# Application of Near-Infrared Spectroscopy for Monitoring and/or Control of Composting Processes
## 5 Use of NIR Spectroscopy to Monitor and/or Control the Composing Process
Due to significant spectra noise for the development of the efficient PLS model, the effect of the different techniques for preprocessing spectrum information were evaluated, and it was noticed that to achieve the appropriate prediction accuracy, the NIRS technique must be matched to every component using specific spectral preprocessing. The significant effect of the used preprocessing method on the developed calibration model performance is considered one of the most important NIR spectroscopy shortcomings. Chemometric analyses are still quite challenging, demanding a specialized chemometrician and to maintain applicable equations. Furthermore, [PERSON] et al. [100] applied middle- and near-infrared spectroscopy to quantify organic carbon and total nitrogen in different organic samples, including wastes, composts, and mixtures of composts and organic wastes. In total, 121 samples were included in the analysis. Their results showed that attenuated total reflectance (PLS-ATR-MIR) models ensure a higher prediction accuracy for both analyzed variables than diffuse reflectance (PLS-DR-NIR) models. Similarly, [PERSON] et al. [101] coupled middle- and near-infrared spectroscopy and partial least squares regression to determinate the total phenolic compound content in compost samples. As spectroscopy pretreatment, the multiplicative scatter correction, standard normal variate, and first derivative were used, and the number of latent variables was adjusted using leave-one-out cross-validation. Their results showed that the diffuse reflectance (PLS-DR-NIR) model was more efficient than the attenuated total reflectance (PLS-ATR-MIR) model for the prediction of the total phenolic compound content in the compost samples. Moreover, [PERSON] et al. [102] showed that PLS regression models based on the first derivatives of the visible near-infrared diffuse reflectance spectra can be used for the assessment of organic matter content during composting with high accuracy (\(R^{2}\) > 0.82). Taking into account that dissolved organic matter not only represents the biochemical change of organic matter during the decomposition process but also assesses the composting humification degree, [PERSON] et al. [103] efficiently estimated the C/N ratio during sludge composting using PLS regression models based on UV and fluorescence data, while [PERSON] et al. [104], [PERSON] et al. [105], and [PERSON] et al. [106] monitored organic matter degradation using UV-Vis and Fourier transform infrared spectroscopy. Similarly, the application of FTIR spectroscopy and differential scanning calorimetry for monitoring biodegradation during olive mill residue composting was also described in the literature [107]. There are also examples of the efficient use of NIR spectroscopy for the characterization of a diverse set of biobased fertilizers [108,109] and for the prediction of agricultural soil fertility properties [109]. [PERSON] et al. [108] analyzed the sample set of eighty-five (85) diverse biobased fertilizers. This set of 85 compost samples included 4 different groups as follows: (i) 50 composts from various Australian composting facilities, (ii) 6 samples of animal manure (from cows and pigs), (iii) 10 fresh plant residues obtained from the main Australian crop species and some alternative species, and (iv) 19 biosolids obtained from waste water plants (urban and rural). Twenty-five properties were analyzed in the listed samples, including essential plant nutrients (N, P, and K), nitrate, free amino acid ammonium nitrogen, other elements and micronutrients (S, Al, As, Ca, Cu, Na, Fe, Mg, Mo, Ni, Mn, Zn, Cr, Co, Cd, Pb, and Se), pH, and electrical conductivity. Their results showed that the wavelength selection method ensured accurate predictions for 21 of the 25 analyzed properties; therefore, they suggested that NIR spectroscopy could replace traditional chemical analysis methods for the analysis of biobased fertilizers composition. Moreover, [PERSON] et al. [109] analyzed 104 organic compost fertilizers from 13 regions in Jiangsu province, China.