The addition of organic matter in the form of compost improves overall physical, chemical and biological properties of soils but, to be really sustainable, the composting process should be carried out using the by-products available in situ. Two different soils of a Mediterranean olive orchard, one managed traditionally (NAS) and the other amended with compost (AS), were investigated in a two-year experiment. Increases in total organic matter, total nitrogen and pH, were detected in AS if compared to NAS. Significant increases in total and specific microbial counts were observed in AS, with a clear amelioration of microbiological soil quality. The results demonstrated that soil amendment using compost deriving from olive mill by-products can be an important agricultural practice for supporting and stimulating soil microorganisms and, at the same time, for re-using these by-products, so avoiding their negative environmental impact
(1) Background: Extra virgin olive oil production is strictly influenced by the quality of fruits. The optical selection allows for obtaining high quality oils starting from batches with different qualitative characteristics. This study aims to test a CNN algorithm in order to assess its potential for olive classification into several quality classes for industrial purposes, specifically its potential integration and sorting performance evaluation. (2) Methods: The acquired samples were all subjected to visual analysis by a trained operator for the distinction of the products in five classes related to the state of external veraison and the presence of visible defects. The olive samples were placed at a regular distance and in a fixed position on a conveyor belt that moved at a constant speed of 1 cm/s. The images of the olives were taken every 15 s with a compact industrial RGB camera mounted on the main frame in aluminum to allow overlapping of the images, and to avoid loss of information. (3) Results: The modelling approaches used, all based on AI techniques, showed excellent results for both RGB datasets. (4) Conclusions: The presented approach regarding the qualitative discrimination of olive fruits shows its potential for both sorting machine performance evaluation and for future implementation on machines used for industrial sorting processes.
Different mixtures of olive pomace (OP), olive mill wastewater (OMWW) and olive pruning residues (OPR) were aerobically co-composted under natural conditions. Compost temperature showed a sharp increase in the first 40 -60 days, followed by a stabilization at 60°C and a decline after 150 days, whereas compost water content ranged from 50% -55% to 25% -30%. Total and selective microbial counts were followed throughout the experiment by means of innovative (IMT) and conventional (CMT) microbiological techniques. Pseudomonas spp., anaerobic bacteria, actinomycetes, and fungi reached levels of 8, 7, 5 and 6 log CFU g -1 compost, respectively, with a slight depression after 30-80 days. Total and fecal coliforms strongly decreased during the composting process. The use of IMT allowed to detect a higher and more stable growth of microorganisms if compared to CMT. IMT was demonstrated to be an appropriate and reliable method for monitoring the microbial pools during the co-composting process.
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