Environmental risk assessment of blight resistant potato: use of a crop model to quantify

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1 Environmental risk assessment of blight resistant potato: use of a crop model to quantify nitrogen cycling at scales of the field and cropping system Online Resource 1. Summary of the model Journal: Environmental Science and Pollution Research Authors: Mark W. Young 1, Ewen Mullins 2, Geoffrey R. Squire 1 1 Ecological Sciences, James Hutton Institute, Dundee DD2 5DA, UK 2 Teagasc Crops, Environment and Land Use Programme, Oak Park Crops Research Centre, Carlow, Ireland Corresponding author: G R Squire geoff.squire@hutton.ac.uk Acknowledgements This work was conducted during the AMIGA project funded by the European Commission as a Large-scale Integrating Project within FP7 under grant agreement n o Introduction The crop model used here is primarily a tool to extend the limited data on yield from small plot trials to other plant attributes, to facilitate comparison between sites and treatments, and from that to identify and quantify risk to the environment due to (in this instance) return of nitrogen to the field at and before harvest. References below are given in the list of references in the main text of the paper. The approach is a continuation and adaptation of that presented and tested by The James Hutton Institute, and its forerunner the Scottish Crop Research Institute, by MacKerron & Waister (1985), MacKerron (1985), Jefferies & MacKerron (1989) and Jefferies & Heilbron (1995). The three main components of the basic model are development of a canopy surface that captures solar radiation (MJ m -2 ), conversion of captured solar radiation to dry matter (g m -2 ) through a conversion coefficient (g MJ -1 ) and partition of the total dry matter among structures such as root, tuber, leaf, stem and grain as appropriate. The approach is extended here to incorporate uptake and partition of nitrogen (N) and limitation due to foliar destruction by the disease late blight. Model parameters for the processes discussed below are summarised for potato in Table OR1.1. Examples of daily weather input and representative output for the resistant and susceptible crops shown in Fig. 3 of the main text are given in Online Resource 2. 1

2 fractional interception Si (MJ m -2 ) Interception, conversion and partition with minimum limitation The fraction of solar radiation intercepted by a crop canopy (f) was determined from thermal time (Ø) using the generic equations in Marshall et al. (1992): f = c/[1+exp{-b(ø-m)}] (Table OR1.1 gives parameter values). Thermal time is calculated as cumulative temperature above a base temperature, where mean temperature is the mean of maximum and minimum recorded at a met site. Estimates of the base temperature above which potato develops and produces a canopy are typically between and 4 o C in different studies (Squire 1995). Here, for consistency a single base of o C is assumed throughout. In an Atlantic zone environment, a potato crop with a duration of 6 months growth typically intercepts around 15 MJ -1 total solar radiation (Fig. OR1.1) time from 1 January (d) Fig. OR1.1 Time course of (continuous line) fractional interception of total solar radiation and (dashed line) cumulative solar radiation capture (Si) based on weather at the trial site; the crop is desiccated just before harvest, causing fractional interception to fall to zero. The conversion coefficient, dry matter per unit solar radiation intercepted (g MJ -1 ) typically varies between 1 and 2 g MJ -1 during maximum growth of C3 crops but commonly falls below the lower value when averaged from emergence to harvest. In the environments used in this paper, temperature during the growth of potato mostly ranged between 5 and 15 o C, over which range the coefficient was assumed vary little, but was adjusted for temperature using the relation in Marshall et al. (1992) scaled for temperate crops. For the 2

3 dry matter (t ha -1 ) purpose of this paper, the value of the coefficient is regulated in the model to ensure that dry matter and nitrogen content were balanced, such as that %N is plant tissue remained within bounds measured in the field (i.e. mostly 1-2% total plant dry matter. The mechanism is described in the section on nitrogen below. The modelled dry matter and yield for the blight resistant condition under the weather at the trial site are given in Fig. OR1.2. Partition equations for tuber yield are described later time from 1 January (d) Fig. OR1.2 Time course of (continuous line) total plant and (dashed line) tuber production based on weather at the experimental site. Dry matter (DM) partitioning coefficients were derived empirically from extensive field trials on the relation between nitrogen fertiliser, growth and yield at the James Hutton Institute (e.g. MacKerron et al. 1993). Four compartments are quantified here: leaf, stem, root and tubers. The first three partitions are always present; that for tubers arises at a specified a point during the growing season (Fig. OR1.2). The relations are described by logistic equations of the form: p = m log(w)+c, where p is the fraction or percentage of dry matter in the respective compartment (leaf, root, stem, tuber) and W is total plant dry matter (Fig. OR3). Values of m and c for compartments before after the start of tuber formation are given in Table OR1.1. 3

