Non-destructive optical techniques as a tool to support high quality production reducing agronomic inputs: case studies on tomatoes and rocket salads

The modern demand for food quality has driven the food industry to develop rapid, reliable, and cost-effective methods for evaluating food products. Traditional destructive analysis methods are time-consuming, expensive, and labor-intensive, leading to a shift towards non-destructive methods. These non-destructive methods are utilized for sorting and classifying fruits and vegetables based on production systems, variety, maturity stage, storage history, and origin, as well as for predicting key internal constituents. This dissertation investigates the application of advanced non-destructive optical techniques, specifically Hyperspectral Imaging (HSI) and Fourier Transform Near-Infrared (FT-NIR) Spectroscopy, to enhance the quality assessment and sustainability of agricultural produce, focusing on tomatoes and rocket salads. Optical non-destructive methods, including Near-Infrared (NIR) spectroscopy and HSI, offer a sustainable and efficient alternative to traditional techniques. These methods allow comprehensive quality evaluation without damaging produce. NIR spectroscopy measures internal attributes like sugar content, acidity, and firmness through light absorption characteristics, while HSI detects subtle quality variations and internal defects. Practical applications include assessing apples for firmness, evaluating citrus fruits for sugar content, and detecting defects in tomatoes and berries. These technologies can be integrated into existing quality control processes, promoting sustainability and high standards of produce quality. Non-destructive optical techniques also ensure the authenticity of agricultural products, addressing consumer demands for transparency and safety. These methods assess authenticity based on internal quality, cultural practices, and production methods. Certifications like Protected Designation of Origin (PDO) safeguard product authenticity. Optical methods, including NIR Spectroscopy and HSI, classify and authenticate products based on geographical origin, production systems, and harvest times, enhanced by chemometric techniques. In experimental work, non-destructive optical techniques were used to classify sustainably produced tomatoes based on growing practices, water use efficiency (WUE), and partial factor productivity of nutrients (PFP). Using HSI and FT-NIR spectroscopy, the study achieved high classification accuracy, supporting low input growing techniques. Further experiments assessed the potential of these techniques in predicting internal quality constituents of tomatoes grown under different hydroponic conditions. HSI and FT-NIR spectroscopy predicted attributes like total soluble solid content (TSS), pH, total titratable acidity (TA), L-ascorbic acid (AA), and vitamin C (VC). FT-NIR data provided superior accuracy and robustness. Finally, HSI techniques were applied to classify rocket leaves based on growing practices and fertilizer levels in different greenhouse environments. HSI effectively differentiated fertilizer levels and cultivation systems, supporting sustainable agricultural practices. Overall, non-destructive optical techniques like HSI and FT-NIR spectroscopy enhance quality assessment and sustainability in agricultural production, offering efficiency, accuracy, and reduced agronomic inputs, supporting high-quality production in modern agriculture.