Perennial Biomass Grasses and the Mason–Dixon Line: Comparative Productivity across Latitudes in the Southern Great Plains

TL;DR: In this paper, the authors quantify latitudinal variation in production of representative upland switchgrass ecotypes (Panicum virgatum L.) and Miscanthus (Miscanthus × giganteus J. M. Greef & Deuter ex Hodk), and investigate the environmental factors affecting yield variation.

Abstract: Understanding latitudinal adaptation of switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus × giganteus J. M. Greef & Deuter ex Hodk. & Renvoize) to the southern Great Plains is key to maximizing productivity by matching each grass variety to its optimal production environment. The objectives of this study were: (1) to quantify latitudinal variation in production of representative upland switchgrass ecotypes (Blackwell, Cave-in-Rock, and Shawnee), lowland switchgrass ecotypes (Alamo, Kanlow), and Miscanthus in the southern half of the US Great Plains and (2) to investigate the environmental factors affecting yield variation. Leaf area and yield were measured on plots at 10 locations in Missouri, Arkansas, Oklahoma, and Texas. More cold winter days led to decreased subsequent Alamo switchgrass yields and increased subsequent upland switchgrass yields. More hot-growing season days led to decreased Kanlow and Miscanthus yields. Increased drought intensity also contributed to decreased Miscanthus yields. Alamo switchgrass had the greatest radiation use efficiency (RUE) with a mean of 4.3 g per megajoule intercepted PAR and water use efficiency (WUE) with a mean of 4.5 mg of dry weight per gram of water transpired. The representative RUE values for other varieties ranged from 67 to 80 % of Alamo’s RUE value and 67 to 87 % of Alamo’s WUE. These results will provide valuable inputs to process-based models to realistically simulate these important perennial grasses in this region and to assess the environmental impacts of production on water use and nutrient demands. In addition, it will also be useful for landowners and companies choosing the most productive perennial grasses for biofuel production.

Summary

Introduction

• Switchgrass (Panicum virgatum L.) and Miscanthus×giganteus J. M. Greef & Deuter ex Hodk. & Renvoize (hereafter referred to asMiscanthus) represent two primary plant species of interest for bioenergy production in the USA.
• Casler et al. [3–5] described latitudinal and longitudinal variation in switchgrass in the northern Great Plains.
• When upland ecotypes (i.e., Blackwell, Cave-in-Rock, and Shawnee) are grown in the south, they remain shorter and flower earlier thus decreasing their dry matter yields.
• Switchgrass water use efficiency (WUE), the balance of carbon assimilated per unit of water transpired, has been linked to higher yields.

Methods

• In 2010, plots at an additional site, Booneville, AR, were also established.
• For switchgrass ecotypes, 0.5 m of a row was harvested, while with Miscanthus 1.0 m of a row (one plant) was harvested.
• These values of FIPAR consisted of multiple measurements with the light sensor moving parallel to the row, in the area from mid-row to mid-row.
• High temperature effects were estimated by determining the number of days with temperatures exceeding 32 °C during each growing season.
• Next, the new PCA variables were used in a multiple regression to analyze the ecotype, environment, and ecotype×environment interactions as predictors of yield.

Results

• Yearly Biomass Yield and Leaf Area Overall, yearly biomass yield and LAI increased between the second and third year after establishment at all sites.
• Cold temperatures during the previous winter were positively correlated with yields in the third year for Kanlow and the Upland ecotypes (Table 6 and Fig. 6).
• The last model with all ecotypes, environmental variables, and ecotype×environment interactions had an R2 of 0.80 (p<0.001).
• Again, none of the other variables were significant in either year.
• The overall mean RUE for Alamo for the higher groups of values was 4.35 (Table 8), with values of the upland types and Kanlow being 72–78 % of Alamo’s value and the mean for Miscanthus being 68 % of Alamo’s value (Table 8).

Discussion

• There appeared to be a breakpoint in adaptation regions of these species and ecotypes, roughly corresponding to the Missouri Compromise Line, an extension of the Mason– Dixon line, that forms the border between Missouri and Arkansas.
• For Miscanthus in year 3, only the two most northern Missouri sites were high yielding.
• In the shortgrass steppe of Colorado, a mixture of cool-season and warmseason grasses (including blue grama) had WUE values of 1.0–4.5 mgg−1 [26].
• This study provided valuable results for various switchgrass ecotypes andMiscanthus related to understanding adaptation to various latitudes in the southern portion of the USA.
• Such improved simulations will allow rapid assessment of resource utilization (water and nutrients) under the diverse climatic conditions and soils in this and similar regions.

