1. Maize trials in Denmark -from design to result
Janne Aalborg Nielsen
M.Sc.,Teamleader

2. Maize variety trials in Denmark
In Denmark app. 100 maize varieties for whole silage are tested – why so many?
Denmark is the Northern limit for growing maize for whole silage
There is a large and intensive dairy farming industry
All breeders can register any variety either for official testing or for supplemental testing

3. Size of the trials
2.6 ha

4. Challenges
Experimental design - how to minimize the variation due to large experimental area
Sowing single plots efficiently
Harvest within as short a time span as possible

5. Challenges - continued
Determining dry matter and minimizing the differences in dry matter content between varieties
Eliminating the influence of the harvest time during the day by correct sampling
Efficient and secure handling of data

6. Experimental design Many treatments – a higher experimental error
Reducing the change of obtaining a significant result
Differences between varieties are small
In this case it is widely recognized to apply an incomplete block design (Williams, 2000)

7. Experimental design - continued
2006: The incomplete block design was implemented for variety testing of maize
The randomization plan is created in “PC-Field Trial (in the “Nordic Field Trial System”)
The algorithm is based on a “dll” from the “CycDesign” program

9. Sowing single plots Same germination conditions
As short a period as possible
Germination percentage, grain weight
Grains are weight out
Number of plants in every variety is exactly the same
Arranged according to the randomization plan

10. “Baural” single plot sower
5-6 hours

12. Growing season

13. Harvest Not all the varieties reach maturity at the same time
Most correctly to harvest at the time when dry matter content is as desired for each variety
Not possible
The data is not available prior to harvest
Very costly to harvest at different periods

14. Harvest - continued
Whole silage maize is harvested when the dry matter is app. 30 percent
“Champion” maize cutter mounted with a “Haldrup” weighing and sampler unit*
Eliminating inter plot competition**

16. Harvest - continued Yield is measured on a “Mettler” weight
Data automatically transferred to a computer in the tractor*
“Haldrup Harvest Manager”
Randomization plan is imported from PC-Field Trial**

18. Sampling Plot sample is drawn from the harvested mass
App. 1 kg is taken*
Perforated plastic bag, bar code label (precise ID)*
The sample is weighed*
Data send to a computer in the tractor**

22. Sampling - continued Samples placed in a trailer* Semi heated air*
Starting the drying process of the sample
Dries in the trailer for hours
Moved to the drying oven*
Dries for 18 hours at 60 °C**

24. Drying of samples

26. Advantages
1) The determined dry matter will exactly match the measured yield and thereby eliminate fluctuations in dry matter during the day;
2) The quality analysis will be more reliable because this fixes the content of sugar and starch. In air tight bags the sample will start to ensile or rot which can result in useless results from the laboratory.

27. Quality analysis Plot samples are subdivided
Send to the laboratory for quality analysis

28. Quality analysis Crude protein, % in dry matter
Wood pulp, % in dry matter
Crude ash, % in dry matter
Sugar, % in dry matter
Starch, % in dry matter
Enzyme digest.OM, %, (cattle)
NDF, % in dry matter, total
iNDF, % in dry mat.

29. Statistics and reporting
Breeder, adviser and farmer: The size of the yield
Very important is also the quality of the yield

30. Statistics and reporting
Quality of the yield
Sugar, starch, digestible parts etc.
Value of the crop
How much milk a kilogram of maize will produce

31. Statistics and reporting
Yield and quality parameters are transformed into yield of feeding units per hectare and net energy value for a high yielding milk cow
SAS Proc mixed
F-test and an LSD value

33. Thank You