management effects on bioenergy sorghum growth, yield and nutrient uptake

12
Management effects on bioenergy sorghum growth, yield and nutrient uptake J.P. Wight a, *, F.M. Hons a , J.O. Storlien a , T.L. Provin a , H. Shahandeh a , R.P. Wiedenfeld b a Department of Soil and Crop Sciences, Texas A & M University, 2474 TAMU, College Station, TX 77843, USA b Texas AgriLife Research and Extension Center, Weslaco, TX 78596, USA article info Article history: Received 1 February 2012 Received in revised form 18 June 2012 Accepted 30 June 2012 Available online 31 July 2012 Keywords: Biomass Sorghum Cropping systems Fertilization Nitrogen Rotation Nutrient uptake abstract Bioenergy sorghum (Sorghum bicolor L. Moench.) productivity and nutrient uptake may be affected by cropping sequence complexity, fertilization, and residue removal. The goal of this research was to optimize the efficiency of crop management in high biomass (bio- energy) sorghum systems. The two-year field study was conducted in two diverse locations near College Station and Weslaco, Texas. The study utilized a complete factorial design with four replications of the following factors: Rotation: continuous biomass sorghum vs. biannual rotation with corn (Zea mays L.); Stover Return: 0, 25, 50% of the sorghum biomass and all corn stover; and N Rate: 0 vs. non-limiting N. The bioenergy sorghum used was a high-yield photoperiod-sensitive hybrid. Other inputs and practices were those commonly used in the respective areas. Sorghum was harvested for yield, and C, N, P and K, were determined. Rotation, fertilization, and residue return affected yields, plant growth, and nutrient uptake ( p < 0.05). Total yields, C, N, P, and K uptake in sorghum were significantly increased by rotation and N fertilization both years, while 25% residue return increased sorghum yield and N uptake at College Station the first year. Uptake of C, N, P and K were increased by N fertilization. Sorghum tissue concentrations of N, P and K declined from the first to the second year although mean yield increased, possibly indi- cating decreased soil nutrient availability after only two years. A regression equation was developed relating biomass yield and site, rotation, nitrogen rate, and plant physical traits (R 2 ¼ 0.67). ª 2012 Elsevier Ltd. All rights reserved. 1. Introduction The Energy Independence and Security Act of 2007 mandated production of renewable fuels: 34 hm 3 currently, increasing to 136 hm 3 by 2022. To meet this goal, the U.S. Department of Energy, estimates that over 254,952 km 2 of dedicated energy crops will be needed [1]. Lignocellulosic conversion of high biomass photoperiod-sensitive sorghum (bioenergy sorghum, Sorghum bicolor L. Moench.) may be one way of helping achieve this goal. Bioenergy sorghum is also of interest due to its relatively low input requirements, drought tolerance, and ability to maintain high yields under a wide range of environmental conditions [2e4]. Though relatively little work has been done to improve bioenergy sorghum, numerous genes affecting feedstock quality are known. Genes have been isolated that * Corresponding author. Tel.: þ1 865 567 5066; fax: þ1 979 845 0456. E-mail addresses: [email protected] (J.P. Wight), [email protected] (F.M. Hons), [email protected] (J.O. Storlien), TProvin@ ag.tamu.edu (T.L. Provin), [email protected] (H. Shahandeh), [email protected] (R.P. Wiedenfeld). Available online at www.sciencedirect.com http://www.elsevier.com/locate/biombioe biomass and bioenergy 46 (2012) 593 e604 0961-9534/$ e see front matter ª 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biombioe.2012.06.036

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Page 1: Management effects on bioenergy sorghum growth, yield and nutrient uptake

ww.sciencedirect.com

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4

Available online at w

http: / /www.elsevier .com/locate/biombioe

Management effects on bioenergy sorghum growth, yield andnutrient uptake

J.P. Wight a,*, F.M. Hons a, J.O. Storlien a, T.L. Provin a, H. Shahandeh a, R.P. Wiedenfeld b

aDepartment of Soil and Crop Sciences, Texas A & M University, 2474 TAMU, College Station, TX 77843, USAbTexas AgriLife Research and Extension Center, Weslaco, TX 78596, USA

a r t i c l e i n f o

Article history:

Received 1 February 2012

Received in revised form

18 June 2012

Accepted 30 June 2012

Available online 31 July 2012

Keywords:

Biomass

Sorghum

Cropping systems

Fertilization

Nitrogen

Rotation

Nutrient uptake

* Corresponding author. Tel.: þ1 865 567 506E-mail addresses: [email protected] (J

ag.tamu.edu (T.L. Provin), [email protected]/$ e see front matter ª 2012 Elsevhttp://dx.doi.org/10.1016/j.biombioe.2012.06.

a b s t r a c t

Bioenergy sorghum (Sorghum bicolor L. Moench.) productivity and nutrient uptake may be

affected by cropping sequence complexity, fertilization, and residue removal. The goal of

this research was to optimize the efficiency of crop management in high biomass (bio-

energy) sorghum systems. The two-year field study was conducted in two diverse locations

near College Station and Weslaco, Texas. The study utilized a complete factorial design

with four replications of the following factors: Rotation: continuous biomass sorghum vs.

biannual rotation with corn (Zea mays L.); Stover Return: 0, 25, 50% of the sorghum biomass

and all corn stover; and N Rate: 0 vs. non-limiting N. The bioenergy sorghum used was

a high-yield photoperiod-sensitive hybrid. Other inputs and practices were those

commonly used in the respective areas. Sorghum was harvested for yield, and C, N, P and

K, were determined. Rotation, fertilization, and residue return affected yields, plant

growth, and nutrient uptake ( p < 0.05). Total yields, C, N, P, and K uptake in sorghum were

significantly increased by rotation and N fertilization both years, while 25% residue return

increased sorghum yield and N uptake at College Station the first year. Uptake of C, N, P

and K were increased by N fertilization. Sorghum tissue concentrations of N, P and K

declined from the first to the second year although mean yield increased, possibly indi-

cating decreased soil nutrient availability after only two years. A regression equation was

developed relating biomass yield and site, rotation, nitrogen rate, and plant physical traits

(R2 ¼ 0.67).

ª 2012 Elsevier Ltd. All rights reserved.

