Prototype decision support system based on the VegSyst simulation ...

Irrig Sci (2014) 32:237–253 DOI 10.1007/s00271-014-0427-3

Original Paper

Prototype decision support system based on the VegSyst simulation model to calculate crop N and water requirements for tomato under plastic cover M. Gallardo · R. B. Thompson · C. Giménez · F. M. Padilla · C. O. Stöckle 

Received: 4 June 2013 / Accepted: 24 January 2014 / Published online: 8 February 2014 © Springer-Verlag Berlin Heidelberg 2014

Abstract  The simulation model VegSyst was calibrated and validated for tomato grown under plastic cover. Calibration was conducted with an autumn–winter soil-grown crop, and validation with five crops with differences in season, cropping media, and site. VegSyst accurately simulated daily dry matter production (DMP), N uptake, and ETc. Comparing simulated and measured values by linear regression, slope and intercept values were not statistically significantly different (P 300 mg NO3− L−1 in a number of wells (Dominguez Prats 2013). The areas where greenhouses are concentrated have been declared nitrate vulnerable zones (Anon. 2008), in accordance with the EU Nitrate Directive (Anon. 1991), and consequently, the growers are required to substantially reduce NO3− leaching losses (Anon. 1991). This agricultural system, based on relatively simple plastic greenhouses known as “Mediterranean greenhouses,” is expanding rapidly throughout the Mediterranean Basin (Castilla 2002; Castilla et al. 2004; Pardossi et al. 2004)

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and in Central America (Castilla et al. 2004; Pardossi et al. 2004). Additionally, there is an estimated 1 M ha of simple plastic greenhouses in China (Dr. N. Castilla IFAPA Granada personal communication), which are also associated with considerable NO3− contamination of aquifers (Ju et al. 2006). The Mediterranean greenhouse system of SE Spain has an advanced technical capacity for precise nutrient and irrigation management. Soil-grown crops are commonly grown with combined drip irrigation and automatically controlled fertigation systems that apply N and other nutrients in all irrigations (Céspedes et al. 2009; Thompson et al. 2007; Granados et al. 2013). High-frequency drip irrigation applying specified N concentrations provides growers with the technical capacity to “spoon feed” both N and irrigation to crops as they are required. However, conventional N and irrigation management are based on collective experience using fixed recipes (Thompson et al. 2007), and this potential for precise N and irrigation management is not being exploited. Practical on-farm management tools are required to enable growers to fully exploit this technical capacity for precise N and irrigation management. Key requirements for optimal N management are to match the supply of mineral N fertilizer to the N demand of the crop (Meisinger et al. 2008a) and to consider all sources of N to avoid an excessive N supply (Meisinger et al. 2008a). Within greenhouses, where no rainwater enters and soils remain at close to field capacity, irrigation requirements can be largely based on crop evapotranspiration (ETc) (Gallardo et al. 2013). A very useful tool for this system would be a practical decision support system (DSS) that provides daily plans of both N fertilizer and irrigation requirements that respond to variations in factors such as climatic conditions, planting dates, length of growing period, and greenhouse design and construction. The most effective way to deal with the appreciable variation and interaction of these multiple factors is for the DSS to be based on a crop simulation model that calculates daily N uptake and daily ETc based on climatic conditions inside the greenhouse. The DSS will require supplementary components to calculate (a) N fertilizer requirements, based on crop N uptake, considering other N sources and the efficiency (percentage recovery by crop) of N use, and (b) gross irrigation requirements, based on ETc, considering irrigation uniformity and salinity. To be suitable for onfarm use, the DSS must have a small number of inputs of data that are readily available to growers or technical advisors (Thompson et al. 1997; Parneaudeau et al. 2009). A suggested approach to achieve this is to use a mechanistic simulation model to calculate daily crop N uptake and ETc and to use an empirical approach for the supplementary components. The empirical supplementary components