Figures

Table 2 County, state, and latitude of origin for each switchgrass type

Table 3 Yield in Mg per hectare±SD for the highest yielding harvest

Fig. 4 Final dry matter yields as related to photoperiod of 30 days after green-up for pooled upland switchgrass ecotypes, Alamo and Kanlow switchgrass, and Miscanthus at 10 locations for the second and third years after plot establishment. P values are the significance levels for the slopes

Table 8 Means of radiation use efficiency (g per MJ IPAR) of the two groups in Table 7: the selected high values and the other, lower values that were not in bold in Table 7

Table 4 First harvest date values for Leaf Area Index±SD

Table 5 Photoperiod of 30 days after green-up, number of days with mean temperature less than 0 °C during previous winter, number of days with mean temperature greater than 32 °C during the growing season, and precipitation (Jan–Aug) for 10 locations

Table 6 Pearson’s correlation coefficients for final biomass yield after the third year of establishment as a function of four environmental variables

Fig. 3 Final dry matter yields for pooled upland switchgrass ecotypes, Alamo and Kanlow switchgrass, at 10 locations for the second and third years after plot establishment as a function of degrees from latitude of origin. P values are the significance levels for the slopes

Fig. 1 Final dry matter yields as related to latitude for three upland switchgrass ecotypes at 10 locations for the second and third years after plot establishment. P values are the significance levels for the slopes

Fig. 5 Final dry matter yields as related to precipitation (for January through August) for pooled upland switchgrass ecotypes, Alamo and Kanlow switchgrass, and Miscanthus at 10 locations for the second and third years after plot establishment. P values are the significance levels for the slopes

Fig. 2 Final dry matter yields as related to latitude for pooled upland switchgrass ecotypes, Alamo and Kanlow switchgrass, and Miscanthus at 10 locations for the second and third years after plot establishment. P values are the significance levels for the slopes

Table 1 Soil type, latitude, and average annual precipitation for 10 locations

Table 10 Mean temperatures (degree Celcius) and days of duration from green-up to first harvest date

Full text

University of Nebraska - Lincoln University of Nebraska - Lincoln
DigitalCommons@University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln
Publications from USDA-ARS / UNL Faculty
U.S. Department of Agriculture: Agricultural
Research Service, Lincoln, Nebraska
2013
Perennial Biomass Grasses and the Mason–Dixon Line: Perennial Biomass Grasses and the Mason–Dixon Line:
Comparative Productivity across Latitudes in the Southern Great Comparative Productivity across Latitudes in the Southern Great
Plains Plains
Jim R. Kiniry
USDA-ARS
, Jim.Kiniry@ars.usda.gov
L. C. Anderson
University of Texas
M.-V. V. Johnson
USDA-NRCS
, mvjohnson@usgs.gov
K. D. Behrman
USDA-ARS
, kate.behrman@gmail.com
M. Brakie
USDA-NRCS East Texas Plant Materials Center
, Melinda.Brakie@tx.usda.gov
See next page for additional authors
Follow this and additional works at: https://digitalcommons.unl.edu/usdaarsfacpub
Kiniry, Jim R.; Anderson, L. C.; Johnson, M.-V. V.; Behrman, K. D.; Brakie, M.; Burner, D.; Cordsiemon, R. L.;
Fay, P. A.; Fritschi, F. B.; Houx, J. H. III; Hawkes, C.; Juenger, T.; Kaiser, J.; Keitt, T. H.; Lloyd-Reilley, J.; Maher,
S.; Raper, R.; Scott, A.; Shadow, A.; West, C.; Wu, Y.; and Zibilske, L., "Perennial Biomass Grasses and the
Mason–Dixon Line: Comparative Productivity across Latitudes in the Southern Great Plains" (2013).
Publications from USDA-ARS / UNL Faculty
. 1271.
https://digitalcommons.unl.edu/usdaarsfacpub/1271
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Authors Authors
Jim R. Kiniry, L. C. Anderson, M.-V. V. Johnson, K. D. Behrman, M. Brakie, D. Burner, R. L. Cordsiemon, P. A.
Fay, F. B. Fritschi, J. H. Houx III, C. Hawkes, T. Juenger, J. Kaiser, T. H. Keitt, J. Lloyd-Reilley, S. Maher, R.
Raper, A. Scott, A. Shadow, C. West, Y. Wu, and L. Zibilske
This article is available at DigitalCommons@University of Nebraska - Lincoln: https://digitalcommons.unl.edu/
usdaarsfacpub/1271