1. Introduction Sorghum bicolor L. Moench.) may be oneway of helping achieve

The Energy Independence and Security Act of 2007 mandated

production of renewable fuels: 34 hm3 currently, increasing to

136 hm3 by 2022. To meet this goal, the U.S. Department of

Energy, estimates that over 254,952 km2 of dedicated energy

crops will be needed [1]. Lignocellulosic conversion of high

biomass photoperiod-sensitive sorghum (bioenergy sorghum,

6; fax: þ1 979 845 0456..P. Wight), [email protected] (H. Shahandeh), B

ier Ltd. All rights reserved036

this goal.

Bioenergy sorghum is also of interest due to its relatively

low input requirements, drought tolerance, and ability to

maintain high yields under a wide range of environmental

conditions [2e4]. Though relatively little work has been done

to improve bioenergy sorghum, numerous genes affecting

feedstock quality are known. Genes have been isolated that

u.edu (F.M. Hons), [email protected] (J.O. Storlien), TProvin@[email protected] (R.P. Wiedenfeld)..

Page 2: Management effects on bioenergy sorghum growth, yield and nutrient uptake

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4594

allow lignin reduction [5]. This crop is also suited to biofuel

production because it contains a significant quantity of

fermentable carbohydrates and does not directly compete

with food crops. Biomass sorghum has wide environmental

adaptability [6], and dual-use corn (Zea mays) and biomass

sorghum systems, similar to the one in our study, could have

production ranges throughout much of the northern, central,

and southern US.

Although bioenergy sorghum has many traits that make it

ideal for biofuel production, environmental and management

conditions can affect the productivity and sustainability of

these systems. Ethanol yield from grain sorghum can be

affected by soil type and growing location [7]. Management

factors such as location [7], nutrient input [4], crop rotation [8],

and residue return [9] can impact yields, and may be linked to

soil quality. Removing residue inputs from a system can

decrease nutrient cycling, soil organic carbon (SOC), water

holding capacity, aggregation, yields over time and may

increase soil erosion.

Soil is the fundamental resource in crop production

systems, and maintaining soil quality is central in ensuring

sustainable productivity. Management practices that enhance

soil organic matter content can affect nutrient cycling

throughout the soil profile by reducing erosion, improving

structure and water infiltration, increasing cation exchange

capacity (CEC), and releasing plant nutrients upon breakdown

[10,11]. Dou et al. [8] found that after 20 years of grain sorghum

production in south-central Texas, no-till increased SOC,

dissolved organic C, and soil total N compared to conven-

tionally tilled systems. However, it remains unclear how

specific cropping sequences affect soil quality and yield under

bioenergy sorghum production with biomass removal.

Soil organic C dynamics may be affected by crop sequence

complexity, residue rate, and residue quality. In a summary of

soil C studies, West and Post [12] found that when farmland is

converted from conventional till to no-till, increasing rotation

complexity enhanced SOC sequestration. Similar results were

found in Texas sorghumproduction systems,with a sorghum-

wheat (Triticum aestivum, L.)-soybean (Glycine max, L. Merr.)

rotation having 18% higher dissolved organic C than contin-

uous sorghum systems [13], and higher yield and nutrient use

efficiency [14]. Crop rotation often increases yield and SOC

sequestration and, therefore, affects many other soil charac-

teristics. One reason for increased sequestrationwith rotation

is differing quantity and quality of residues with different

crops [14,15].

Studies have found increasing crop residue input often

directly correlates with SOC [16,17]. These authors concluded

that the mulch rate of winter covers was directly related to

gains in SOC. As overall system productivity increases,

quantities of residues returned to soil should also increase.

However, this relationship may be confounded by residue

characteristics. Drinkwater et al. [18] found that residue

quality can affect C and N cycling, and suggested high C-to-N

organic residues increased C retention in soil. Residue return

can also improve soil microbial properties including nutrient

cycling and diversity [19,20]. Powell andHons [9] observed that

removal of more than 50% of aboveground high energy

sorghum biomass for three years resulted in lower yields,

reduced N fertilizer uptake efficiency and reduced SOC

concentrations. Results were more pronounced when all

biomass was removed. With complete biomass removal, N

uptake efficiencies decreased from 68% in the first year of the

study to only 22% in the fourth year. Improving soil nutrient

dynamics can also increase yield. These factors should be

considered when determining biofuel production strategies.

Potential drawbacks of the use of biofuel systems include

the diversion of food crops into fuel, added greenhouse gas

emissions, low profitability, loss of soil quality, drawdown of

water resources, spread of invasive species and increased

non-point source pollution [21]. A key factor for maintaining

the economic viability of the biofuel sector is sustainable

biomass yield, allowing guaranteed feedstock supply while

preserving food resources. Our study quantified how yields of

photoperiod-sensitive bioenergy sorghum were affected by

location, rotation, fertilization, and residue removal.

2. Materials and methods

2.1. Site description

Field studies were established at two sites in 2008. The first

site was at the Texas AgriLife Research Farm near College

Station (ARECCS), TX (30.32�N, 94.26�W, ca. 60 m msl). This

region has a mean annual temperature of 20 �C and averages

97.8 cm of annual precipitation. Soil at the site is classified as

a Weswood silty clay loam (Fine, mixed, thermic Udifluventic

Ustochrept). The second site was at the Texas AgriLife

Research and Extension Center near Weslaco, TX (ARECW)

(26.22�N, 98.23�W ca. 5 m msl). Unlike ARECCS, mean annual

precipitation is lower at 59 cm, but mean annual temperature

is higher at 23.3 �C. The soil type is a Hidalgo sandy clay loam

(Fine-loamy, mixed, active, hyperthermic Typic Calciustoll).

Prior to the study, the field near College Station was in cotton

production in 2007, and rotated annually with corn. Corn was

grown at the Weslaco site. Both fields were under conven-

tional disk tillage.