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would offer options to users while providing default values. This mixed mechanistic-empirical approach would enable the DSS to have the limited number of readily available inputs required for on-farm use (Parneaudeau et al. 2009), while providing the capacity to respond dynamically to variations in cropping conditions (Parneaudeau et al. 2009). The on-site data requirements would be those required by the model component to calculate crop N uptake and ETc, and the supplementary components would require the selection of values from a short menu. An additional requirement of a practical DSS for N and irrigation management in Mediterranean greenhouses is to provide recommendations for both soil- and substrate-grown vegetable crops. In greenhouses in Almeria, approximately 80 % of the cropped area is in soil and 20 % is in substrate (Céspedes et al. 2009; Thompson et al. 2013a). VegSyst is a crop simulation model driven by thermal time that calculates daily crop biomass production, N uptake, and ETc for vegetable crops (Gallardo et al. 2011; Giménez et al. 2013). Being driven by thermal time, VegSyst is adaptable to the variations in climate, crop management, and greenhouse type mentioned previously. The VegSyst model assumes that crops have no water or nutrient limitations; in commercial production in this system, N supply and irrigation are both generally excessive to crop requirements, particularly N (Thompson et al. 2007, 2013a; Jadoski et al. 2013). VegSyst has previously been calibrated and validated for greenhouse-grown sweet pepper (Giménez et al. 2013) and muskmelon (Gallardo et al. 2011). Several DSS based on simulation models have been developed in Europe to assist with N fertilization, e.g., WELL_N (Rahn et al. 1996), EU-Rotate_N (Nendel 2009; Rahn et al. 2010), N-Expert (Fink and Scharpf 1993), Azodyn (Jeuffroy and Recous 1999), and Azofert (Parneaudeau et al. 2009). These DSS have been developed for open field crops and mostly for northern European conditions. Generally, they do not calculate irrigation requirements, and most are not suitable for high-frequency N application by combined fertigation and drip irrigation. Large data requirements of more mechanistic DSS limit on-farm adoption (Parneaudeau et al. 2009). Therefore, there is a requirement to develop a grower-friendly DSS for both N and irrigation, with limited inputs, for vegetable crops in Mediterranean greenhouses. Tomato is the most important crop, in terms of area, in the greenhouse-based vegetable production system of SE Spain (Consejería de Agricultura y Pesca 2011). It is grown in both soil and substrate. Two growing cycles are used: (1) an autumn–winter cycle commonly from August to February, and (2) a spring cycle, commonly from February/ March to June. The present work consists of four components. Firstly, the VegSyst simulation model was calibrated and validated

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for tomato grown in greenhouses in SE Spain. The validation considered different growing cycles (autumn–winter or spring), different growing media (soil or substrate), and different greenhouses and sites. Secondly, the VegSyst model was incorporated into a DSS, known as VegSyst-DSS in which empirical components calculate (a) crop mineral N fertilizer requirements based on simulated crop N uptake, and (b) crop water requirements based on simulated ETc considering salinity and irrigation application uniformity. Thirdly, the VegSyst-DSS was used to conduct a scenario analysis to demonstrate how N fertilizer application rate and the applied N concentration in the nutrient solution varied in response to consideration of the various sources of soil N under a range of representative cropping conditions for greenhouse vegetable production in SE Spain. Fourthly, sensitive analyses were conducted to assess the effect of changes in the values of efficiencies of N use of all N sources on model output.