4 partition (%) 8 7 T 6 5 L 4 3 R 2 1 S total dry matter (t/ha) Fig. OR1.3 Partition of total dry matter into percentage fractions for tuber (T), leaf (L), root (R) and stem (S) using functions in Table OR1.1. Nitrogen uptake and concentration A range of attributes vary with the amount of nitrogen made available as fertiliser. The relations are complex, and are represented in the blight trial by reference to the results of field trials in which nitrogen input was varied and the crops responses measured (MacKerron et al. 1993). In that work, the rate of N uptake and %N by mass were maximal in early growth then fell sharply during tuber bulking; while the rate, % and final N-uptake all increased with added fertiliser over the range to >2 kg ha -1. The dynamics of the plant attributes therefore depend much on the N-available. At the blight trial site (model output shown Fig. 3, Table 1 main text), N-fertiliser was 87.5 kg ha-1 and (in the absence of information) an additional residual of 25 kg ha -1 nitrogen was assumed. A total N- available of kg ha -1 does not match exactly any of the input-rates in MacKerron et al. (1993), but the nearest treatment (average of two cultivars) indicate maximum uptake of 1.84 kg ha -1 d -1 (measured over a 2-day period), which fell to zero part way through bulking, and a maximum %N of 5.4% falling to around 1% during bulking and at harvest, at which point most of the available N was taken up. These data do not allow an accurate description of the decline in uptake rate with either time or N-available as the latter is depleted. Moreover, the relations between uptake and N available in the soil are in principle complex, comprising many attributes not measured in typical agronomic trials (Greenwood & Draycott, 1995; 4

5 N taken up by crop (kg ha -1 ) %N in whole plant Devienne-Barret et al. 2). For the purpose of simulating plant N in this paper, therefore, daily uptake rate (U) is approximated by a single function: U = m log(n-available)-c. The resulting time course of N accumulated by the crop (N-uptake) and %N by mass are shown in Fig. OR4. The time course of %N shows high values around 6% (consistent with field measurements cited) falling rapidly to 2% and then a much slower descent over 1 d to just above 1% as the tubers bulk. The rapid fall in %N is due more to an accelerating rise in dry matter production as f increases, than to fall in daily N uptake at that time time from 1 January (d) Fig. OR1.4. Time course of nitrogen taken up by the crop (dashed line, N-uptake) and %N by mass in the whole plant (continuous line). To estimate maximum return of N to soil around harvest, N taken up by the whole plant is partitioned between N in tubers and N in the rest of the plant. The same extensive data set that was used to estimate dry matter partition functions (Fig. OR1.3) and nitrogen relations (Fig. OR1.4) was used to estimate N partition, for which the parameters are given in Table OR1.1. Proportionate to dry matter, less N is allocated to tubers than to the rest of the plant, such that %N in tubers is lower than that in the whole plant. Balance between dry matter production and nitrogen uptake Nitrogen uptake and dry matter production are indirectly regulated in the model to prevent - for a given fertiliser input - %N and dry matter production moving out of realistic bounds. The regulation occurs through 5

