Agronomy Journal 94:345-350 (2002)
© 2002 American Society of Agronomy
MODELING
Timothy Yield and Nutritive Value by the CATIMO Model
II. Digestibility and Fiber
Helge Bonesmoa and
Gilles Bélanger*,b
a Norwegian Crop Res. Inst., Kvithamar Res. Cent., NO-7500 Stjordal, Norway
b Soils and Crops Res. and Dev. Cent., Agric. and Agri-Food Can., 2560 Hochelaga Blvd., Sainte-Foy, QC, Canada G1V 2J3
* Corresponding author (belangergf{at}em.agr.ca)
Received for publication December 4, 2000.
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ABSTRACT
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Growth and nutritive value of forage crops have rarely been integrated into one mechanistic computer simulation model. In a companion paper, we described the growth and N concentration modules of an integrated model of timothy (Phleum pratense L.) primary growth and nutritive value, known as CATIMO (Canadian Timothy Model). In this paper, we describe the digestibility module, which features the cell wall (CW) digestibility and CW concentration for each of the plant morphological components derived from the growth module of the model. The model parameters were calibrated to key model attributes: concentration and digestibility of CW in leaves, stems, and forage and dry matter (DM) digestibility of leaves, stems, and forage. Calibration measurements were taken weekly on timothy primary growth in four different years at one location (Fredericton, NB, Canada). The model satisfactorily fitted the measured values with root mean square errors of estimation (RMSE) of 0.051 g g-1 DM for forage CW concentration, 0.026 g g-1 CW for forage CW digestibility, and 0.018 g g-1 DM for forage DM digestibility. The leaf and stem CW concentration (RMSE 
0.044 g g-1 DM), CW digestibility (RMSE 0.019 g g-1 CW), and DM digestibility (RMSE 0.018 g g-1 DM) were also calculated satisfactorily by the model. The CATIMO model is a promising tool because of its mechanistic and flexible approach and the good agreement between measured and simulated values.
Abbreviations: CW, cell wall • DM, dry matter • IVTD, in vitro true dry matter digestibility • RMSE, root mean square error of estimation
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INTRODUCTION
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UNDERSTANDING THE COMPLEX INTERACTION among plant growth, plant nutritive value, and environmental conditions requires the integration of information derived from experimentation. As well as integrating information and developing knowledge of complex systems, mechanistic computer simulation models can assist in developing site-specific recommendations to optimize harvest yield and nutritive value.
The decrease in the leaf/stem ratio and the increase in the amount of senescent material contributes significantly to the decline of forage digestibility with time (Marten, 1985). The proportions of the morphological components—stems, green leaves, and dead leaves—however, do not entirely account for forage digestibility; respective cell wall (CW) concentration and digestibility of leaves and stems are also factors. Bélanger and McQueen (1999) reported that young grass stems of timothy (Phleum pratense L.) are as digestible as leaves; digestibility declines with age in both fractions, with faster decline in stems.
In a companion paper appearing in this issue of Agronomy Journal, we describe the growth module of the CATIMO model (Bonesmo and Bélanger, 2002). The growth module of the model includes the partitioning of biomass into stems, green leaves, and senescent leaves. This provides the necessary linkage between growth and digestibility. Few models have integrated both growth and nutritive value of forage crops (Fick et al., 1994).
Our overall objective was to develop an integrated model of timothy growth and nutritive value. Our model simulates CW digestibility and CW concentration for each of the plant morphological components derived from the growth module. In this paper, we describe the digestibility module of the integrated model and its calibration.
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MATERIALS AND METHODS
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Field Experiments
Field experiments were conducted on timothy primary growth following winter at the Fredericton Research Centre of Agriculture and Agri-Food Canada (45°55' N lat) in 1991, 1992, 1993, and 1995. In each year, plots were sampled weekly to determine dry matter (DM) yield, CW concentration, CW digestibility, and in vitro true DM digestibility (IVTD) of forage. The CW concentration, CW digestibility, and IVTD of leaves and stems were also determined weekly in 1991, 1992, and 1993. A combination of chemical and near-infrared reflectance analyses were used to determine CW concentration, CW digestibility, and IVTD (Bélanger and McQueen, 1996, 1997, 1998, 1999). Cell wall concentration was determined as described by Van Soest et al. (1991), without use of sodium sulfite (Na2SO3) and with correction for neutral detergent–insoluble ash. Cell wall digestibility and IVTD were determined using rumen contents following the approach described by Van Soest et al. (1966). Crops were fertilized with N in early May of each year. Details of the 1991, 1992, and 1993 experiments were reported previously (Bélanger and Richards, 1995, 1997), and specific information used for the growth module of the integrated model can be found in Bonesmo and Bélanger (2002).
