1. Sorghum Feedstock Performance Tests:
Coordinator: W.L. Rooney Texas A&M University
Collaborators:
Scott Staggenborg, Kansas State University
Ken Moore, Iowa State University
Todd Pfieffer/Michael Barrett, University of Kentucky
Bissondat Macoon, Mississippi State University
Ron Heiniger, North Carolina State University
Gary Odvody, Texas Agrilife Research
Jim Heilman, Texas A&M University
Jeff Pedersen, USDA-ARS

2. Objectives Establish yield parameters for different types of sorghums
Establish quality parameters for different sorghums across environments
Sustainability Analysis

4. Sorghum Experimental Design
Medium experimental units (0.05 to 0.10 ha)
3 to 4 replications
Nitrogen as recommended for forage sorghum production
Rainfed, no supplemental irrigation
Harvest
Single, end of season Harvest (2008)
Multiple, optimized to Type (2009)
6 Genotypes (varies in year)
Biomass Yield (Fresh, Dry),
Height
Maturity
Composition

5. 2008

6. Sorghum Hybrid Selection - 2008
Forage Sorghum Hybrids
Graze-All, Graze-n-Bale
PS and PI
Silage Sorghum Hybrids
22053 and Sugar-T
PS and PI, BMR and bmr
Sweet Sorghum Variety
M81-E
Grain Sorghum (check)
No energy sorghum hybrids available in 2008

7. 2008 Results Harvestable Yield in 6/7 locations Yields Composition
Iowa – not planted due to wet spring
Planting Dates - mid March to early June
Harvest Date - late September to late November
Yields
Dry Weights
9 Mg/ha (grain check) to 26.2 Mg/ha (PS Forage Hybrid)
Composition
Biomass composition samples collected in most locations

8. 2009

9. Sorghum Hybrid Selection - 2009
Forage Sorghum Hybrids
Graze-All (PI)
Graze-n-Bale (PS)
Silage Sorghum Hybrids
22053, PS bmr
Sugar-T, PI
Sweet Sorghum Variety
M81-E
Energy Sorghum
TAM08001

10. 2009 Results Harvestable Yield in 6/7 locations
CC, Texas – not planted due to extreme drought
Yields – generally very good
Composition
Biomass composition samples collected in most locations (2008 and 2009)
NIR Scans completed in CS
Sorghum composition model co-developed by NREL and TAMU to estimate fiber composition.

11. Trials Overview Trial Location Planting Dates Lead PI
Major Factors (freeze, flood, draught, etc.)
Harvest Date(s), Length of Harvest, & Harvest Process
Obstacles to Data Collection
Other Information?
College Station, Texas
Annually in late March or early April
Rooney
Very dry in 2009 with moisture early and late
July/Oct
Extremely wet fall made harvest difficult
Manhattan, KS
Early May
Staggenborg
Below average temps and above average moisture
Sept/Oct
Ames, IA
Mid to Late May
Moore
Average year
September
Lexington KY
Pfieffer/Barrett
Average temps, good moisture
Discuss basic trial information such as:
Locations of each trial
Planting dates for each trial
Lead PI of each trial
Major factors affecting trial establishment (freeze, flood, drought, loss of PI, etc)
Harvest dates, length of harvest
Discuss the harvest process, methods used, obstacles to data collection

12. Trials Overview (continued)
Trial Location
Planting Dates
Lead PI
Major Factors (freeze, flood, draught, etc.)
Harvest Date(s), Length of Harvest, & Harvest Process
Obstacles to Data Collection
Other Information?
Mississippi
April, replant in June
Maccoon
Average climate, but herbicide damage from drift required replant
August to October
Plymouth NC
Late April/early May
Heininger
Excellent Year
July to October
Corpus Christi, Texas
Mid March
Odvody
Drought, did not even plant.
None
Not Planting
Discuss basic trial information such as:
Locations of each trial
Planting dates for each trial
Lead PI of each trial
Major factors affecting trial establishment (freeze, flood, drought, loss of PI, etc)
Harvest dates, length of harvest
Discuss the harvest process, methods used, obstacles to data collection

