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Author(s)

First Name / Middle Name / Surname / Role / Email
David / H / Fleisher / ASABE member /

Affiliation

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USDA-ARS / 10300 Baltimore Avenue / Beltsville, MD 20705 / USA

Author(s) – repeat Author and Affiliation boxes as needed--

First Name / Middle Name / Surname / Role / Email
Dennis / J / Timlin / Coauthor /

Affiliation

Organization / Address / Country
USDA-ARS / 10300 Baltimore Avenue / Beltsville, MD 20705 / USA

Author(s) – repeat Author and Affiliation boxes as needed--

First Name / Middle Name / Surname / Role / Email
Yang / Yang / ASABE member /

Affiliation

Organization / Address / Country
University of Maryland / Wye Research and Education Center, University of Maryland, Queenstown, MD / USA

Author(s) – repeat Author and Affiliation boxes as needed--

First Name / Middle Name / Surname / Role / Email
V.R. / Reddy / Coauthor /

Affiliation

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USDA-ARS / 10300 Baltimore Avenue / Beltsville, MD 20705

Publication Information

Pub ID / Pub Date
073013 / 2007 ASABE Annual Meeting Paper

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An ASABE Meeting Presentation

Paper Number: 073013

Simulation of Potato Gas Exchange Using SPUDSIM

David H. Fleisher

Crop Systems and Global Change, USDA-ARS, Beltsville, MD 20705 USA

Dennis J. Timlin

Crop Systems and Global Change, USDA-ARS, Beltsville, MD 20705 USA

Yang Yang

Wye Research and Education Center, University of Maryland, Queenstown, MD

V.R. Reddy

Crop Systems and Global Change, USDA-ARS, Beltsville, MD 20705 USA

Written for presentation at the

2007 ASABE Annual International Meeting

Sponsored by ASABE

Minneapolis Convention Center

Minneapolis, Minnesota

17 - 20 June 2007

Abstract. SPUDSIM is a new potato model derived from an older USDA-ARS model, SIMPOTATO, developed to incorporate new advances in the knowledge of plant growth and development. Modifications incorporated in SPUDSIM focus at simulating canopy growth and development at the individual leaf level and include routines for individual leaf appearance rates and leaf expansion as a function of leaf physiological age and plant assimilate status. Coupled sub-models for leaf level photosynthesis, transpiration, and stomatal conductance were used to replace the older radiation use efficiency approach. A radiative transfer routine that estimates intercepted photosynthetically active radiation for sunlit and shaded leaves was also added. During each time increment, net photosynthetic rate is estimated for sunlit and shaded leaf area. Photosynthate is partitioned among leaves in the canopy according to leaf age, potential expansion, and plant assimilate status. Assimilate allocation to branches, roots, and tubers proceeds according to fixed partitioning coefficients defined in SIMPOTATO. Remaining photosynthate is used to support the appearance of new leaves or branches in the canopy according to predicted demand. Whole plant gas exchange and harvest data from SPAR (soil-plant-atmosphere research) chamber experiments conducted at USDA-ARS Beltsville, MD were used to evaluate SPUDSIM predictions. Results indicate that SPUDSIM accurately captures potato growth and developmental responses over a wide range of temperatures and will be suitable for a variety of applications involving complex soil-plant-atmospheric system relationships.

Keywords. Potato, Models, Simulation, Decision Support, Photosynthesis, Gas Exchange

Introduction

The United States is the 5th largest potato growing country in the world, producing 19.7 million metric tons on 453,000 ha in 2006 (USDA, 2007). As with other agricultural crops, there are significant risks and challenges involved in potato production due to uncertainties with climate, pests, and other pressures. As operations increase in size and complexity, farmers are required to manage, interpret, and make decisions upon large amounts of information. Fluctuating market prices, costs of fertilizers, pesticides and irrigation, environmental impact concerns from agricultural practices, land-use pressures, and projected climate change factors create additional demands on farmers, crop consultants, policy planners and scientists. Over the past 40 years, mechanistic, process level computer models have been developed that attempt to mimic crop responses to climatic and management factors. Complex, mechanistic crop models are needed to encapsulate knowledge on the soil-plant-atmosphere system, test hypotheses, evaluate the behavior of complex agricultural systems, and study alternative production scenarios under different climactic, management, and geographic locations (Reddy and Reddy, 1998). These models are typically integrated with computerized decision support systems to help manage and interpret large amounts of complex information in order to help farmers reduce risk (Uehara and Tsuji, 1998; Timlin et al., 2002; Wang et al., 2002). However, many crop models are still at an early stage of development and do not necessarily include state-of-the-art science due to (a) lack of perceived need to incorporate this new information, (b) lack of resources, or (c) other knowledge gaps that prevent adoption of new research in the models. By including this new information into the models, more reliable predictions of growth and development in response to climactic and nutritional stresses can be obtained.

Potato models generally simulate crop growth and development by using a ‘big-leaf’ approach. Increases in total canopy leaf area are based on inputs for environment and plant nutritional status (e.g. International Benchmark Sites Network for Agrotechnology Transfer, 1993; Kooman and Haverkort, 1995; Hodges et al., 1992; Shaykewich et al., 1998). Daily gains in plant dry weight are obtained by multiplying an estimate for canopy light interception (based on leaf area) by a conversion factor known as radiation use efficiency (RUE, g carbohydrate (CHO) MJ-1 daily intercepted radiation). This value can be reduced by additional empirical factors that approximate limiting effects of plant nutritional status, water content, and temperature on growth rate. Conceptual carbon (C) pools for total leaf and stem dry mass are then computed through the use of empirical partitioning coefficients as opposed to predicting individual leaf appearance, expansion, and duration. RUE based models are popular and have been successfully applied to a variety of studies for many crops. However, factors such as leaf nitrogen content, water stress, senescence, elevated [CO2] and rising air temperatures play significant roles in influencing plant photosynthetic rate at daily and shorter time-scales, and cannot be mechanistically accounted for with an RUE approach (Demetriadeshah et al., 1992, 1994). In addition, such an approach can over-estimate daily growth rate due to the nonlinearity of leaf response to light (Thornley, 2002).

