Forage and feed analysis Methods available and differences Han van de Goor, NorFor Workshop, November 7/8, 2018
Forage analysis Topics: o Eurofins Agro o Laboratory Wageningen o Forage analysis o Samplinq network
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
Eurofins Agro Sampling Analysis Recommendation
Value of roughage 8 ton DM/ha 50 ha 400 ton DM/year 0,15 /kg DM 60.000,-
Forage analysis How to recognize a good silage?
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
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
Analyses Sample: Chemical analysis methods: o Starch: polarimetric / enzymatic o Protein: 5 (!) different o Digestibility: enzymatic / rumen fluid
Good sample-taking
Laboratory
A sample arrives
With barcode on plate
Drying
Grinding
NIRS vial with ground sample
Tray with NIRS vials
NIRS scanning
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)
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
NIRS Calibrations Global calibration Traditional : calibration lines Spectrum x regression model = result Independent on sample composition Sample X Reference
Nearest neighbor method Local calibration Product database = NIR-spectra + Wet-chemical reference data Regression protocol Parameter specific Sample X
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
Analysis report
Analysis report
Rumen characteristics
Ration check Analysis of the diet in front of the cows: Check: Fed vs calculated diet The mixing process Selecting behavior An unknown diet
Need to combine Eurofins Agro data + Know-how of Advisors = Good rations!
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
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
Customers Samplinq, setup NIR database Reports Archive Web client data Q LIMS Eurofins Agro Samplinq partner
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.
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
Thank you Questions?