Perennial Biomass Grasses and the Mason–Dixon Line:
Comparative Productivity across Latitudes in the Southern
Great Plains
J. R. Kiniry & L. C. Anderson & M.-V. V. Johnson &
K. D. Behrman & M. Brakie & D. Burner &
R. L. Cordsiemon & P. A. Fay & F. B. Fritschi &
J. H. Houx III & C. Hawkes & T. Juenger & J. Kaiser &
T. H. Keitt & J. Lloyd-Reilley & S. Maher & R. Raper &
A. Scott & A. Shadow & C. West & Y. Wu & L. Zibilske
Published online: 23 September 2012
#
Springer Science+Business Media, LLC (outside the USA) 2012
Abstract Understanding latitudinal adaptation of switch-
grass (Panicum virgatum L.) and Miscanthus (Miscanthus×
giganteus J. M. Greef & Deuter ex Hodk. & Renvoize) to the
southern Great Plains is key to maximizing productivity by
matching each grass variety to its optimal production environ-
ment. The objectives of this study were: (1) to quantify lati-
tudinal variation in production of representative upland
switchgrass ecotypes (Blackwell, Cave-in-Rock, and
Shawnee), lowland switchgrass ecotypes (Alamo, Kanlow),
and Miscanthus in the southern half of the US Great Plains
and (2) to investigate the environmental factors affecting yield
variation. Leaf area and yield were measured on plots at 10
locations in Missouri, Arkansas, Oklahoma, and Texas. More
cold winter days led to decreased subsequent Alamo switch-
grass yields and increased subsequent upland switchgrass
yields. More hot-growing season days led to decreased
Kanlow and Miscanthus yields. Increased drought intensity
also contributed to decreased Miscanthus yields. Alamo
Electronic supplementary material The online version of this article
(doi:10.1007/s12155-012-9254-7) contains supplementary material,
which is available to authorized users.
J. R. Kiniry (*)
:
K. D. Behrman
:
P. A. Fay
USDA-ARS,
Temple, TX, USA
e-mail: Jim.Kiniry@ARS.USDA.GOV
L. C. Anderson
:
K. D. Behrman
formerly with University of Texas,
Austin, TX, USA
M.-V. V. Johnson
USDA-NRCS,
Temple, TX, USA
M. Brakie
:
A. Shadow
USDA-NRCS East Texas Plant Materials Center,
Nacogdoches, TX, USA
D. Burner
USDA-ARS,
Houoma, LA, USA
D. Burner
formerly USDA-ARS,
Booneville, AR, USA
R. Raper
Oklahoma State University, Stillwater, formerly USDA-ARS,
Booneville, AR, USA
R. L. Cordsiemon
:
J. Kaiser
USDA-NRCS Elsberry Plant Materials Center,
Elsberry, MO, USA
F. B. Fritschi
:
J. H. Houx III
University of Missouri,
Columbia, MO, USA
C. Hawkes
:
T. Juenger
:
T. H. Keitt
University of Texas,
Austin, TX, USA
J. Lloyd-Reilley
:
S. Maher
USDA-NRCS Kika de la Garza Plant Materials Center,
Kingsville, TX, USA
A. Scott
Rio Farms, Inc.,
Monte Alto, TX, USA
Bioenerg. Res. (2013) 6:276–291
DOI 10.1007/s12155-012-9254-7
This article is a U.S. government work, and is not subject to copyright in the United States.