6 the conversion coefficient (g MJ -1 ), described above. The coefficient is set to a maximum of 2.3 g MJ -1, a realistic value in new crop vegetation well supplied with nitrogen. However, such a high level is rarely maintained in practice, and if it was, then unrealistic rates of dry matter production would result, e.g. 23 t ha -1 on only 1 MJ m -2 intercepted radiation. To achieve more realistic long term production, the coefficient is reduced in proportion to the fall in %N below a maximum limit of 5%. So if for example, %N is 2%, the conversion coefficient is reduced to.92 g MJ -1. While expedient, this form of regulation ensured in the simulations that dry matter production, N-uptake and %N all remained within realistic bounds as observed in the field. However, as the dataset analysed by MacKerron et al. (1993) illustrates, these limits shift upwards as fertiliser N is raised. Late Blight In principle, late blight can infect potato foliage in the model at any time stated by the operator. In the absence of preference, the trigger for onset was based on the "temperature-humidity rule" (Beaumont 1947, After a particular date (dependent on geographic location) blight can develop within days following a period when the temperature>1 o C and relative humidity>75% for 2 consecutive days. Potato cultivars differ greatly in susceptibility as defined by Platt and Tai (1988). When re-plotted for this paper, the data in that paper appeared to fall naturally into four groups, distinguished by the rate of leaf destruction. Empirical relations derived from the data in Platt & Tai are given in Table OR1.1. To generate different rates of foliar destruction for Fig. 3 in the main text, the infection of earliest onset was simulated by the most susceptible type, that of intermediate onset by a moderately susceptible type, and that of latest onset by the least susceptible type. As presented here, leaf destruction is quantified by a given loss of fractional interception which has three subsequent effects. It reduces the rate of solar energy capture and hence dry matter production. It feeds back to reduce nitrogen uptake by a fraction directly proportional to the loss of fractional interception. And it is accompanied by a loss of leaf dry matter, and any nitrogen in that leaf, by a mass directly proportional to the loss of fractional interception. Therefore, as soon as blight begins to destroy leaf, it sets back growth and nitrogen uptake in proportion and adds to N return to the soil. 6

7 Cereals and oilseeds in regional crop sequences The growth and yield of these crops is represented through interception, conversion and partition using similar relations and equations as for potato described above. Parameters were derived from empirical data obtained by the Institute in the Atlantic agroecological zone of eastern Scotland. Typical yields, inputs and environments are described in Squire et al. (215) and related papers. For the simulation of crop sequences shown in Fig. 4 of this paper, parameters were adjusted to achieve yields that were within 1% of the mean national grain output for each crop type based on the government s annual yield census for the region. Example of daily weather inputs and modelled outputs for solar energy interception, dry matter production and yield, available nitrogen and nitrogen uptake are given over the six years of each sequence in Fig. 4 in Online Resource 2. Table OR1.1 Values of the principle model parameters used in potato simulations under conditions at the trial site. Attribute (and equation) units of attribute parameter values Solar energy income (S) MJ m -1 input from met records Fractional solar energy interception (f) f = c/[1+exp{-b(ø-m)} fraction between and 1 b =.921 c =.924 m = 18 Thermal time Ø, accumulated temperature (T-T b ) Intercepted solar energy (Si) y = f S o Cd MJ m -1 T, input from met records T b = o C f (as above) S (as above) Conversion coefficient (e) g MJ , maximum.65, typical crop average Dry matter production by whole plant y = Si e Dry matter partition p = m log(w)+c where p is the fraction of dry matter in stated compartment (leaf, stem, etc.) as % of dry matter in whole plant (W) g m -2, kg ha -1 % estimated pre-tuber (leaf, stem, root only) and post-tuber (all four compartments Si (as above) e (as above) pre-tuber leaf % m = 1.9 c = 56.5 pre-tuber stem % m = 2.13 c = 5. Values given for compartments below pre-tuber root % m = -13. c = 38.5 post-tuber leaf % m = c =

8 post-tuber stem % as for pre-tuber post-tuber root % m = -13. c = 38.5 tuber % m = 28.5 c =.98 Nitrogen uptake (daily rate) u = m ln(n-available) c where u is uptake rate and Nitrogen partition between tuber and whole plant y = ax2+bx+c where y is N in tubers as % of N in whole plant and X is dry matter in tubers as % of dry matter in whole plant Blight disease effect - where y is reduction of fractional interception (f) and X is time after onset, for three levels of susceptibility - least susceptible, y = mx2+cx+a kg ha -1 d -1 m =.65 c = 1.4 % a =.79 b =.17 c = 1.52 reduction of f m =.545 C = a = 3.25 intermediate y = mx+c reduction of f m = 2.7 c = 6.45 most susceptible y = cx b reduction of f c = 25.8 b =.48 8