Materials and methods The VegSyst model: calibration and validation VegSyst was calibrated for tomato (Solanum Lycopersicum L.) using experimental data from a tomato crop grown in 2009–2010 in soil with an autumn–winter growing season. Validation of the model was conducted with data from five different tomato crops, three grown in soil (two in spring and one in autumn–winter), and two tomato crops grown in an artificial substrate (one in autumn– winter, and the other in spring). All crops were grown in greenhouses. Descriptions of the calibration and validation crops are provided in Table 1. The greenhouses, soil, and crop management practices are more fully described

subsequently. Detailed descriptions of the VegSyst model are available in Gallardo et al. (2011) and Giménez et al. (2013). A schematic diagram of the model is included in Fig. 1. The calibration parameters are listed in Table 2. VegSyst simulates the fraction of intercepted photosynthetically active radiation (PAR) (fi-PAR) from thermal time, that is calculated using lower and upper temperature threshold values of 10 and 40 °C for tomato (Fernández et al. 2001). Daily PAR interception (PARi) was calculated as the product of daily values of fi-PAR and the daily sum of PAR inside the greenhouse, calculated from the measurement of solar radiation (SR) inside the greenhouse, considering that the ratio PAR/SR for plastic greenhouses is 0.43 (Cabrera 2010). The maximum fraction of intercepted PAR (ff-PAR) and the fraction of intercepted PAR at maturity (fmat-PAR) were both 0.73 (Table 2). Above-ground dry matter production (DMP) for a given day (DMPi) was calculated as the product of daily PAR interception and the radiation-use efficiency (RUE). The optimized value of seasonal radiation-use efficiency (RUE) obtained from the data of PAR interception and DMP was 4.01 g MJ−1 PAR (Table 2). Crop N uptake for a given day was determined as the product of DMPi and the simulated crop N content (%Ni) for that day calculated as follows:

%Ni = a × TDMbi

(1)

where a and b are calibration factors (Giménez et al. 2013; Table  2); these coefficients were determined from data of a broader study including four treatments of different rates of applied N in the calibration crop of 2009–2010 following the methodology of Tei et al. (2002). ETc was calculated following the FAO approach (Allen et al. 1998) as the product of reference evapotranspiration (ETo) and a crop

Table 1  Descriptions of the tomato crops used for calibration and validation Cropping media/ growing season/year

Location

Date of transplanting

Date of end of crop

Total irrigation volume (mm)b

Average N concentration of nutrient solution (mmol L−1)c

Total N applied (kg N ha−1)b

Soil-spring 2008 Soil-winter 2009a Soil-winter 2010 Soil-spring 2011 Substrate-spring 2005

GH1 GH1 GH1 GH1 GH2

January 10, 2008 September 15, 2009 August 5, 2010 March 14, 2011 March 7, 2005

June 20, 2008 March 15, 2010 January 24, 2011 July 14, 2011 July 7, 2005

418 256 282 240 357

12.0 12.4 13.6 13.4 9.6

701 319 490 425 479

Substrate-winter 2005

GH2

September 20, 2005

March 2, 2006

235

11.5

379

For each crop, dates of transplanting and end of crop, total volume of irrigation applied, N concentration of nutrient solution, and total amount of N applied. GH1 is greenhouse 1, and GH2 is greenhouse 2; both greenhouses are fully described in “Materials and methods” a

  Crop used for calibration

b

  Total N and total irrigation applied correspond to the complete cropping cycle

c

 N concentration values are for the period of N treatments, which commenced 20, 40, 25, and 25 days after transplanting in the 2008, 2009, 2010, and 2011 soil-grown crops; in substrate-grown crops, the N concentration is for the entire crop

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Fig. 1  Schematic diagram of the VegSyst-DSS decision support system showing the calculations made by (1) the VegSyst simulation model component and (2) the DSS component. The simulations made by VegSyst model are enclosed in the box formed by the dotted line. The calculations made by the DSS component are enclosed in the

box formed by the broken and dotted line. Parameters within ovals at the top are inputs. Parameters enclosed in solid rectangles, within the two boxes, are intermediate calculations. Parameters enclosed in rectangles formed by broken lines, at the bottom, are the outputs of the VegSyst-DSS

coefficient value (kc). ETo was calculated using the Penman–Monteith equation adapted for Mediterranean-type plastic greenhouses with a fixed aerodynamic resistance of 295 s cm−1 (Fernández et al. 2010, 2011). kc for a given day (kci) was calculated as follows:

intervals at P