issue to improve fertilizer efficiency, reducing unnecessary input costs to farmers and N environmental impact. Among the multiple soil and crop tests developed, optical sensors that detect crop N nutritional status may have a large potential to adjust N fertilizer recommendation (Samborski et al. 2009). Optical readings are rapid to take and non-destructive, they can be efficiently processed and combined to obtain indexes or indicators of crop status. However, other physiological stress conditions may interfere with the readings and detection of the best crop nutritional status indicators is not always and easy task. Comparison of different equipments and technologies might help to identify strengths and weakness of the application of optical sensors for N fertilizer recommendation. The aim of this study was to evaluate the potential of various ground-level optical sensors and narrow-band indices obtained from airborne hyperspectral images as tools for maize N fertilizer recommendations. Specific objectives were i) to determine which indices could detect differences in maize plants treated with different N fertilizer rates, and ii) to evaluate its ability to identify N-responsive from non-responsive sites.

The impact of large-scale circulation patterns on summer crop in Iberian Peninsula

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5).

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

Designing new cereal cultivars as an adaptation measure using crop model ensembles

To date, crop models have been little used for characterising the types of cultivars suited to a changed climate, though simulations of altered management (e.g. sowing) are often reported. However, in neither case are model uncertainties evaluated at the same time.

Improving Crop Models: Incorporating New Processes, New Approaches, and Better Calibrations

Early ancestors of crop simulation models (De Wit, 1965; Monteith, 1965; Duncan et al., 1967) were born before primitive personal computers were available (e.g. Apple II released in 1977, IBM PC released in 1981). Paleo-computer programs were run in mainframes with the support of punch cards. As computers became more available and powerful, crop models evolved into sophisticated tools summarizing our understanding of how crops operate. This evolution was triggered by the need to answer new scientific questions and improve the accuracy of model simulations, especially under limiting conditions.

Model inter-comparison on crop rotation effects ? an intermediate report

Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions.

Testing of crop Models for Accurate Predictions of Evapotranspiration and crop Water Use

All crop models, whether site-specific or global-gridded and regardless of crop, simulate daily crop transpiration and soil evaporation during the crop life cycle, resulting in seasonal crop water use. Modelers use several methods for predicting daily potential evapotranspiration (ET), including FAO-56, Penman-Monteith, Priestley-Taylor, Hargreaves, full energy balance, and transpiration water efficiency. They use extinction equations to partition energy to soil evaporation or transpiration, depending on leaf area index. Most models simulate soil water balance and soil-root water supply for transpiration, and limit transpiration if water uptake is insufficient, and thereafter reduce dry matter production. Comparisons among multiple crop and global gridded models in the Agricultural Model Intercomparison and Improvement Project (AgMIP) show surprisingly large differences in simulated ET and crop water use for the same climatic conditions. Model intercomparisons alone are not enough to know which approaches are correct. There is an urgent need to test these models against field-observed data on ET and crop water use. It is important to test various ET modules/equations in a model platform where other aspects such as soil water balance and rooting are held constant, to avoid compensation caused by other parts of models. The CSM-CROPGRO model in DSSAT already has ET equations for Priestley-Taylor, Penman-FAO-24, Penman-Monteith-FAO-56, and an hourly energy balance approach. In this work, we added transpiration-efficiency modules to DSSAT and AgMaize models and tested the various ET equations against available data on ET, soil water balance, and season-long crop water use of soybean, fababean, maize, and other crops where runoff and deep percolation were known or zero. The different ET modules created considerable differences in predicted ET, growth, and yield.

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.

Location of bioelectricity plants in the Madrid Community based on triticale crop: a multicriteria methodology

This paper presents a work whose objective is, first, to quantify the potential of the triticale biomass existing in each of the agricultural regions in the Madrid Community through a crop simulation model based on regression techniques and multiple correlation. Second, a methodology for defining which area has the best conditions for the installation of electricity plants from biomass has been described and applied. The study used a methodology based on compromise programming in a discrete multicriteria decision method (MDM) context. To make a ranking, the following criteria were taken into account: biomass potential, electric power infrastructure, road networks, protected spaces, and urban nuclei surfaces. The results indicate that, in the case of the Madrid Community, the Campiña region is the most suitable for setting up plants powered by biomass. A minimum of 17,339.9 tons of triticale will be needed to satisfy the requirements of a 2.2 MW power plant. The minimum range of action for obtaining the biomass necessary in Campiña region would be 6.6 km around the municipality of Algete, based on Geographic Information Systems. The total biomass which could be made available in considering this range in this region would be 18,430.68 t.

