## 3 Results and Discussion
### Total Carbohydrates and Polyhydroxyalkanonates (PHAs)  
Most studies using Raman as a monitoring tool for PHAs production have focused on intracellular polymer content, composition and degree of crystallinity [43]. The most prominent contributions of PHB to a bacterial Raman spectrum were associated with a peak at around 1734 cm\({}^{-1}\)[45]. Furthermore, studies using commercial copolymers of poly(3-hydroxybutyrate-_co_-3-hydroxyvalerate) (PHBV) identified specific Raman bands associated with 3-hydroxyvalerate (3 HV) [43] and quantified the molar fraction of 3 HV in polyester solutions and molten polyester films based on specific Raman peaks [44]. Subsequently, Raman spectroscopy has been suggested as a potentially fast and efficient tool for the process control of PHB bioproduction through qualitative and quantitative in situ monitoring of intracellular PHB content in biomass, specifically in _Cupriavidus__incator_ H16 cultures [29]. In the context of wastewater treatment in a photo-BNR reactor, the online monitoring of intracellular polymers such as PHAs and glycogen (accounted for as part of the total carbohydrates), which are involved in the P removal process, is relevant to assess whether nutrient removal is limited by the low concentration of biopolymers and to optimize this process. The Raman region located at 1200-800 cm\({}^{-1}\) has been reported to be mainly dominated by polysaccharide peaks, and the spectral region between 1288 and 987 cm\({}^{-1}\) was previously used to develop a Raman-based PLS model for carbohydrates in powdered milk samples [47]. Accordingly, the optimization of the PLS models for total carbohydrates in the present study led to the selection of spectral regions within the 1200-800 cm\({}^{-1}\) range (Table 1), which include some of the peaks characteristic of glycogen vibrations (484-478, 860-840, 944-937, 1087-1048, 1131, 1383-1333, and 1460 cm\({}^{-1}\)) [24]. The glycogen skeletal deformation band (484-478 cm\({}^{-1}\)) was not accounted for in the carbohydrates model, probably due to overlapping peak positions between PHAs and glycogen in this region [41]. In fact, the optimized PLS model for PHAs included the 484-478 cm\({}^{-1}\) band within the selected spectral regions, i.e., 491.6-464.0 cm\({}^{-1}\) + 850.4-798.9 cm\({}^{-1}\) + 1001.3-898.2 cm\({}^{-1}\) (Table 1). The selection of these spectral regions is in accordance with two of the most prominent bands reported in the Raman spectra of PHB and PHBV: 433 and 860-840 cm\({}^{-1}\), assigned to \(\delta\)(C-C) skeletal deformations and v(C-C) skeletal stretches, respectively [24]. Despite the excellent calibration statistical results obtained in both models (R\({}^{2}_{\text{Cal}}\) and RMSEC of 99.4% and 0.15 mmol C L\({}^{-1}\) for total carbohydrates, and 99.9% and 0.12 mmol C L\({}^{-1}\) for PHAs, respectively), good cross-validation performance was only reached in the PHAs model (R\({}^{2}_{\text{CV}}\) = 95.9%, RPD\({}_{\text{CV}}\) = 5.0; Figure 3e), while only satisfactory results were obtained in the model developed for total carbohydrates (R\({}^{2}_{\text{CV}}\) = 88.2%, RPD\({}_{\text{CV}}\) = 2.9; Figure 3a). Overall, the predicted values follow the measured values along the SBR treatment cycles, as represented in Figure 3a,e for total carbohydrates and PHAs, respectively. Nevertheless, according to the respective RPD values, the PLS model constructed for PHAs prediction could be used as a good screening method within the 0.7-12.8 mmol C L\({}^{-1}\) concentration range, while the one for total carbohydrates can only be considered as a rough screening method for concentration values within 2.8-8.3 mmol C L\({}^{-1}\)[38]. In light of the labor-intensive, complex and time-consuming protocols involved in the analytical methods used to measure PHAs and total carbohydrates (involving biomass digestions, GC and HPLC analysis, respectively), the application of Raman spectroscopy as a fast, direct and not destructive monitoring tool would enable timely decisions regarding process control and optimization.