switchgrass had the greatest radiation use efficiency (RUE)
with a mean of 4.3 g per megajoule intercepted PAR and water
use efficiency (WUE) with a mean of 4.5 mg of dry weight per
gram of water transpired. The representative RUE values for
other varieties ranged from 67 to 80 % of Alamo’s RUE value
and 67 to 87 % of Alamo’s WUE. These results will provide
valuable inputs to process-based models to realistically simu-
late these important perennial grasses in this region and to
assess the environmental impacts of production on water use
and nutrient demands. In addition, it will also be useful for
landowners and compan ies choosing the most productive
perennial grasses for biofuel production.
Keywords Biofuel grasses
.
Switchgrass
.
Miscanthus
.
Simulation modeling
Introduction
Switchgrass (Panicum virgatum L.) and Miscanthus×gigan-
teus J. M. Greef & Deuter ex Hodk. & Renvoize (hereafter
referred to as Miscanthus) represent two primary plant species
of interest for bioenergy production in the USA. Both have
repeatedly shown promise as being highly productive peren-
nial grasses adapted to either marginal or prime agricultural
soils. Switchgrass, with its high variation in ecotypes, can be
grown as far south as northern Mexico and as far north as
southern Canada. The sustainability and yield stability of
switchgrass biomass production will depend on understanding
the adaptation of representative ecotypes to different environ-
ments. Widespread reports of Miscanthus grown in the
Midwest have spurred interest in it as an alternative to switch-
grass. However, no Miscanthus yields have been reported for
the southern Great Plains. It is therefore imperative to quantify
productivity of these biofuel grasses in this region of the USA.
If biofuel production is targeted for “marginal” soils, identi-
fying the species and ecotypes adapted to these conditions
also is extremely important.
There are many environmental gradients that transverse the
southern two thirds of the US Great Plains. In the often-cited
biofuel crop regional adaptation map [30] (Electronic supple-
mentary material (ESM) Fig. S1), there is a break in adapta-
tion regions running east to west through eastern Oklahoma
and western Arkansas. There are north-to-south gradients in
the average daily temperature of the coldest quarter (ESM Fig.
S2a) and in average daily temperature of the warmest quarter
(ESM Fig. S2b) and east-to-west gradients annual precipita-
tion (ESM Fig. S2c). Casler et al. [3–5] described latitudinal
and longitudinal variation in switchgrass in the northern Great
Plains. The major abiotic factors that regulate adaptation of
switchgrass populations are photoperiodism, heat tolerance,
cold or freez ing tolerance, and precipitation [ 5, 25].
Furthermore, Vogel et al. [34] used climate and ecoregions
to develop plant adaptation regions for switchgrass ecotypes.
Previous switchgrass studies have shown variable responses
to photoperiod manipulation depending on the ecotype. In the
central Great Plains, switchgrass ecotypes from the Dakotas
(upland ecotypes) flower and mature early and are short in
stature, whereas those from Texas and Oklahoma (lowland
ecotypes) flower late and are tall [9, 24]. When upland
(northern) ecotypes (i.e., Blackwell, Cave-in-Rock, and
Shawnee) are grown in the south, they remain shorter and
flower earlier thus decreasing their dry matter yields.
However, when lowland (southern) ecotypes (i.e., Alamo)
a
re planted further north, they flower later and are taller, thus
having more stable yields than upland ecotypes. The photope-
riod response has also been reported to be responsible for
winter survival. Southern types moved too far north mature
too late and do not survive late season winter freezes [34].
Switchgrass water use efficiency (WUE), the balance of
carbon assimilated per unit of water transpired, has been
linked to higher yields. While transpiration and photosynthe-
sis are closely related to yield, WUE is most closely linked to
higher biomass yield [37]. Measurements of WUE on single
leaves indicate that switchgrass, as expected, uses relatively
low levels of water, and that the highest yielding switchgrass
varieties have the highest water use efficiencies [23].
In this study, five switchgrass ecotypes and Miscanthus
were planted in replicated field trials at 10 locations in Texas,
Arkansas, Oklahoma, and Missouri. The main objectives
were to: (1) describe and identify the most productive (high-
est biomass and leaf area) perennial species and ecotype at
each location; (2) determine the impact of photoperiod, pre-
cipitation, high temperature stress during the growing season,
and low temperature stress during the preceding winter on
yield; (3) determine the radiation use efficiency (RUE) and
WUE of these perennial grasses in these representative sites
in the central and southern Great Plains to allow realistic
simulation of their production with process-based simulation
models. Proce ss-based models such as Agricultural Land
Management Alternatives with Numerical Assessment
Criteria (ALMANAC) [17], Environmental Policy Integrated
Climate (SWAT) [35, 36], and Soil and Water Assessment
Tool (EPIC) [2] provide realistic simulation of biofuel plant
species for assessing management practices that maximize
C. West
Texas Tech University, Lubbock,
formerly with University of Arkansas,
Fayetteville, AR, USA
Y. W u
Oklahoma State University,
Stillwater, OK, USA
L. Zibilske
formerly with USDA-ARS,
Weslaco, TX, USA
Bioenerg. Res. (2013) 6:276–291 277