Use of tomato and cucumber horticulture by-products in goat diets: effects o nrumen fermentation and microbial communities in batch and continuous cultures

Two in vitro experiments were conducted to analyse the effects of replacing dietary barley grain with wastes of tomato and cucumber fruits and a 1 : 1 tomato : cucumber mixture on rumen fermentation characteristics and microbial abundance. The control (CON) substrate contained 250 g/kg of barley grain on a dry matter (DM) basis, and another 15 substrates were formulated by replacing 50, 100, 150, 200 or 250 g of barley grain/kg with the same amount (DM basis) of tomato or cucumber fruits or 1 : 1 tomato : cucumber mixture. In Expt 1, all substrates were incubated in batch cultures with rumen micro-organisms from goats for 24 h. Increasing amounts of tomato, cucumber and the mixture of both fruits in the substrate increased final pH and gas production, without changes in final ammonia-nitrogen (NH3-N) concentrations, substrate degradability and total volatile fatty acid (VFA) production, indicating that there were no detrimental effects of any waste fruits on rumen fermentation. Therefore, in Expt 2 the substrates including 250 g of waste fruits (T250, C250 and M250 for tomato, cucumber and the mixture of both fruits, respectively) and the CON substrate were incubated in single-flow continuous-culture fermenters for 8 days. Total VFA production did not differ among substrates, but there were differences in VFA profile. Molar proportions of propionate, isobutyrate and isovalerate were lower and acetate : propionate ratio was greater for T250 compared with CON substrate. Fermentation of substrates containing cucumber (C250 and M250) resulted in lower proportions of acetate, isobutyrate and isovalerate and acetate : propionate ratio, but greater butyrate proportions than the CON substrate. Carbohydrate degradability and microbial N synthesis tended to be lower for substrates containing cucumber than for the CON substrate, but there were no differences between CON and T250 substrates. Abundance of total bacteria, Fibrobacter succinogenes and Ruminococcus flavefaciens, fungi, methanogenic archaea and protozoa were similar in fermenters fed T250 and CON substrates, but fermenters fed C250 and M250 substrates had lower abundances of R. flavefaciens, fungi and protozoa than those fed the CON substrate. Results indicated that tomato fruits could replace dietary barley grain up to 250 g/kg of substrate DM without noticeable effects on rumen fermentation and microbial populations, but the inclusion of cucumber fruits at 250 g/kg of substrate DM negatively affected some microbial populations as it tended to reduce microbial N synthesis and changed the VFA profile. More studies are needed to identify the dietary inclusion level of cucumber which produces no detrimental effects on rumen fermentation and microbial growth.

Multicriteria decision analysis applied to cover crop species andcultivars selection

Cover crop selection should be oriented to the achievement of specific agrosystem benefits. The covercrop, catch crop, green manure and fodder uses were identified as possible targets for selection. Theobjective was to apply multi-criteria decision analysis to evaluate different species (Hordeum vulgareL., Secale cereale L., ×Triticosecale Whim, Sinapis alba L., Vicia sativa L.) and cultivars according to theirsuitability to be used as cover crops in each of the uses. A field trial with 20 cultivars of the five specieswas conducted in Central Spain during two seasons (October?April). Measurements of ground cover, cropbiomass, N uptake, N derived from the atmosphere, C/N, dietary fiber content and residue quality werecollected. Aggregation of these variables through utility functions allowed ranking species and cultivarsfor each usage. Grasses were the most suitable for the cover crop, catch crop and fodder uses, while thevetches were the best as green manures. The mustard attained high ranks as cover and catch crop the firstseason, but the second decayed due to low performance in cold winters. Mustard and vetches obtainedworse rankings than grasses as fodder. Hispanic was the most suitable barley cultivar as cover and catchcrop, and Albacete as fodder. The triticale Titania attained the highest rank as cover and catch crop andfodder. Vetches Aitana and BGE014897 showed good aptitudes as green manures and catch crops. Thisanalysis allowed comparison among species and cultivars and might provide relevant information forcover crops selection and management.

Quantitative characterization of five cover crop species

The introduction of cover crops in the intercrop period may provide a broad range of ecosystem services derived from the multiple functions they can perform, such as erosion control, recycling of nutrients or forage source. However, the achievement of these services in a particular agrosystem is not always required at the same time or to the same degree. Thus, species selection and definition of targeted objectives is critical when growing cover crops. The goal of the current work was to describe the traits that determine the suitability of five species (barley, rye, triticale, mustard and vetch) for cover cropping. A field trial was established during two seasons (October to April) in Madrid (central Spain). Ground cover and biomass were monitored at regular intervals during each growing season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment, carbon (C), nitrogen (N), and fibre (neutral detergent, acid and lignin) contents, and the N fixed by the legume were determined. The grasses reached the highest ground cover (83–99%) and biomass (1226–1928 g/m2) at the end of the experiment. With the highest C:N ratio (27–39) and dietary fibre (527–600 mg/g) and the lowest residue quality (~680 mg/g), grasses were suitable for erosion control, catch crop and fodder. The vetch presented the lowest N uptake (2·4 and 0·7 g N/m2) due to N fixation (9·8 and 1·6 g N/m2) and low biomass accumulation. The mustard presented high N uptake in the warm year and could act as a catch crop, but low fodder capability in both years. The thermal time before reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crop selection and management.

Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.