13. Texas – Burleson County
Variety (# cuts)
Fresh Weight (MT/ha)
Moisture %
Dry Weight (MT/ha)
BRIX %
Height (m)
Days to Flowering
Grazeall 3 (2)
30.8 77
7.0
12.5
2.4 60
Graze-n-Bale (2)
44.9 81
8.5
7.7
2.2 No
22053 (2)
38.3 75
9.4
14.2
3.0 99
TAM8001 (1)
48.4 70
14.5
8.4
2.8
M81E (1)
45.3 82
8.7
10.1
140
Sugar T (2)
56.1
12.9
12.8
2.9 85

14. Iowa - O'Brien County Variety (# cuts) Fresh Weight (MT/ha) Moisture %
Dry Weight (MT/ha)
BRIX %
Height (m)
Grain (MT/ha)
Grazeall 3 (1)
98.4 76
23.0
13.0
2.7
1.07
Graze-n-Bale (1)
107.7
26.5
9.5
3.0
0.00
22053 (1)
69.5 75
16.4
10.1
0.74
TAM8001 (1)
47.3 72
13.4
11.7
3.1
M81E (1)
67.1
15.8
13.1
0.98
Sugar T (1)
57.6
14.4
14.8
2.9
4.38

15. North Carolina – Washington County
Variety
(# cuts
Fresh Weight (MT/ha)
Moisture %
Dry Weight (MT/ha)
BRIX %
Height (m)
Days to Flowering
Grazeall 3 (2)
110.9 80
18.9
8.4
2.3 45
Graze-n-Bale (2)
100.8
15.4
7.1
2.2 No
22053 (2)
69.7 74
17.9
11.0
3.1 90
TAM8001 (1)
104.3 67
34.7
9.9
4.5
M81E (1)
111.0 72
30.9
10.9
3.6
105
Sugar T (1)
97.5 76
23.5
11.8

16. Combined – mean (range)
Variety (# cuts)
Fresh Weight (MT/ha)
Moisture %
Dry Weight (MT/ha)
Grazeall 3
64.7
(19, 110)
74.0
(63, 80)
16.8
(7, 23)
Graze-n-Bale
73.4
(40, 108)
76.0
(67, 81)
17.6
(9, 27)
22053
52.2
(31, 70)
73.5
(70, 75)
13.8
(9, 18)
TAM8001
60.0
(39, 104)
68.0
(63, 72)
19.2
(13, 34)
M81E
65.9
(40, 111)
75.5
(72, 82)
16.1
(9, 31)
Sugar T
61.5
(34, 98)
(66, 77)
16.3
(12, 24)

17. Yield Data and Interpretation
Multiple Cut Hybrids provide greater window of harvest, more cost/harvest
Single Cut Hybrids provide total yield in single harvest reduce cost/harvest
Yield of top MC, SC in year is similar
Adaptation:
Photoperiod Sensitive
Higher Yielding
Less susceptible to drought

18. Composition Sample Collected Composition will be estimated
NIR Calibration Curve
Collaborative with NREL, NSP
Standardization is critical
Estimate on all over years for GxE study

20. Carbohydrate Composition
Table 3 Summary of the chemical composition data obtained on the calibration set using dietary fiber analysis
 Constituent N
Mean
Std Dev
Min
Max
Range
CV†
Lignin 97
13.8
2.9
9.2
20.6
11.4
21.0
Xylan
16.5
2.7
10.8
22.5
11.7
16.6
Glucan
32.8
5.1
21.9
47.4
25.5
15.4
Solubles
23.1
8.0
11.0
44.0
32.9
34.8
Data are expressed as wt% dry basis
†CV, Coefficient of variation

21. NIR Curve Development
Table 5 Summary of the NIR calibration models built for predicting lignin, xylan, glucan, and solubles
Constituent
Multivariate procedure
Math Pre-treatments
# PCs† N‡
Mean
SEC R2
SECV
R2 for CV
Lignin
MPLS
; MSC 9 90
13.62
0.74
0.93
1.12
0.84
Xylan
PLS
; D 94
16.45
1.34
0.76
1.65
0.64
Glucan
Solubles
†Number of principal components included in the model
‡Number of samples used in building the calibration model

22. Sustainability
Sustainability analysis initiated in College Station in 2009
Soil Carbon
Nitrogen Requirements
Initial collections in 2009, no information available as of now.

23. 2010 Plans
Continue testing, further refining of hybrid variety selections.
Compile three year averages
Location
Hybrids
Additional Emphasis
Composition Analysis
Nutrient Analysis
Economic Analysis
Additional Locations