2.2. Experiment design

The experiment used a randomized complete block design

with three treatment factors: crop rotation, nitrogen rate and

residue return. Crop rotations were either continuous bio-

energy sorghum or biannual rotation with corn. Sorghumwas

planted in the continuous sorghum treatments in both 2008

and 2009, while corn was planted in the rotation treatment in

2008 followed by sorghum in 2009. Nitrogen was applied to

sorghum at either 0 or a non-limiting rate: 336 kg ha�1 in 2008

and 280 kg ha�1 in 2009. Nitrogen application to corn was

either 0 or 168 kg ha�1. Nitrogen as urea was sidedress applied

15-cm deep approximately 6 weeks after planting at the 4-to-

5-leaf stage for sorghum and the 6-to 8-leaf stage for corn.

Residue return rates were 0, 25 or 50% of sorghum biomass

yield at harvest. All corn stover was returned. Each possible

combination of residue return, fertilization, and crop rotation

was replicated four times across both locations.

At both College Station and Weslaco, an additional treat-

ment was included with 0% residue return, but where nutri-

ents removed in aerial sorghum biomass (P, K, Ca, Mg, Mn, Zn,

Page 3: Management effects on bioenergy sorghum growth, yield and nutrient uptake

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4 595

Fe, andCu)were returned inmineral formprior to planting the

subsequent crop. These plots also received the non-limiting N

rate. At Weslaco, an extra treatment was implemented due to

the importance of sugarcane (Saccharum sp.) production in the

region. This treatment received the equivalent of 100% of dry

biomass removed as sugarcane “mill mud”. Mill mud is

a byproduct of sugarcane milling, consisting of processed

sugarcane leaf and stalk material, soil, and lime added during

the clarification process. The material is a source of N, P, and

Ca. This treatment also received non-limiting N fertilization.

These additional treatments were replicated four times at

their corresponding locations, resulting in a total of 56 plots at

College Station and 64 plots atWeslaco. Fields were blocked to

help control variation, with treatments being randomly

assigned within each block.

Plots were 9.14-m long, four rows wide and planted on 102-

cm row centers, giving a total plot width of 4.08 m. The bio-

energy sorghum used in this study was “4-Ever Green”,

a modern photoperiod-sensitive, one-cross hybrid with high

biomass yield and low lodging potentials (Walter Moss Seed

Co, Waco, TX, U.S.A.). Planting dates ranged from late March

to late April (Table 1), with a seeding rate of 160,000 ha�1.

Bioenergy sorghum and corn were managed under conven-

tional disk tillage. After the final harvest each year, plots were

disked three times to a depth of 15e20 cm, and bedded (see

Table 1 for a list of field operations). Furrow irrigation was

minimally performed as needed and dates and amounts are

also given in Table 1.

2.3. Soil methodology

Composite soil samples for separate depths from each

experimental unit were formed from three soil cores taken at

depth increments of 0e5, 5e15, 15e30, 30e60, and 60e100 cm.

Initial samples were taken in March 2008 prior to the begin-

ning of the study. Samples were oven dried at 60 �C for 7 d,

ground using a flail grinder and sieved to pass through

Table 1 e Field operations and dates performed at College Stat

Operation

2008

College Station W

Soil sampling 24th March 16th

Pre-plant disking 25th March 21st

Interrow cultivation 24th April 12th

Bedding 15th October 4th

Irrigation 10th June 9 cm 25th

10th July 9 cm 2nd

e 3rd

e e

e e

e e

Pre-plant herbicide application 3rd March n/a

Planting 26th March 23rd

Post-plant herbicide application n/a 24th

Fertilization 1st May 29th

Harvest 5th August 14th

14th October 2nd

1.75 mm mesh. Soil pH was determined in 2:1 (water:soil)

suspensions. Residual soil inorganic nitrate-N was extracted

(10:1 solution:soil) with a KCl solution made by dissolving

74.54 g KCl per L of H2O, reduced to nitrite using a cadmium

column, and analyzed using spectrophotometric methods

[22]. Mehlich III extractable nutrients including P, K, Ca, and

Mg were extracted using a method adapted from Mehlich [23]

and measured by inductively coupled spectroscopy (ICP). A

subsample of each composite sample was finely ground with

a puck-and-ring grinder and analyzed for organic and inor-

ganic C and N by combustion [24e26] using an Elementar

Americas Inc, VarioMAX CN analyzer (Mt. Laurel, NJ, U.S.A.).

Differential heating was used to separate inorganic and

organic C. For organic carbon, the primary furnace was set at

650 �C and a 2 L min�1 O2 flow rate. Total N and C were

analyzed with the same instrument at 900 �C [27,28].

2.4. Plant methodology

Biomass sorghum plots were harvested using hand imple-

ments and cut to leave a short stubble (ca. 10 cm) in August

and October 2008 and November 2009 at ARECCS, and in

August and December 2008 and January 2010 at ARECW. For

determination of yield, the two inner rows of each plot were

hand-harvested for yield in 2008 and harvested with

amechanical harvester in 2009. Harvests in 2009 were delayed

at both locations by excessively wet conditions. Residue cor-

responding to 25 and 50% of harvested biomass were returned

to appropriate plots after each harvest.Water content of aerial

plant biomass from each plot was determined by randomly

selecting 5 plants, chopping in a commercial chipper/

shredder, and taking an approximately 600-g subsample.

Subsamples were weighed, oven dried at 60 �C for 7 d, and

then re-weighed to determine moisture content.

Dried plant samples were initially ground to pass a 1-mm

sieve and then powdered in a ring and puck mill prior to total

elemental analysis for C and N by combustion [24] using an

ion and Weslaco, Texas.

Year

2009

eslaco College station Weslaco

April 6th April 26th January

April 6th April 3rd March

May 5th June 27th April

December 6th November 17th Februrary

April 8 cm 16th July 6 cm 12th April 4 cm

June 5 cm 24th August 6 cm 18th May 4 cm

July 5 cm e 9th July 5 cm

e 21st July 3 cm

e 10th August 3 cm

e 5th September 3 cm

9th March 10th April

April 7th April 13th April

April n/a 1st May

May 20th June 19th May

August 5th November 6th January

December n/a n/a

Page 4: Management effects on bioenergy sorghum growth, yield and nutrient uptake

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4596

Elementar Americas, Inc, CNSAnalyzer (Mt. Laurel, NJ). Total P

and K were determined after nitric acid digestion [29] using

a Spectro Arcos ICP (Kleve, Deutschland). Total accumulation

of each element in aerial biomass was calculated as dry

yield � total elemental concentration.