Model Description
The model applies to the primary growth of timothy, which starts shortly after snowmelt and ends approximately 450°C-d later when timothy is normally harvested at the early heading stage. All parameters were estimated by calibration to key model attributes: concentration and digestibility of CW in leaves, stems, and forage and DM digestibility of leaves, stems, and forage. A realistic calibration range, reflecting the possible variation for each parameter, was specified (Table 1).
Digestibility
In CATIMO, the crop is considered to consist of green leaves, dead leaves, and stems including leaf sheaths. Green leaves and stems were characterized for CW concentration and digestibility. We assumed a DM digestibility of 0.98 g g-1 DM for the cellular content of green leaves and stems (Van Soest, 1982). Dead leaves were assumed to consist of CW only, with a DM digestibility of 0.70 g g-1 DM (Duru, 1997). The DM digestibility of the forage (DF) was calculated by combining the DM digestibility of green leaves (DL), dead leaves (DD), and stems (DS) with their weight ratios:
 | [1] |
where LWRG is the proportion of green leaves to the total amount of stems and green leaves and GWR is the proportion of stems and green leaves to the total amount of DM. The LWRG and GWR were calculated from the weights of green leaves, dead leaves, and stems estimated by the growth module of the model (Bonesmo and Bélanger, 2002). The DL and DS were calculated with the respective CW concentration of leaves (CWcL) and stems (CWcS) and the CW digestibility of leaves (CWDL) and stems (CWDS):
 | [2a] |
 | [2b] |
 | [2c] |
The basic idea (Eq. [2a and 2b]) is the separation of leaf and stem DM into cellular content and CW constituents. The cellular content of leaves (1 - CWcL) and stems (1 - CWcS) is almost completely digestible. And although the CW constituents have limited digestibility, this does not inhibit the digestion of the cellular content (Deinum, 1973).
Cell Wall Concentration
The CW concentrations of green leaves (CWcL) and stems (CWcS) were calculated as the proportion of CW in the DM. These concentrations were obtained by integrating the proportion of respective daily growth rates partitioned to CW, the daily rates of conversion of cellular content into CW, and the daily death rate of leaves. The daily growth rates of green leaves and stems and the daily death rate of leaves were estimated by the growth module of the integrated model (Bonesmo and Bélanger, 2002). Because temperature affects the rates of CW deposition (Fales, 1986), both the partitioning (g CW g-1 DM d-1) and the conversion (g CW g-1 cellular content d-1) in leaves and stems were assumed to be affected by temperature. Furthermore, we assumed that the proportion of the daily growth rate partitioned to CW is the sum of a minimum fraction and an additional temperature-dependent fraction:
 | [3a] |
 | [3b] |
where GCWL and GCWS are the daily growth partitioned to the CW of leaves and stems, respectively; GL and GS are the daily growth rates of leaves and stems, respectively; GCWLmin and GCWSmin are the minimum fractions of daily growth partitioned to CW of leaves and stems, respectively; GCWLadd and GCWSadd are the maximum additional proportions related to temperature for leaves and stems, respectively; and KCW is the temperature-dependent rate constant for CW deposition (Eq. [5]). The fraction of the daily growth rate not partitioned to CW was considered as cellular content.
The daily conversion rates of cellular contents into CW for leaves (RCCL) and stems (RCCS) were calculated as:
 | [4a] |
 | [4b] |
where CCL and CCS are the cellular contents of leaves and stems, respectively, and RCCLmax and RCCSmax are the maximum rates of cellular content converted into CW of leaves and stems, respectively. The KCW was related to the daily mean air temperature (T, °C) by use of a zero to unity factor:
 | [5] |
where KCW is 0 below or at CWTbase and 1 above CWTmax. The CWTbase is the base temperature for CW deposition, and CWTmax is its maximum temperature.
