Reducing the risk of diffuse pollution by improved assessment of the nutrient content in farm manures and biosolids via Near Infrared Reflectance Spectroscopy (NIRS)
Project number: 7290
Lead contractor: ADAS UK Ltd
MDC, EBLEX, BPEX, HGCA, BPC, Severn Trent Water Ltd, Yorkshire Water Ltd, Bruker Optics UK Ltd, Kemira Growhow, Grampian Country Food Group, Agrivert Ltd, Spreadwise Ltd
Start & end date: 01 October 2007 – 31 December 2010
Actulal end date: October 2011
- On an individual farm manure analyses can vary considerably compared with standard figures
- Sampling of stored manures is difficult
- Laboratory analysis can be slow, expensive and may give inconsistent results for solid manures
- There are no simple on farm methods for assessment of solid manure nutrient content
- At present few manure samples are analysed and confidence in the use of manures is low
The aim of the project was to extend substantially the sustainable recycling of organic manures and residues in UK agriculture, through the development of Near Infrared Reflectance Spectroscopy (NIRS) as a robust and reliable technology for multi-nutrient manure analysis.
The project developed on-farm rapid analysis technology to improve users confidence and understanding of organic manure nutrient composition, and this will potentially result in greater nutrient recovery and recognition of manure nutrient value, so improving the financial viability and environmental performance of the industry.
Within this research, NIRS has been successfully developed for estimation of the nutrient content of livestock manures and biosolids via multiple, rapid, scanning of fresh samples. The initial focus of the research was on the development of robust calibration models for estimation of dry matter, total N, NH4-N, SO3, P2O5, K2O, MgO and pH, covering a range of manure types and treated biosolids. From the statistics associated with the validation procedure, performance of the calibrations for conventional analysis of manure and biosolids samples was as follows: excellent – DM, total N; successful – NH4-N, P2O5; moderately successful – SO3, K2O; moderately useful – MgO. Performance for pH was unsatisfactory, which was not a surprise given the limited range in pH (almost all between pH 6.5 and 9.0), even within the very large range of samples scanned and analysed.
Manure and biosolids samples from the NIR spectral database were also selected for N mineralisation and N recovery studies in order to develop a calibration model for the estimation of N release from the organic component of manure N. In this case, data for the calibration model were derived from a large experiment with ryegrass grown in large pots (10 litre), tracking the release of N from manures applied to 3 different soil types (clay loam, sandy loam, loamy sand) at two sites. Regressions were run with the calibration models and grass N uptake data expressed in several ways:
Kg manure N per hectare;
N uptake as percentage of manure N applied;
N uptake as percentage of manure organic N applied;
g N per tonne applied;
g N per tonne of manure applied per day;
g N uptake per 100 day degrees (thermal time).
Correlations with these derived variables were good, and best with the data expressed as g N/tonne/day, thus indicating a good estimate of manure N uptake over the season was possible via the NIRS scanning procedure. However, detailed analysis of the experimental N uptake results also showed a good correlation between manure N recovery and the mineral N content of the manures (both as NH4-N and NH4-N as % of total N), indicating that N uptake was dominated by mineral N content. The improvement in the calibration of the NIRS model for predicting N recovery, compared to proportion of available N alone as a predictor, indicates that the NIRS model is able to account for the mineral N component and mineralisation of organic N in estimating manure N release. Further development of this NIRS calibration model is necessary in order to separate out the effect of the mineral N from the organic N content of the manure and to develop this predictive capacity for use by farmers.
In the final year of the project, the developed NIR calibration models were used to study nutrient content of intensively sampled manure storage and field spread manures. The results of these variability studies were used to evaluate a range of sampling strategies, the conclusions supporting current advice for a minimum of ten samples from well constructed solid manure storage. Where visual examination suggest a more variable and uneven (e.g. shape, size and age) store, however, more intensive sampling is likely to be necessary. The results also confirmed the benefits of a reliable analytical service for improved utilisation of manure nutrients.
Highlights of the research, presented throughout the project within reports, press articles, conference papers and farming events (e.g. Grassland-MUCK2008 and 2011) have attracted significant industry interest. Key information and advice have been compiled within promotional material (posters, technical leaflets) used at events and in farmer leaflets (AHDB and Eurofins) produced in support of the recent launch of a NIRS-based commercial service for manure analysis. This service is to be provided initially by Eurofins Laboratories, under the terms of a two-year licence agreed by the consortium. A preliminary, “commercial launch of this service was undertaken by Eurofins at the Grassland-MUCK Event at NAC, Stoneleigh, in May, 2011. This involved running the Bruker Matrix-I instrument, on the AHDB Stand, with attendant, pre-event publicity and an opportunity for farmers to see the machine scanning a range of samples and generating reports; also to have some of their own manures analysed without charge, with results delivered after the event.