Over the past few years, a new potato model, SPUDSIM, has been developed. SPUDSIM is based on a series of modifications to an older ARS potato model, SIMPOTATO (also known as SIMGUI), that follows the general RUE based modeling approach outlined above (Hodges et al., 1992). These modifications primarily focus on replacing RUE and big-leaf method to simulate canopy growth and development with an individual leaf level approach. Modifications include simulation of individual leaf appearance on different stems in the canopy (Fleisher et al, 2006a), individual leaf expansion as a function of leaf physiological age and plant assimilate status (Fleisher and Timlin, 2006), and incorporation of a leaf-level coupled model for photosynthesis, transpiration, and stomatal conductance (Soo and Lieth, 2003). This paper focuses on the details of these modifications, provides preliminary comparison between model predictions with experimental gas exchange data, and discusses the future modifications planned for the model.

Materials and Methods

i. Data

The majority of new modifications incorporated in SPUDSIM come from experiments conducted in daylit soil-plant-atmosphere research (SPAR) chambers at USDA-ARS facilities in Beltsville, MD in 2003 through 2006. Data from field studies and literature have been used to validate modeling sub-components where appropriate. Daylit SPAR chambers were constructed from clear acrylic, transparent to natural sunlit, had a 1 m2 cross-sectional area, and a total chamber volume of 3360 L. Air temperature and relative humidity were monitored and controlled with TC2 controllers (Environmental Growth Chambers, Ohio USA). A dedicated Sun SPARC5 work station (Sun Microsystems, Mountainview, CA) logged environmental data (air and soil temperatures, atmospheric CO2 concentration ([CO2]), and photosynthetically active radiation (PAR, in µmol m-2 s-1)) every 300 s. Mass flow controllers in each chamber were used to maintain [CO2] at desired levels during the day. Each chamber has a dedicated infrared gas analyzer, permitting continuous monitoring of whole plant carbon dioxide fluxes at 5 minute intervals during the course of the season. This permits calculation of gross and net canopy photosynthetic rates. Additional details on SPAR chamber operation and related calculations can be found in Reddy et al., (2001).

ii. SPUDSIM

SPUDSIM contains most of the same phenological components and carbon allocation routines as the original SIMPOTATO model. SPUDSIM was coded in C++ and runs on an hourly time-step. The model has been integrated with 2DSOIL, a modular, comprehensive two-dimensional soil simulator that is specifically designed to be integrated with existing crop models (Timlin et al., 1996). 2DSOIL modules can simulate water, solute, heat and gas movement as well as plant root activity in a two-dimensional profile. Coupling SPUDSIM with 2DSOIL allows simulation of the soil-plant-atmosphere continuum.

The basic weather data needed to run SPUDSIM include daily solar radiation, maximum and minimum temperature, relative humidity and rainfall. Management inputs include planting and emergence date, planting density and depth, seed reserve at planting, row spacing, cultivar, amount, type and incorporation depth of crop residue, and in-season fertilization and irrigation information. Soil inputs include initial, saturated, wilting and upper limit of field capacity volumetric water contents, mineral ammonium and nitrate concentrations, and soil pH of each user defined soil horizon.

At each time-step, SPUDSIM reads in the appropriate input data and simulates plant development, gas exchange, carbon allocation, and organ initiation as indicated in Figure 1. Routines that are different between SPUDSIM and SIMPOTATO are shaded. The model keeps iterating until either harvest date, maturity date, or other user-specified end point is reached. The frequency and type of model outputs can be specified by the user and include, but are not limited to, dry weights of all organs, transpiration, photosynthetic rate, assimilate status, leaf and lateral branch numbers, and leaf area index.

iii. Modifications

a. Leaf appearance rate

Data from the literature (Kirk and Marshall, 1992) and daylit SPAR and field experiments were used to model leaf appearance rates on potato mainstem and lateral branches as detailed in Fleisher et al. (2006a). Rates followed a nonlinear response with temperature and were modeling using a modified β distribution function (Yan and Hunt, 1999), and take the form shown in equation (1). Rates accumulate at an hourly basis in SPUDSIM using the previous 24 h average air temperature (°C).

(1)
where:
r – leaf appearance rate (leaves plant-1 day-1)
Rmax – maximum leaf appearance rate (leaves plant-1 day-1); 0.96
Tmax – ceiling temperature where r = 0; 39.5°C
Topt – optimum temperature where r = Rmax; 27.2°C
T – average daily temperature from previous 24 h (°C)

A comparison with experimental data is shown in Figure 2. As implemented in the model, leaves can appear on any lateral or mainstem branch – i.e., each branch accumulates leaf appearance rate separately, as long as there is sufficient plant assimilate supply to support the new organ. The appearance of lateral branches is assumed to have the same temperature response.

b. Leaf expansion

Individual leaf expansion rate was modeled using a modification of an organ expansion routine introduced by Ng and Loomis (1984). The routine simulates individual leaf expansion primarily as a function of genetic potential and temperature, with external factors for nutrient, water, and plant assimilate supplies limiting the expansion (Fleisher and Timlin, 2006):