Cell Wall Digestibility
The daily decrease in CW digestibility is indirectly related to increasing phenological development but also directly related to increasing temperature (Ford et al., 1979). Thus, the CW digestibility of leaves (CWDL) and stems (CWDS) was determined from an initial maximum value of CW digestibility (g g-1 CW) and a daily rate of decrease for leaves (RCWDL, g g-1 CW d-1) and for stems (RCWDS, g g-1 CW d-1) as related to the daily mean temperature (T) (Eq. [6a and 6b)]. Early in the growth cycle, there are no true stems (Bélanger and Richards, 1995). Thus, RCWDS was assumed to be similar to RCWDL when the temperature sum above a base temperature of 0°C, from spring growth initiation, was below that required for the start of true stem elongation.
 | [6a] |
 | [6b] |
where RCWDLmax and RCWDSmax are the maximum rates of decrease in CW digestibilities of leaves and stems, respectively, and KCWD is the temperature-dependent rate constant for decrease in CW digestibility. This rate constant was calculated as a function of the daily mean temperature:
 | [7] |
where KCWD is 0 below or at CWDTbase and 1 above CWDTmax. The CWDTbase is the base temperature for decrease in CW digestibility, and CWDTmax is the maximum temperature for decrease in CW digestibility.
Nitrogen Effects on Cell Wall Concentration and Digestibility
The rates of decline in CW deposition and digestibility were assumed to decrease in both leaves and stems when the crop was N stressed (Bélanger and McQueen, 1999). A multiplicative index (NCWI) was introduced to account for the effect of N stress on rates of growth partitioned to CW, conversion of cellular content to CW, and decrease in CW digestibility:
 | [8] |
where RNC is the relative N concentration of the crop as provided by the growth module of the integrated model described in the companion paper (Bonesmo and Bélanger, 2002). We assumed that the rates of decline in CW deposition and digestibility would only be affected when the relative N concentration was <0.5 (Bélanger and McQueen, 1998, 1999). The values for leaves and stems of rates of growth partitioned to CW (Eq. [3a and 3b]), conversion of cellular content to CW (Eq. [4a and 4b]), and decrease in CW digestibility ([Eq. 6a and 6b]) were multiplied by NCWI.
Parameter Estimation and Model Performance
The calibration was based on data from weekly samplings of CW concentration and digestibility. Most of the data used for calibration have been published previously (Bélanger and McQueen, 1996, 1997, 1998, 1999). The program package Powersim Solver (Version 1.0, Powersim, Herndon, VA) was used to estimate a set of parameters that minimized the root mean square error of estimation (RMSE) over all experiments (Powersim, 1996; Bonesmo, 1999). A linear regression analysis between simulated and measured values was used to quantify over- or underestimation of the simulations.
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RESULTS
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The estimated minimum proportion of daily growth partitioned to CW of leaves (GCWLmin) was half of that of stems (GCWSmin), and the maximum additional proportions related to temperature for leaves (GCWLadd) was only 15% of that for stems (GCWSadd) (Table 1). However, the estimated maximum rate of cellular content converted into CW of leaves (RCCLmax) was only slightly lower than that of stems (RCCSmax). The estimated maximum rate of decrease in CW digestibility of leaves (RCWDLmax) was as low as 36% of the estimated maximum decrease in CW digestibility of stems (RCWDSmax). The rate of decrease in CW digestibility of stems, however, was set to be similar to that of leaves until the start of true stem elongation. Within a narrow calibration range, the temperature sum for the start of true stem elongation was estimated at 220°C-d. The estimated base temperature for the decrease in CW digestibility (CWDTbase) was slightly higher than that for CW deposition (CWTbase), whereas the estimated maximum temperature for decrease in CW digestibility (CWDTmax) was considerably higher than that for CW deposition (CWCTmax).
In general, the simulated green-leaf and stem CW concentration and digestibility agreed well with the measurements (Fig. 1)
. The simulated CW concentration of the stem fraction was more closely correlated with the measurements than that of the leaf fraction; the RMSE for CW concentration of leaves was twice that of stems (Table 2). For CW digestibility, the slope coefficients for leaves (0.97) and stems (0.95) were close to 1, and the RMSE values were low (Table 2).
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Fig. 1. Simulated leaf and stem cell wall (CW) concentration and CW digestibility plotted against measured values for timothy grown under nonlimiting and limiting N conditions in three separate experiments. DM, dry matter.
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When combining CW concentration and digestibility, the calculated true DM digestibility of green leaves and stems agreed well with the measured values of IVTD, both for the nonlimiting (Fig. 2) and limiting N conditions (Fig. 3)
. The simulated forage IVTD—obtained by combining the digestibility of green leaves, stems, and dead leaves—was close to the measured values (Fig. 4)
. However, both forage CW concentration and digestibility tended to be overestimated by the model. The largest discrepancy between simulated and measured forage CW concentration (0.09 g CW g-1 DM) occurred on the last measurement in 1992; the largest discrepancy for forage CW digestibility (0.11 g g-1 CW) occurred on the first measurement in 1995 (Fig. 4).
