The Technology
Soil analysis is important for predicting seasonal crop nutrient availability. In season leaf analysis identifies efficacy and sufficiency of nutrient uptake at the point of sampling, and grain analysis indicates the success of seasonal crop nutrition strategies. The aim is to prevent suboptimal nutrition from limiting crop performance and yield. However, monitoring of crop nutrition by plant analysis is variable and requires reference to nutrient concentration standards for a series of prescriptive growth stages. Prescriptive sampling methodologies are required together with a detailed knowledge of local weather conditions. Tissue analysis is offered by laboratory services and assesses macronutrients N, K, P: secondary nutrients Mg, S and Ca; and micronutrients B, Mn, Fe, Ni, Cu, Zn, Mo. Large regional soil-type and crop cultivar-specific nutrient assimilation datasets are critical for predictive planning.
How it works
Once the nutrient status of a crop has been diagnosed from lab analysis of plant tissue samples, knowledge can be used to correct existing problems if timely enough, or to help predict and prevent future soil deficiencies. If corrective action is taken, tissue and grain analysis in combination with final yield data will reveal how successful the strategy was. Where big data has been accumulated, algorithms instructing machine learning can help drive tailored fertiliser choice and application recommendations.
Farmer / Agronomist Benefits
Plant tissue analysis combined with soil data provides the critical information required to ensure all crop nutrition decisions are accurate, efficient, cost-effective and responsible. Best used as a diagnostic tool for future correction of nutrient problems using the relevant plant tissue permits corrective action. When deficiency symptoms are visible yield development is already impaired.
Key Researchers and Stakeholders
NRM Laboratories
Yara
Lancrop
Agrigem
Video Link
Yara – How to take a leaf tissue sample for nutrient analysis: https://youtu.be/j6eXe-gaJkE