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Composting is an interesting option to recycle big quantities of organic waste because it helps to mitigate different environmental problems. Complementary characteristics of rice straw (RS) and sewage sludge (SS) create a suitable mixture to be used in a composting process. This work studies industrial-scale RS and SS composting to assess both its viability and optimization. Windrow composting was conducted during two seasons. The complete characterisation (moisture, pH, electrical conductivity, total, oxidisable and water-soluble organic carbon, humic substances, organic and mineral nitrogen, macronutrients, micronutrients, heavy metals) of starting materials, samples taken periodically and final composts were carried out. During the first season, an RS:SS ratio of 1:8 (w:w fresh weight) was used, which led to a process with adequate temperatures for biodegradation, but not for ensuring materials’ sanitation. During the second season, the RS:SS ratio was increased (1:6) to enhance the energy process and, thus, temperatures. Although this increase took place, degradation slowed down as oxidisable organic carbon and water-soluble organic carbon indicated. During both seasons, final composts presented adequate pH, high N-richness, and interesting macro- and micronutrient values. Notwithstanding, they also presented certain salinity and high ammonium contents, which must be considered for their field application. The obtained composts have interesting agronomic characteristics, which suggest their potential as an alternative to conventional fertilisers.

Recycled sources of phosphorus (P) and nitrogen (N), such as struvite extracted from wastewater, have the potential to substitute conventional manufactured fertilizers and mitigate environmental problems such as water eutrophication or the depletion of non-renewable resources. This study aimed to evaluate the potential of struvite as a nitrogenous and phosphate fertilizer in the Spanish Mediterranean region. Two experiments were carried out using struvite recovered from sewage sludge and different representative soils from the area. Since knowing the rates at which their nutrients are released is key for efficient use, experiment I determined the struvite N-releasing rate for 16 weeks. Experiment II studied the effect of different struvite doses (50, 100, 200 kg P2O5 ha−1) on crop growth compared to superphosphate + ammonium nitrate. The results indicated N-releasing rates that fall in line with a slow-release fertilizer. More than 20% of applied struvite-N was unavailable for plants or in the longer term, which suggests struvite fractionation as the most efficient application method. Struvite showed similar fertilization capacity, which was even better at some points, than conventional mineral fertilization, plus adequate plant growth and good nutrient concentration at the 50 kg P2O5 ha−1 dose. Based on this study, struvite can be considered an interesting and effective option for sustainable fertilization in the Mediterranean region.

Visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI) was used for rapid and non-destructive determination of macro- and micronutrient contents in persimmon leaves. Hyperspectral images of 687 leaves were acquired in the 500–980 nm range over 6 months, covering a complete vegetative cycle. The average reflectance spectrum of each leaf was extracted, and foliar ionomic analysis was used as a reference method to determine the actual concentration of the nutrients in the leaves. Analyses were performed via emission spectrometry (ICP-OES) for macro- and micronutrients after microwave digestion and using the Kjeldahl method to quantify nitrogen. Partial least square regression (PLS-R) was used to predict the nutrient concentration based on spectral data from the leaf using actual values of each element as predictor variables. Several methods were used to pre-process the spectra, including Savitzky–Golay (SG) smoothing, standard normal variate (SNV) and first (1D) and second derivatives (2D). Seventy-five percent of the samples were used to calibrate and validate the model by cross-validation, whereas the remaining twenty-five % were used as an independent test set. The best performance of the models for the test set achieved an R2 = 0.80 for nitrogen. Results were also satisfactory for phosphorous, calcium, magnesium and boron, with determination coefficient R2 values of 0.63, 0.66, 0.58 and 0.69, respectively. For the other nutrients, lower prediction rates were attained (R2 = 0.48 for potassium, R2 = 0.38 for iron, R2 = 0.24 for copper, R2 = 0.23 for zinc and R2 = 0.22 for manganese). The variable importance in projection (VIP) was used to extract the most influential bands for the best-predicted nutrients, which were N, K and B.

The aim of this study was to establish DRIS (Diagnosis and Recommendation Integrated System) norms and Nutritional Optimal Ranges (NOR) for ‘Rojo Brillante’ Protected Designation of Origin (PDO) ‘Ribera del Xúquer’. The database contained 800 leaf samples collected in different crop phenological stages [after flowering (AF), fruit enlargement (FE), fruit colouring (FC), and harvesting HV)]. DRIS norms (78) were established for macronutrients: N, P, K, Ca, Mg and S; micronutrients B, Cu, Fe, Mn, and Zn and salinity elements: Na and Cl. The Nutrient Balance Index (NBI; the absolute value of the sum of the DRIS indices) was used to determine the optimal sampling period. Fruit enlargement was the period during which persimmon trees were more nutritionally balanced regardless of sprout origin (vegetative or floral) and irrigation type (drip or flood) in orchards