Leaf chlorophyll readings were made using a Minolta 502

SPAD meter (Spectrum Technol., East Plainfield, IL, U.S.A.).

Readings were taken about one third of the distance from the

tip of the leaf to the base and halfway between themidrib and

the leaf edge. The youngest collared leaf was chosen for each

reading. Height and SPAD measurements were taken period-

ically during the growing season at College Station in 2008 and

approximately biweekly at both locations in 2009. At each

measurement, fifteen SPAD observations and five height

measurements were taken from randomly chosen plants in

each plot with one reading taken per plant. Readings were

averaged into a single measurement for each plot.

2.5. Statistical analysis

Plant characteristics, nutrient uptake, and yield changes due

to crop rotation, residue return, nitrogen fertilization, location

and their interactions over the course of the experiment were

analyzed using Mixed Model procedures [30]. Analysis of

variance (ANOVA, PROC Mixed) was performed to identify

differences caused by rotation, fertilization, residue return,

and their interactions. Means separationwas performed using

SAS macro “pdmix800” [31] with a Fisher’s Least Significant

Difference test type one error rate of 0.05% (a ¼ 0.05) after

overall treatment significance was established using ANOVA

(P < 0.05).

Multiple linear least square regression models were

developed to determine which factors and combinations of

factors were related to yield. Models excluded non-significant

factors and included those that explained a significant portion

of biomass sorghum yield variation. Models were developed

using McHenry’s algorithm, a variable selection technique

which seeks the best subset through an iterative process

based on maximizing the coefficient of determination (R2) of

each variable combination. This variable selection technique

was chosen because the regression utilized management

factors as categorical variables and McHenry’s algorithm can

Table 2 e Soil information for bioenergy sorghum research sit

Property

College station

0e5 5e15 15e30 30e60 60e

TC g kg�1a 16.6 15.3 14.5 14.0 1

OC g kg�1 9 7.4 5.8 4.0

TN g kg�1 1.0 0.9 0.8 0.6

NO3 mg kg�1 6 6 6 5

P mg kg�1 24 26 17 6

K mg kg�1 244 236 182 127 10

Ca mg kg�1 753 654 800 1320 126

Mg mg kg�1 243 238 230 228 24

S mg kg�1 22 22 21 27 2

a TC, OC, and TN represent total C, organic C, and total N, respectively.

consider groupings of categorical variables together for

inclusion in or deletion from the model, as a single unit [32].

Potential models were then evaluated through multiple

regression to estimate each variable’s significance and coef-

ficient, ultimate model performance and interpretation. The

“Multivariate Variable Selection and Multiple Regression”

analyses of NCSS 2004 were used [33]. Variables with proba-

bility levels lower than 0.05 were designated significant. The

resultant model quantified yield components as a function of

management and observable sorghum physical traits.

3. Results and discussion

3.1. Site characteristics

TheWeswood soil near College Station is calcareous and near

surface samples rated very low for extractable NO3eN,

moderate for P, and high for K, Ca and Mg (Table 2). The Hil-

dalgo soil at Weslaco was calcareous below 30 cm and near

surface samples rated low for extractable NO3eN, moderate

for P and Ca, very high for K, and high Mg. Soil organic C and

total N were slightly higher in the Weswood soil, especially at

depths above 30 cm. Although soils ranked very low or low in

extractable NO3 in surface samples, significant residual NO3

was observed with depth, especially in the Hildalgo soil.

Air temperatures at College Station were higher than

historic averages during both the 2008 and 2009 growing

seasons (Fig. 1). In August 2008, Hurricane Ike passed near

CollegeStation,depositingover17cmofprecipitation just after

the first sorghum harvest. Air temperatures at Weslaco were

below average for the 2008 growing season and near normal in

2009 (Fig. 2). Hurricane Dolly passed nearWeslaco in July 2008,

resulting in severe lodging and depositing 30.4 cm of rainfall

over twodays.Bothsiteshadhigher thanaverage rainfall in the

fall of 2009, which may have improved late-season growth.

3.2. Height

Plant height has been reported to be a useful indicator of dry

matter yield in photoperiod sensitive sorghum [34]. Biomass

sorghum in this study displayed increasing height throughout

es at College Station and Weslaco, Texas in 2008.

Depth cm

Weslaco

100 0e5 5e15 15e30 30e60 60e100

4.7 5.8 5.9 5.6 6.0 12.4

3.5 5.9 5.7 5.5 4.6 4.8

0.6 0.8 0.8 0.8 0.7 0.7

4 13 17 14 13 14

4 40 39 32 17 19

6 489 474 381 281 217

8 467 514 476 561 1115

7 356 354 357 396 431

8 22 27 28 33 46

Page 5: Management effects on bioenergy sorghum growth, yield and nutrient uptake

Jan.

Feb.

Mar. Apr. May

Jun. Ju

l.Aug

.Sep

.Oct.

Nov.

Dec.

Mo

nth

ly P

recip

itatio

n cm

0

10

20

30

40

Mo

nth

ly T

em

peratu

re o

C

0

10

20

30

40

20082009Long-term Avg.20082009Long-term Avg.

Fig. 1 e Summary of weather data at the Texas A&M

University AgriLife Research and Extension Center at

College Station, Texas for 2008 and 2009 along with

30-year site averages. Lines refer to monthly average

temperature, while bars are monthly precipitation.

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4 597

the growing season in both years due to the photoperiod-

sensitive characteristic of delayed flowering. Sorghum

height was significantly increased (P < 0.01) by N application

at College Station (Fig. 3A) in 2008. Significant differences

(P < 0.01) in sorghum height were observed due to location,

rotation, and N fertilization in 2009 (Fig. 4). As might be ex-

pected, sorghum height trends were similar to those observed

with dry matter yield, with fertilized and rotated sorghum

being taller than unfertilized continuous sorghum. Heights at

Weslaco were greater than those at College Station (P < 0.01)

and rotated sorghum was significantly taller than continuous

sorghum (P < 0.05). Sorghum fertilized with N also was

significantly taller than unfertilized controls throughout most

of the observed period (P < 0.01).

3.3. SPAD measurements

Increasing SPAD readings have previously been positively

correlated with N rate [35] and chlorophyll content [36] in

Jan.

