Olive cultivation is still concentrated within the Mediterranean basin, although the last thirty years have seen an expansion into geographical areas outside it. Traditional olive groves, with large planting distances and centuries-old trees, still predominate. However, more and more space is being given over to modern plantations, which allow an ever-increasing degree of mechanisation, although some legal restrictions, often related to the monumental nature of the plantations, make the conversion of old plantations into new ones not always easy. The extreme case is super-intensive olive growing, where the very concept of olive growing has been rethought. In this context, harvesting is the most time-consuming and costly of the cultivation operations. Without it, or rather without a high degree of mechanisation, it is still not possible to produce high-quality oils. A leading role is always played by the trunk shakers, who are still the undisputed protagonists in this sector. This review looks at trunk shakers in olive groves, showing the latest models, and their strengths and weaknesses, based on the research carried out in recent decades.

Protected crops are intensive production systems characterized by high vegetation density, high temperatures, and high moisture, making them favorable environments for the development of pests and diseases. Consequently, these systems often require several interventions with agrochemicals to maintain profitable yields and high produce quality. However, the application of plant protection products (PPPs) in such systems is not efficient and poses environmental concerns. This study aims at analysing spray behaviour, particularly in terms of foliar deposition and losses to the ground according to spraying equipment and foliage height, focusing on a specifically designed and developed system for agrochemical application in protected crops, and comparing it with a commonly used spraying system, namely, the cannon sprayer. Such a system consists in a fixed net of tubing and anti-drip nozzles positioned at the top of the greenhouse’s apex, connected to a pneumatic sprayer ‘Special Serre 2000’ outside the greenhouse. Findings revealed a significant effect of the spraying system (Kruskal–Wallis χ² = 12.239, df = 1, and p-value = 0.0004681) on normalized foliar deposition, with higher values obtained using the fixed spraying system. In addition, a simulation of the spatial distribution based on the principle of inverse distance weighting (IDW) was performed for qualitative spray assessment, confirming the heterogeneity of foliar deposition over the greenhouse with both of the used equipment. In addition, losses to the ground were affected by both spraying equipment and captor position.

This research represents an advancement in smartphone-based image acquisition methodology, building upon a previous study to estimate the essential oil content of bergamot fruits in situ using a deep learning approach. To overcome an operational constraint due to a bulky portable dark box to standardise illumination, this study proposes a more versatile solution: a mobile application based on a colour card reference. By replacing physical shielding with digital compensation, the app functions as a local colourimetric sensor, enabling real-time correction of images acquired directly in the orchard, regardless of environmental variables such as direct sunlight or shadows. Workflow relies on an automated calibration procedure. Upon image acquisition, the application utilises ArUco Markers to autonomously detect and extract both the colour card and the fruit surface. The core of the innovation lies in the colour calibration algorithm based on RGB histogram matching logic, which calculates the precise chromatic transformation required to align the field data with the reference card data (acquired under controlled conditions). These calculated parameters are then dynamically mapped onto the fruit’s image. The final output is a normalised high-fidelity image, ready for the calculation of chromatic indices, such as the citrus colour index, or for seamless integration into predictive models. The results show that the application is a valid tool for colour calibration, thanks to the good agreement with the values obtained using the inspection chamber. The latter can therefore be replaced by the app, which allows reliable results to be obtained even when used on its own.