production and minimize environmental impact. Process-
based simulation of these perennial biofuel grasses requires
realistic understanding of the important processes affecting
adaptation and consequently biomass production.
Methods
In 2009, we selected nine locations (Table 1) across the south-
central USA to capture a range of environmental conditions. In
2010, plots at an additional site, Booneville, AR, were also
established. At each site, five switchgrass ecotypes, “Alamo”,
“Blackwell”, “Cave-in-Rock”, “Kanl ow”,and“Shawnee”
(Table 2) were sown from seed from Turner Seed,
Breckenridge, TX, 76424-8165. Seeding rate was 5.6 kg pure
live seed per hectare. Miscanthus plants (originally purchased
from Kurt Bluemel, www.kurtbl uemel .com/Mis canthus_
giganteus.html) in 4-l pots were transplanted into the plots.
Genetic analysis of the Miscanthus material used indicated that
the plant material was identical to the Illinois clone (Michael
Casler, personal communication). In spring 2009, all ecotypes
and species were planted in randomized complete block design
withsinglerow plots, 1 m apart and5 m long, withfour replicate
rows per plant variety. Harvest dates were chosen to establish
plant growth during the active growing portion of spring and
summer, with logistical constraints due to travel distances be-
tween plots. In 2010, plants were harvested once in June or July
at each location and again in October. In 2011, plants were
harvested three times at each location. These were in May or
June, July and August, September, or October. At each loca-
tion, weeds were controlled by use of pre- and postemergence
herbicides [Prowl H20 (pendimethalin: (N-(1-ethylpropyl)-
3,4-dimethyl-2,6-dinitrobenzenamine)) and 2,4-D-2,4-
dichlorophenoxyacetic acid], hoeing, and hand weeding.
Destructive harvests were taken during the growing seasons
in order to characterize plant growth. These harvests were all
taken from areas not previously harvested during the growing
season. “Final yield” was the biomass at the final harvest each
year. At each harvest, plant height, fresh and dry weights,
fraction intercepted photosynthetically acti ve radiation
(FIPAR), and leaf area index (LAI) were also measured. For
switchgrass ecotypes, 0.5 m of a row was harvested, while with
Miscanthus 1.0 m of a row (one plant) was harvested. The
samples were weighed for a total fresh weight. When the total
sample exceeded 1,000 g, a grab sample of 200–500gwas
separated. Samples were dried at 66 °C in a forced-air oven until
the dry weight had stabilized. Measurements of FIPAR were
taken using an AccuPAR LP-80 Ceptometer (Decagon Devices,
Pullman,WA,USA)within2hofsolarnoon.Thesevaluesof
FIPAR consisted of multiple measurements with the light
sensor moving parallel to the row, in the area from mid-row
to mid-row. In this way, the pertinent ground area for each row
was sampled. Care was taken to avoid shadows from neigh-
boring rows. An external light source was used for concurrent
above and below values that were averaged for the row. Leaf
area of a subsample was measured with a LI-3100 Area Meter
(LI-COR Biosciences, Lincoln, NE, USA).
WUE and RUE were calculated using output from the
ALMANAC model [17]. The ALMANAC model was parame-
terized so that the actual LAI equaled the simulated LAI for the
first harvest date each year. We used only this early growth
interval for RUE and WUE calculations in an effort to minimize
the prevalent drought impacts evident at several of the sites in
these years. This avoided unrealistically low values of RUE and
WUE due to growth decreasing drastically due to drought. Daily
weather data at each site and (2009–2011) from National
Oceanic and Atmospheric Administration were used in the
model [29]. The RUE was calculated as the ratio of measured
dry matter over cumulative simulated intercepted PAR. The
WUE was calculated in terms of measured dry matter produced
per unit simulated water transpired [28
]. Plant dry weight was the
total
above-ground dry weight (cutting height, 0.1 m). Water use
was determined using the ALMANAC model to simulate the
amount of water transpired by plants during the growth period.
Final dry weights for each plant type as a function of latitude
were analyzed by regression with Statistical Analysis System
[32]. Firstly, within each year , the three upland types were
analyzed for significant different slopes and intercepts using
Table 1 Soil type, latitude, and
average annual precipitation for
10 locations
a
Obtained from US Climate Data
[29]
Location Soil type Latitude Precipitation
a
(mm)
Elsberry, MO Menfro silt loam 39.16 972
Columbia, MO Mexico silt loam 38.89 1,025
Mt. Vernon, MO Gerald silt loam 37.07 1,171
Stillwater, OK Kirkland silt loam 36.12 932
Fayetteville, AR Pickwick gravely loam 36.09 1,169
Booneville, AR Leadvale silt loam 35.09 1,213
Nacogdoches, TX Attoyac fine sandy loam 31.50 1,229
Temple, TX Houston black clay 31.04 910
Kingsville, TX Cranell sandy clay loam 27.54 736
Weslaco, TX Hidalgo sandy clay loam 26.22 645
278 Bioenerg. Res. (2013) 6:276–291

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Perennial biomass grasses and the mason–dixon line: comparative productivity across latitudes in the southern great plains" ?

The objectives of this study were: ( 1 ) to quantify latitudinal variation in production of representative upland switchgrass ecotypes ( Blackwell, Cave-in-Rock, and Shawnee ), lowland switchgrass ecotypes ( Alamo, Kanlow ), and Miscanthus in the southern half of the US Great Plains and ( 2 ) to investigate the environmental factors affecting yield variation. The online version of this article ( doi:10.