Feb.

Mar. Apr. May

Jun. Ju

l.Aug

.Sep

.Oct.

Nov.

Dec.

Mo

nth

ly P

recip

itatio

n cm

0

10

20

30

40

Mo

nth

ly T

em

peratu

re o

C

0

10

20

30

40

20082009Long-term Avg.20082009Long-term Avg.

Fig. 2 e Summary of weather data at the Texas A&M

University AgriLife Research and Extension Center at

Weslaco, Texas for 2008 and 2009 along with 30-year site

averages. Lines refer to monthly average temperature,

while bars are monthly precipitation.

sorghum. Readings in our study varied with sampling date

during each growing season. Others also reported SPAD

reading variation through the growing season in stay-green

sorghum [35] and corn [37]. Fertilization significantly

increased (P < 0.01) SPAD readings throughout the growing

season at College Station in 2008 and 2009 (Figs. 3B and 5A).

Both fertilization and rotation affected SPAD readings

throughout the 2009 growing season (P < 0.01), with differ-

ences generally following the same trends as yield and height

(Fig. 5A). SorghumatWeslaco generally exhibited higher SPAD

readings than at College Station (Fig. 5B). Continuous, unfer-

tilized sorghum showed significantly lower SPAD values than

all other treatments throughout most of the growing season,

especially at College Station (P < 0.05). Rotation generally had

a stronger influence than fertilization on readings at both

locations. This effect was more pronounced at Weslaco,

possibly because of greater residual soil NO3with depth at this

location (Table 2). SPAD values tended to decrease for all

treatments after approximately the 8th of June at College

Station. Readings at Weslaco decreased slightly from early in

the season to the 4th of June and then increased significantly

for all treatments. Plots at Weslaco were irrigated on 9 and 21

of July 2009 (Table 1) and this may partially account for

increased SPAD values after these dates. Plots at College

Station received irrigation on 16 July and 24 August 2009, but

did not affect SPAD values. A higher photosynthetic capacity

with increasing SPAD reading may be partly responsible for

the increased yields observed in these treatments [38].

3.4. Bioenergy sorghum yield

Total annual yield at both locations was significantly affected

by application of N fertilizer (P < 0.1) in 2008, but did not differ

across locations. Total yield of fertilized sorghum in 2008 was

23.11 � 2.02 t ha�1 at College Station and 22.53 � 2.4 t ha�1 at

Weslaco (Fig. 6). Yields from the first harvest were greater

than the second at both locations, but the portion of total yield

from the first harvest was greater at College Station. Returning

25 or 50% of the biomass produced during the first harvest in

2008 resulted in significantly greater yield in the second

harvest at College Station compared to complete removal of

biomass (Fig. 7). Total yield, was also affected by biomass

return at College Station, being highest with 25% return.

However, neither the first or second harvest nor total yields

were influenced by this factor at Weslaco in 2008. For the first

harvest, no effect of biomass return was expected since

residue return treatments were implemented beginning after

the first cutting in August 2008. Soil quality parameters related

to soil organicmatter and residue return typically take time to

become evident. For example, Powell and Hons [9] observed

that 50% removal of energy sorghum aboveground biomass

resulted in reduced soil quality parameters and yields after

three years. However, in the second harvest of 2008 at the

College Station site, residue return increased yield (P < 0.05).

This site only received natural precipitation after the first

harvest and 2008 was drier than normal (Fig. 1). Increased

yield with residue return may have been due to reduced soil

evaporation provided by the additional residue cover. This

hypothesis is supported by the fact that no significant yield

differences due to residue returnwere observed for the second

Page 6: Management effects on bioenergy sorghum growth, yield and nutrient uptake

Heig

ht, cm

150

200

250

300

350

400

450

+ N- N

30

35

40

45

50

+ N- N

A B

Fig. 3 e College Station sorghum plant height (A) and SPAD readings (B) In 2008 with or without added N. Bars denote the

standard error.

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4598

harvest at Weslaco, which received two flood irrigations of

approximately 15 cm ha�1 each along with approximately

18 cm ha�1 (Fig. 2) of precipitation between the 1st and second

harvests of 2008.

Of the two cuttings that occurred in 2008, the first harvest

tended to highlight effects of N fertilization at College Station

(Fig. 6), while the effect of residue return was observed on the

second cutting (Fig. 7). Individual yields of the first and second

harvests were not affected by N fertilization at Weslaco, but

total yield was increased by N addition. Nitrogen addition

increased total biomass dry matter yield by about 14% at

College Station and by about 10% at Weslaco in 2008.

First harvest yields at Weslaco in 2008 were slightly lower

than at College Station (Figs. 6 and 7), possibly due to lodging

or stress caused by Hurricane Dolly. Hand harvesting sorghum

in 2008 likely reduced potential yield losses associated with

the severe lodging. The second harvest yields at this location

were greater than at College Station, while total dry matter

yields were similar at both locations.

Total dry biomass yield in 2009 was significantly affected

by site, rotation, fertilization, and the interaction of

rotation � fertilization (Figs. 8 and 9). Mean yield at Weslaco

was 26.1 � 1.2 t ha�1, significantly higher (P < 0.001) than the

mean yield of 20.2 � 1.2 t ha�1 at College Station (Fig. 8). This

difference may have been due to a longer growing season at

Weslaco, given the later harvest date, higher temperatures,

He

ig

ht c

m

0

50

100

150

200

250

300CS + NCS - NSS + NSS - N

A

Fig. 4 e Plant height at College Station (A) and Weslaco (B) In 2

standard error; CS is rotated and SS is continuous sorghum.

and lack of senescence of the photoperiod-sensitive sorghum

used. This site also received significantly more irrigation than

the study at College Station. Fertilization significantly

(P < 0.001) increased yield across location and rotation in 2009

from 20.7 � 1.2 up to 25.1 � 1.2 t ha�1, a gain of approximately

21%. Rotation with corn also significantly (P< 0.001) increased

yield in 2009 across both locations, with continuous sorghum

and rotated sorghum yielding 19.4 and 26.8 t ha�1, an increase

of 38%. Others have reported that rotation of grain sorghum

increased grain yield [14], but less is known about high

biomass sorghums. In Iowa, Buxton et al. [4] found mono-

culture sweet and forage sorghum yields were similar to those

that were rotated.

