Forage and feed analysis. Methods available and differences

Transcription

1 Forage and feed analysis Methods available and differences Han van de Goor, NorFor Workshop, November 7/8, 2018

2 Forage analysis Topics: o Eurofins Agro o Laboratory Wageningen o Forage analysis o Samplinq network

3 Eurofins Agro Wageningen o Agricultural laboratory o Started in 1928 o 700,000 samples/year o 200,000 forage samples/year o Expertise: agricultural analyses o Highly automated o New developments: o o Analysis techniques Measured parameters (e.g. digestibility) o More milk from roughage

4 Eurofins Agro Sampling Analysis Recommendation

5 Value of roughage 8 ton DM/ha 50 ha 400 ton DM/year 0,15 /kg DM ,-

6 Forage analysis How to recognize a good silage?

7 Analyses Forage analyses is a must for: Energy content Protein content Minerals and trace-elements To achieve: Good Rations (50-80% forage!) Optimal milk production But also Judgement of silo management

8 Analyses o Results depend on: o o o o o o o o Sample Chemical analysis methods Equipment Procedures Standardization, duplicates People - automation Interpretations (NIRS) Internal checks o More / less information o Feed valuations

9 Analyses Sample: Chemical analysis methods: o Starch: polarimetric / enzymatic o Protein: 5 (!) different o Digestibility: enzymatic / rumen fluid

10 Good sample-taking

11 Laboratory

12 A sample arrives

13 With barcode on plate

14 Drying

15 Grinding

16 NIRS vial with ground sample

17 Tray with NIRS vials

18 NIRS scanning

19 Analysis methods o Wet-chemical: Slow Cost o Dried NIRS: Data quality Homogeneous sample, repeatable results Storage of samples Optimization (fertilization, milk production) o Fresh NIRS: Fast, cheap DM (and protein)

20 Calibrations Basis for good calibrations: Only duplicate results Independent batches! From one laboratory Check every day (validation also duplicate results) Good long-term stability Large number and variety of samples

21 NIRS Calibrations Global calibration Traditional : calibration lines Spectrum x regression model = result Independent on sample composition Sample X Reference

22 Nearest neighbor method Local calibration Product database = NIR-spectra + Wet-chemical reference data Regression protocol Parameter specific Sample X

23 Nearest neighbors o Advantages: o o o o Continuity No risk of trend breaks Maintenance Actuality Reference sample directly active More robust o Drawbacks: o o No physical models (= calibration lines) Large number of samples required

24 Analysis report

25 Analysis report

26

27 Rumen characteristics

28 Ration check Analysis of the diet in front of the cows: Check: Fed vs calculated diet The mixing process Selecting behavior An unknown diet

29 Need to combine Eurofins Agro data + Know-how of Advisors = Good rations!

30 Samplinq Sample analysis at other locations Analysis results at Eurofins Agro quality level Analysis by Eurofins Agro and/or partners Start with crops, now also soil, manure to follow Currently: (a.o.) Austria, Belarus, Belgium, Brazil, China, Colombia, Finland, France, Germany, Hungary, Lithuania, Netherlands, New Zealand, Norway, Poland, Portugal, Russia, South Africa, Ukraine, United Kingdom Expanding

31 Samplinq, procedure o Samplinq partner: o Sample registration o Sample drying (overnight) o Sample grinding o NIRS scanning o (Determine ash content) o Send scanned spectrum, sample data o Eurofins Agro: o Check info (complete?) o Process sample data, product specific: NIR-data, feeding value o Send results o Samplinq partner: o Print customer report Sample on a Quant

32 Customers Samplinq, setup NIR database Reports Archive Web client data Q LIMS Eurofins Agro Samplinq partner

33 Samplinq analysis packages Standard package: nutritional value Dry Matter Crude ash (+/-) Crude protein Crude fibre Crude fat Sugar Starch Ammonia fraction NDF Digestible Organic Matter Feeding values Fast package: For raw materials No drying required Profi package: digestibility ADF ADL NDF-digestibility (van Soest) Bypass starch ph (fresh) Lactic acid Acetic acid Recommendations: Rumen character Conservation index Stability bypass starch N-Index Etc.

34 Samplinq advantages Very reliable analysis results Same results in different countries Validations, calibrations (dried, ground) More parameters measured (i.s.o. calculated) Recommendations possible Local investment relatively low Different languages Many feed valuation systems Input directly into NorFor FAS rationing / advising software

35 Thank you Questions?