Rapid analysis of manure and organic recyclables for sustainable agriculture via Near Infrared Reflectance Spectroscopy (NIRS)


Cereals & Oilseeds
Project code:
01 October 2007 - 31 March 2010
AHDB Cereals & Oilseeds.
AHDB sector cost:
£65,000 from HGCA.
Project leader:
Ken Smith ADAS Wolverhampton, Woodthorpe, Wolverhampton WV6 8TQ



About this project


This project set out to promote the sustainable recycling of organic manures in UK agriculture, through the development of Near Infrared Reflectance Spectroscopy (NIRS) as a robust and reliable technology for multi-nutrient manure analysis.

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. 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 to develop a calibration model for the estimation of N release from the organic component of manure N. Data for the calibration model were derived from a large experiment with ryegrass grown in large pots, tracking the release of N from manures applied to 3 different soil types (clay loam, sandy loam, loamy sand) at two sites for 3 years (180 manures in total). Correlations with derived variables were good, and best with the data expressed as g N/tonne/day, indicating a good estimate of manure N uptake over the season was possible via the NIRS scanning procedure. 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.

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 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. They also confirmed the benefits of a reliable analytical service for improved utilisation of manure nutrients.

The potential for NIRS-based characterisation of soils for nutrient content and soil microbial activity/community, was also assessed. The soil characterisation work showed potential for application with certain nutrients; organic matter, total C, pH, total P, organic P, total N; it appeared likely that the models could be improved by increasing the calibration sample base and by restricting calibration to a single soil type.