The interaction of rotation � N fertilization was also

significant (P< 0.001) for total dry biomass yield in 2009 (Fig. 8).

Continuous sorghum responded more to fertilization,

although rotated sorghum yields were higher. Absolute

responses to N fertilization were 3.4 and 6.9 t ha�1 for rotated

and continuous sorghum, respectively. Across both locations,

yield was highest in the fertilized rotated treatment, followed

by unfertilized rotated, fertilized continuous sorghum, and

unfertilized continuous sorghum. Of the continuous sorghum

plots, those with 25% biomass returned in 2008 (Fig. 7)

exhibited generally higher mean yields in 2009 (Fig. 9)

compared with 0 or 50% biomass return, though differences

were not statistically significant. Typically, crop residue is

Heig

ht cm

0

50

100

150

200

250

300CS + NCS - NSS + NSS - N

B

009 as affected by added N and rotation. Bars denote the

Page 7: Management effects on bioenergy sorghum growth, yield and nutrient uptake

SP

AD

R

ead

in

g

25

30

35

40

45

50 CS + NCS - NSS + NSS - N

SP

AD

R

ead

in

g

25

30

35

40

45

50 CS + NCS - NSS + NSS - N

A B

Fig. 5 e SPAD readings at College Station (A) and Weslaco (B) during 2009 as affected by added N and rotation. Bars denote

the standard error; CS is rotated and SS is continuous sorghum.

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4 599

needed to maintain soil organic matter, which is critical to

nutrient cycling and in soil physical, chemical, and microbial

quality. Powell and Hons [9] noted significant impacts on

sorghum yield due to complete residue removal within three

years of treatment imposition. Although the current study did

not observe overall yield impacts due to residue return, the

experiment is in its’ initial stages and will be ongoing to

determine the long-term effects of biomass removal.

Biomass yields in the mineral replacement þ N fertilizer

treatment were similar to other treatments that also received

N fertilization in 2009 at both locations (Fig. 9). The mill

mudþN treatment at Weslaco also resulted in biomass yields

similar to other treatments receiving N. This supports the

conclusion that mineral depletion due to biomass removal

was not a significantly limiting factor to yield at this time.

3.5. Plant nutrient concentration and uptake and carbonfixation

Site, N fertilization, and rotation affected plant C fixed and

uptake of N, P, and K, while biomass return had no effect

(Tables 3 and 4). Overall at both study sites, sorghum biomass

contained approximately 9.5 t ha�1 of C, and 254, 20, and

375 kg ha�1 of N, P, and K, respectively in 2008. In 2009, total

aboveground biomass contained approximately 9.75 t ha�1 of

C, and 173, 27, and 310 kg ha�1 of N, P, and K. When averaged

across sites, biomass yield was greater in 2009 than 2008,

while N, P, and K removals were lower, possibly indicating

lower nutrient availability after only one year of cropping.

Site affected total nutrient uptake both years (P < 0.01),

with Weslaco having higher nutrient uptake and plant tissue

nutrient concentrations in both study years (Tables 3 and 4).

Besides higher extractable soil nutrients at this site as already

discussed, the longer growing season and higher tempera-

tures at this site may also have had an effect.

Site, N fertilization, and rotation influenced C, N, P, and K

concentrations in sorghum biomass, while biomass return

had no effect on concentrations (Table 3). Sorghum biomass

had greater C concentrations at College Station each year, but

lower concentrations of N, P, and K. Soil at Weslaco had

greater residual NO3eN and greater extractable P and K

throughout the profile compared to College Station (Table 2).

Adding N fertilizer increased the C concentration of biomass

in 2008 and increased N concentrations both years, but had

minimal effects on P and K concentrations. Biomass of rotated

sorghum showed increased C concentration compared to

continuous, but lower N, P, and K concentrations. The latter

effect was likely due to nutrient dilution in the greater yield of

rotated sorghum.

Nitrogen fertilization affected total C fixation, andN, K, and

P uptake at both locations in 2008 and 2009 (Tables 3 and 4).

Tissue concentrations of N were significantly increased by N

fertilization (P < 0.01) both years (Table 3). Nitrogen fertiliza-

tion significantly increased (P < 0.01) total C fixed via photo-

synthesis at both locations during both years. In 2008, total

aboveground C fixed was 9.4 � 0.3 t ha�1 in fertilized plots,

while unfertilized plots fixed 8.3� 0.3 t ha�1 (P< 0.01). In 2009,

differences in C fixation due to fertilization were greater

(P < 0.001), with unfertilized sorghum fixing approximately

9� 0.2 t ha�1 and fertilized sorghumfixing 11� 0.2 t ha�1. Crop

nitrogen uptake was increased both years by N fertilization

due to higher plant N concentrations and biomass yields.

Greater P and K uptake was associated with higher yield with

N application.

Rotation also affected nutrient uptake and C content in

2009 (P< 0.01). Rotated sorghum exhibited significantly higher

fixed C (11 � 0.2 t ha�1), and N (185 � 7.9), P (28 � 1.0), and K

(346� 9.7 kg ha�1) uptake comparedwith continuous sorghum

that contained 8 � 0.2 t ha�1 of C, and 161 � 7.9, 26 � 1.0, and

274 � 9.7 kg ha�1 of N, P, and K, respectively. Continuous

sorghum showed significantly higher (P < 0.01) tissue

concentrations of P (1.3 � 0.05) and K (13.9 � 0.05) g kg�1 than

rotated sorghum (1.0 � 0.05) and K (12.7 � 0.05) g kg�1.

Concentrations of these nutrients were likely lower in rotated

sorghum because of dilution associated with greater yield.

3.6. Regression analysis of biomass sorghum yieldcomponents

To better understand the relationships betweenmanagement

and yield, components explaining variation in yield were

studied through regression analysis. The original parameter

set encompassed many potential variables and their interac-

tions. To identify the smallest subset of properties for

Page 8: Management effects on bioenergy sorghum growth, yield and nutrient uptake

Location

Yie

ld t

ha

-1

0

5

10

15

20

25

30 - N+ N

Location

Yie

ld t

ha

-1

0

5

10

15

20

25

30 - N+ N

Location

College Station Weslaco

Yie

ld t

ha

-1

0

5

10

15

20

25

30 - N+ N

A

B

C

Fig. 6 e Bioenergy sorghum dry matter yields in 2008 near

College Station and Weslaco, Texas for the first cutting (A),

second cutting (B) and total annual yield (C) As affected by

nitrogen fertilization. Error bars denote the standard error.