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Fig. 2. Measured and simulated in vitro true dry matter (DM) digestibility (IVTD) of green leaves and stems of timothy grown under nonlimiting N conditions in three separate experiments. The data are from three cultivars in 1991, two cultivars in 1992, and one cultivar in 1993.
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Fig. 3. Measured and simulated in vitro true dry matter (DM) digestibility (IVTD) of green leaves and stems of timothy cv. Champ grown under two levels of N-limiting conditions in 1993 (N0, 0 g N m-2; N7, 7 g N m-2).
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Fig. 4. Simulated forage in vitro true dry matter (DM) digestibility (IVTD), cell wall (CW) digestibility, and CW concentration plotted against measured values for timothy grown under nonlimiting and limiting N conditions in four separate experiments.
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Overall, the model satisfactorily fitted the measured values with RMSEs of 0.051 g g-1 DM for forage CW concentration, 0.026 g g-1 CW for forage CW digestibility, and 0.018 g g-1 DM for forage DM digestibility (Table 2). The leaf and stem CW concentration (RMSE 0.044 g g-1 DM), CW digestibility (RMSE 0.019 g g-1 CW), and DM digestibility (RMSE 0.018 g g-1 DM) were also calculated satisfactorily by the model.
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DISCUSSION
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Models of nutritive value differ substantially in their underlying concepts and complexity. Most are based on statistical relationships describing the changes in digestibility with time or advancing phenological development (Fick et al., 1994); they contain little information on the physiological processes involved in determining forage nutritive value. Deinum (1973) proposed that both CW concentration and digestibility must be calculated accurately to establish the cause–effect relationship in forage nutritive value. Because the proportion of CW and the decline of digestibility with time are different in leaves and stems, a model should include forage morphological components, such as leaves and stems as a function of environmental factors.
The growth module of the CATIMO model presented in the companion paper (Bonesmo and Bélanger, 2002) provides these forage components, and thus constitutes a good basis for an integrated model of growth and nutritive value. Buxton and Fales (1994) attempted to divide the environmental impact on nutritive value into direct and indirect effects; the direct effect was related primarily to temperature and the indirect effect through phenological development and the resulting proportion of leaves. An integrated model of both growth and nutritive value, such as the one presented here, accounts for both of these aspects. In contrast, the model developed for timothy by Gustavsson et al. (1995) is based on the indirect effects, and the timothy model by Fagerberg and Nyman (1994), originally developed for ryegrass (Lolium perenne L.) by Kornher et al. (1991), simulates changes in nutritive value without considering plant growth and development.
The forage DM digestibility was slightly underestimated for low IVTD values corresponding to the end of the primary growth cycle (Fig. 4; Table 2); this occurred even though the growth module of the model tended to underestimate the stem fraction of the forage at the end of the growth period. Because the simulated digestibility of the stem and leaf fractions agreed well with the measurements, the proportion of dead leaves was likely overestimated. We did not measure the amount of dead leaves. Furthermore, there are limited data in the literature on leaf senescence and disappearance rates in grasses. In timothy primary growth harvested later than early heading, the amount of senescent material can be as high as 17% of the forage DM yield (Kunelius et al., 2000).
On most days during primary growth, daily mean air temperatures were well above the estimated base temperatures and lower than the maximum temperatures. These cardinal temperatures for CW deposition and digestibility are an extrapolation of linear functions, but they are all at physiologically acceptable levels (Table 1). Also, the relationship between the estimated parameters for leaves and stems seems physiologically relevant. For example, under high temperatures, the stem digestibility of several tropical and temperate grasses was only half that of leaves (Wilson et al., 1991).
When interpreting the model parameters, however, it is important to bear in mind the model boundary conditions imposed by the modeling approach itself and by the range of the calibration data set (Table 2). The model calibration data set covers a period in primary growth with a continuing increase in CW content and a continuing decrease in CW digestibility. Hence, the model does not apply when CW deposition ceases. Furthermore, the data set used in calibration is limited in soil moisture and daylength conditions. The consequences of this limitation are discussed in the companion paper (Bonesmo and Bélanger, 2002). The CATIMO model is promising because of its mechanistic and flexible approach and the resulting close agreement between measured and simulated values of yield and nutritive value. The next step is to validate the model using a broader independent data set from a wider selection of sites in eastern Canada.
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NOTES
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Contrib. no. 715, Agric. and Agri-Food Can.
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REFERENCES
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ABSTRACT
INTRODUCTION
