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Présentation Handbook Of Reference Methods For Plant Analysis Format Broché
- Livre Économie
Résumé :
This book attempts to consolidate the time-tested methods into one handbook in order to promote standardization of plant analysis procedures. It is useful to plant scientists in production agriculture, forestry, horticulture, environmental sciences, and other related disciplines.
Biographie:
Kalra, Yash
Sommaire:
1. Principles of Plant Analysis 2. Field Sampling Procedures for Conducting a Plant Analysis 3. Preparation of Plant Tissue for Laboratory Analysis 4. Determination of Dry Matter Content of Plant Tissue: Gravimetric Moisture 5. High-Temperature Oxidation: Dry Ashing 6. Nitric-Perchioric Acid Wet Digestion in an Open Vessel 7. Microwave Digestion of Plant Tissue in an Open Vessel 8. Microwave Digestion of Plant Tissue in a Closed Vessel 9. Determination of Total Nitrogen in Plant Tissue 10. Extractable Nitrate in Plant Tissue: Ion-Selective Electrode Method 11. Determination of Ammonium-Nitrogen in Plant Tissue 12. Total Sulfur Determination in Plant Tissue 13. Sulfate-Sulfur Determination in Plant Tissue 14. Determination of Chloride in Plant Tissue 15. Extractable Chloride, Nitrate, Orthophosphate, Potassium, and Sulfate-Sulfur in Plant Tissue: 2% Acetic Acid Extraction 16. Tissue Testing Kits and Procedures for Nutrient Element Assessment in Plant Tissue 17. Chlorophyll Meter Method for Estimating Nitrogen Content in Plant Tissue 18. Analytical Instruments for the Determination of Elements in Plant Tissue 19. Determination of Potassium and Sodium by Flame Emission Spectrophotometry 20. Elemental Determination by Atomic Absorption Spectrophotometry 21. Elemental Determination by Inductively Coupled Plasma Atomic Emission Spectrometry 22. Determination of Boron, Molybdenum, and Selenium in Plant Tissue 23. Determination of Arsenic and Mercury in Plant Tissue 24. Determination of Cadmium, Chromium, Cobalt, Lead, and Nickel in Plant Tissue 25. Quality Control Procedures for Plant Analysis 26. Reference Materials for Data Quality Control 27. Data Processing in Plant Analysis
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