Yie

ld t

ha

-1

0

5

10

15

20

25

30 0% Return25% Return 50% Return

Yie

ld t

ha

-1

0

5

10

15

20

25

30 0% Return25% Return50% Return

Location

College Station Weslaco

Yie

ld t

ha

-1

0

5

10

15

20

25

30 0% Return25% Return50% Return

A

B

C

Fig. 7 e Bioenergy sorghum yields in 2008 near College

Station and Weslaco, Texas for the first cutting (A), second

cutting (B) and total annual yield (C) as affected by biomass

return. Error bars denote the standard error.

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4600

meaningful prediction of yield, multivariate variable selection

was performed using McHenry’s algorithm. Ultimately, the

regression used site and management treatments as binary

categorical variables and N rate, sorghum height and SPAD

reading as continuous variables. These variables were chosen

over other potential variables due to their direct interpret-

ability and significance in explaining yield variation (Table 5).

All regression coefficients were significant at least to P < 0.01.

The multiple regression equation to predict biomass sorghum

yield was highly significant (P < 0.001, R2 ¼ 0.67);

Y ¼ 2130:50þ 76:09ðNrateÞ � 0:22ðNrateÞ2þ61:55ðHeightÞþ 181:73ðSPADÞ þ 4651:71ðSequence ¼ CSÞþ 5787:58ðSite ¼ WeslacoÞ;

where Y is yield (kg ha�1), Nrate is added N (kg ha�1), height is

average plant height (cm), SPAD (unitless), sequence ¼ CS is

the rotation of sorghum following corn, and site ¼ Weslaco

indicates location where yield corresponds to biomass

measured at the Weslaco experiment station.

Though height and SPAD measurements were taken

throughout the growing season, those taken in early June of

each year exhibited the strongest relationships with yield, and

Page 9: Management effects on bioenergy sorghum growth, yield and nutrient uptake

College Station Weslaco

Yield

t h

a -

1

0

5

10

15

20

25

30

35CS + N CS - N SS + N SS - N

Fig. 8 e Total sorghum biomass dry yields at College

Station and Weslaco, Texas sites in 2009 with or without

added N. Error bars denote the standard error. CS indicates

corn-sorghum rotation, while SS indicates continuous

sorghum.

College Station Weslaco

Yield

t h

a-1

0

5

10

15

20

25

30

350% + N 25% + N 50% + N 0% - N 25% - N 50% - N

Fig. 9 e Total sorghum biomass dry yields of rotated and

continuous sorghum at College Station and Weslaco sites

in 2009 as affected by N fertilization and residue return.

Error bars denote the standard error.

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4 601

were therefore used in the regression model. Addy et al. [35]

also found SPAD varied through the growing season and

that early season SPAD measurements were useful in yield

prediction of “stay-green” and common grain sorghum.

Results from ANOVA analysis supported the regression

analysis. In the regression, N fertilizationwas significant, with

each kg ha�1 of N fertilizer added, increasing biomass yield

approximately 76 kg ha�1, with a decreasing response rate of

�0.22 kg ha�1 yield per kg2 ha�1 of N fertilizer. This differs

Table 3 e Biomass sorghum tissue nutrient concentrations. CS

Treatment First harvest 2008 Seco

Yield C N P K Yield C

Site t ha�1 g kg�1 g kg�1 g kg�1 g kg�1 t ha�1 g kg�

Weslaco 12.4 409.6 13.0 1.4 22 9.1 399.6

College Station 15.8 414.8 9.9 0.6 17 5.7 415.9

LSD(0.05) 1.9d 3.6c 0.7d 0.1d 1.2d 1.9d 3.6

Fertilization

�N 13.2 410.7 10.7 1.0 20.1 7.0 406.2

þN 15.0 413.8 12.2 1.0 19.1 7.8 409.3

LSD(0.05) 1.9 3.6c 0.7d 0.1 1.2a 1.9 3.6

Rotation

CS e e e e e e e

SS e e e e e e e

LSD(0.05) e e e e e e e

Biomass return

0% e e e e e 6.9 405.5

25% e e e e e 7.8 411.6

50% e e e e e 7.6 406.3

LSD(0.05) e e e e e 2.5 12.2

a Significant at the 0.1 probability level.

b Significant at the 0.05 probability level.

c Significant at the 0.01 probability level.

d Significant at the 0.001 probability level.

from results of Wortmann et al. [39], who showed little

response to nitrogen fertilization in sweet sorghum. However,

the quadratic relationship is common in similar sorghum

crops including sorghum � sudangrass [9,40] and

photoperiod-sensitive sorghum [41]. Plant height measured in

June was directly related to yield, with each additional cm

increasing predicted yield by 61 kg ha�1. Each unit increase of

SPAD resulted in a predicted yield increase of 182 kg ha�1.

Others have linked higher SPAD to increased chlorophyll

concentration in sorghum [36], which can result in increased

indicates rotated while SS represents continuous sorghum.

nd harvest 2008 2009

N P K Yield C N P K

1 g kg�1 g kg�1 g kg�1 t ha�1 g kg�1 g kg�1 g kg�1 g kg�1

8.9 1.1 13 26.1 419.9 7.1 1.4 14.9

10.0 0.8 12 20.2 424.4 8.1 0.9 11.2c 0.7c 0.1d 1.2a ‘ 5.1c 0.6b 0.1d 0.6d

9.0 0.9 12 20.7 423.0 7.0 1.18 13.3

9.7 1.0 12 25.1 424.4 8.2 1.18 13.7

0.7a 0.1 1.2 1.6d 5.1 0.6d 0.1 0.6

e e e 26.8 426.2 7.1 1.0 12.7

e e e 19.4 421.1 8.1 1.3 13.9

e e e 1.6d 5.1b 0.6c 0.1d 0.6d

9.3 1.0 12.2 23.3 422.5 7.6 1.2 12.9

9.7 0.9 12.2 23.5 424.3 7.6 1.1 13.5

9.1 1.0 12.2 22.4 424.2 7.6 1.2 13.6

1.9 0.3 1.3 2.1 6.2 0.8 0.1 0.8

Page 10: Management effects on bioenergy sorghum growth, yield and nutrient uptake

Table 4 e Total biomass sorghum nutrient uptake per unit land area. CS indicates rotated while SS represents continuoussorghum.

