Cover crops are increasingly used for biogas production, a renewable energy source, without competing for food production. The behavior of the resulting digestates after soil application is poorly understood, which prevents their efficient recycling in agriculture and the environmental assessment of their application. The objective of this study was to quantify the nitrogen availability and potential carbon storage of cover crop-issued digestates after soil application. A total of 10 raw digestates, 2 liquid phases, and 3 solid phases after phase separation were sampled. Main cover crops used in the sampled biogas plants were winter barley, rye, and maize. Classical physicochemical analyses and laboratory incubations to study their C and N mineralization were conducted. Despite a moderate C mineralization of raw and liquid digestates after 91 days, their initial limited carbon content induced, in the end, a low contribution to soil organic carbon (13 and 11 kg remaining C Mg −1 FM, respectively), similar to a pig slurry and much lower than a bovine manure. With a higher initial carbon content and lower C mineralization, the contribution of solid digestates to carbon storage could be higher if applied at a sufficient rate. Organic N mineralization of raw and liquid digestates was moderate, but their N availability was high (3 and 4 kg available N Mg −1 FM, respectively), thanks to their mineral nitrogen contents, similar again to a pig slurry. In contrast, that of solid digestate was almost null with a very low mineral N content and no organic N mineralization. Finally, all the digestates also brought significant amounts of P and K.
Combined with multivariate calibration methods, near-infrared (NIR) spectroscopy is a non-destructive, rapid, precise and inexpensive analytical method to predict chemical contents of organic products. Nevertheless, one practical limitation of this approach is that performance of the calibration model may decrease when the data are acquired with different spectrometers. To overcome this limitation, standardization methods exist, such as the piecewise direct standardization (PDS) algorithm.
The dataset presented in this article consists of 332 manure samples from poultry and cattle, sampled from farms located in major regions of livestock production in mainland France and Reunion Island. The samples were analysed for seven chemical properties following conventional laboratory methods. NIR spectra were acquired with three spectrometers from fresh homogenized and dried ground samples and then standardized using the PDS algorithm. This important dataset can be used to train and test chemometric models and is of particular interest to NIR spectroscopists and agronomists who assess the agronomic value of animal waste.
Determining the chemical composition of animal manure rapidly is essential to manage fertilisation and decrease environmental pollution. Near infrared (NIR) spectroscopy is a non-destructive, inexpensive and rapid method to determine several components of manure simultaneously. This study investigated the ability of NIR spectroscopy to analyse the dry matter, total and ammonium nitrogen, phosphorus, calcium, potassium and magnesium contents in a database of heterogeneous cattle and poultry solid manures. The accuracy of calibration models obtained from different sample preparation methods (dried ground vs. fresh homogenized) and multivariate regression methods (partial least squares (PLS) vs. local regression) were compared. The results showed that using local regression with NIR spectra of fresh homogenized manure could predict dry matter (R2=0.99, RMSEV = 1.64%, RPD = 13.31), total (R2=0.98, RMSEV = 0.16%, RPD = 7.11) and ammonium nitrogen (R2=0.97, RMSEV = 0.042%, RPD = 5.57) and phosphorus (R2=0.95, RMSEV = 0.10%, RPD = 5.56) contents accurately.
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