Treatment First harvest 2008 Second harvest 2008 2009

C N P K C N P K C N P K

Site t ha�1 kg ha�1 kg ha�1 kg ha�1 t ha�1 kg ha�1 kg ha�1 kg ha�1 t ha�1 kg ha�1 kg ha�1 kg ha�1

Weslaco 5.1 160 18 275 3.7 82 10 116 11.0 182 36 385

College Station 6.7 158 10 266 2.4 56 5 66 8.6 163 18 235

LSD(0.05) 0.7 19.1 1.7d 27.5 0.7a 19.1d 1.7d 27.5d 0.7d 18.7b 3.0d 27.5d

Fertilization

�N 5.5 139 13 261 2.9 64 7 88 8.8 143 24 276

þN 6.2 180 15 280 3.2 75 8 94 10.7 203 30 344

LSD(0.05) 0.7c 19.1d 1.7c 27.5 0.7 19.1 1.7 27.5 0.7d 18.76d 3.0d 27.5d

Rotation

CS e e e e e e e e 11.4 185 28 346

SS e e e e e e e e 8.2 161 26 274

LSD(0.05) e e e e e e e e 0.7d 18.7c 3.0d 27.5d

Biomass return

0% e e e e 2.8 64 7 85 9.9 173 27 306

25% e e e e 3.2 75 8 95 10.0 176 27 317

50% e e e e 3.1 69 8 93 9.5 169 28 308

LSD(0.05) e e e e 0.9 25.6 3.6 28.0 0.9 24.5 3.4 33.6

a Significant at the 0.1 probability level.

b Significant at the 0.05 probability level.

c Significant at the 0.01 probability level.

d Significant at the 0.001 probability level.

y = 7.81+0.65*x (r2=0.67)95 % regression confidence interval95% prediction interval

0

5

10

15

20

25

30

Weslaco RSWeslaco SSCollege Station RSCollege Station SS

Weslaco CSWeslaco SSCollege Station CSCollege Station SS

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4602

yield. Rotation increased predicted biomass sorghum yield by

approximately 4.6 t ha�1. Few have documented the rotation

effect on biomass sorghum yields, but rotation has been

shown to improve grain sorghum yield [42], but may lower

apparent N use efficiency [43]. The location at Weslaco had

soil with higher extractable nutrients and a longer growing

season, which may explain the increased yield prediction of

5.8 t ha�1 when this termwas included in themodel. The deep

rooting pattern and photoperiod sensitivity of biomass

sorghum may allow it to capitalize on both of these factors

[44]. Linear regression of model predicted vs. observed yield

confirmed a linear relationship, normal distribution, and

goodness of fit r2 ¼ 0.67 (Fig. 10).

Table 5 e Parameter estimates for regression of biomasssorghum yield (kg haL1) in 2008 and 2009 onmanagement factors of sequence (CS [ corn-sorghum,SS [ continuous sorghum), site (College Station orWeslaco), nitrogen fertilization rate (Nrate, kg haL1),plant height (height, cm), and chlorophyll meter readings(SPAD, unitless). Parameter estimates are kg haL1.

Yield component Parameterestimate

F prob. Model R2

Partial Total

Intercept 2130.5 � 3115.5 0.496 0.00 0.00

Site ¼ Weslaco 5788.6 � 764.1 0.000 0.26 0.27

Sequence ¼ CS 4651.7 � 721.5 0.000 0.14 0.4

Nrate 76.1 � 25.9 0.004 0.12 0.53

Nrate2 �0.2 � 0.1 0.013 0.09 0.62

Height 61.6 � 10.6 0.000 0.027 0.65

SPAD 181.8 � 70.5 0.011 0.021 0.67

0 5 10 15 20 25 30 35

Fig. 10 e Relationship of actual yield to that predicted from

an optimized multiple regression analysis in studies

conducted at Texas AgriLife Research and Extension

Centers near Weslaco and College Station, Texas in 2008

and 2009. CS indicated corn-sorghum rotation, while SS

indicated continuous sorghum.

4. Conclusions

Biomass sorghum dry yields exceeded 25 t ha y�1 in optimized

systems within this study. Nitrogen fertilization increased

yields of rotated and continuous sorghum at both study sites.

A quadratic response curve indicated diminishing return on N

input, and the optimumN rate should be based on production

conditions. Although continuous sorghum responded to

fertilization, N addition could not fully compensate for

Page 11: Management effects on bioenergy sorghum growth, yield and nutrient uptake

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 5 9 3e6 0 4 603

differences in yields due to rotation. Rotation had a large

effect on sorghum biomass yield, and will likely be important

in maintaining long-term productivity. Over two years,

sorghum yields were insensitive to biomass return, indicating

that even with complete biomass removal, short term

productivity may remain high in systems with higher soil

fertility. However, uptake of N, P, and K declined from the first

to the second year even though average yield increased,

possibly indicating a decrease in soil nutrient availability after

only two years.

Variation in yield and nutrient uptake due to experiment

site illustrated the importance of designing biomass produc-

tion strategies tailored to specific regions. SPAD readings and

height were directly related to yields. Reduced early season

SPAD readings and plant height were indicative of lower yield,

indicating a potential for assessment of in-season N needs.

Research is ongoing to determine the effect of biomass

removal and management variables on longer-term yield and

soil quality.

Acknowledgments

We thank Landon Crotwell, Martha Wight, Jim Florey,

Jeff Morris, Justin Ng, Katie Rothlisberger, Vince Saladino, and

Eric Smith for their assistance. This research was funded by

the Texas AgriLife Research Cropping Systems Program and

USDA/NIFA Agriculture and Food Research Initiative (grant

#2011-67009-30050). Seed was supplied by the Walter Moss

Seed Company.

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