The phenolic profiles of six varieties of avocado (Persea americana) grown in Sicily were investigated. The ultra-high-performance liquid chromatography-heated electrospray-mass spectrometry method was developed to determine qualitative and quantitative changes in fruits at two different ripening stage. Nineteen individual phenolic compounds were detected in avocado pulp extracts. Gallic acid, sinapinic acid, vanillin, p-coumaric acid, and gentisic acid were present only in ripe fruits. On the contrary, epicatechin decreased with fruit ripening, whereas protocatechuic acid, 4-hydroxybenzoic acid, chlorogenic acid, and benzoic acid were relatively stable or exhibited erratic changes with fruit ripening. The different avocado cultivars exhibited different phenolic profiles and total quantities and it was found that, among the tested cultivars, “Orotawa” avocados may provide the highest nutritional and health contribution to human diet. The qualitative and quantitative differences among cultivars and maturation stages by multivariate analysis allowed for the individuation of a set of phenolic compounds that have a great potential in the discrimination and identification of different genetic groups.

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies.

Soil and water pollution caused by excessive use of fertilizers and resource scarcity are critical issues in modern horticulture. Although laboratory tests are reliable, they take time and use chemical reagents that must be disposed of and complex protocols. Monitoring plant nutrient status through technologies that allow continuous and rapid assessment is crucial for precise resource management. Several proximal and remote sensors that use different physico-chemical principles to monitor plant nutrient status are available nowadays. However, these technologies still have important operative and structural limitations that must be overcome. The aim of this review is to summarize the current status and latest developments in proximal and remote sensors capable of monitoring plant and soil nutrients, focusing on sensor types, principles, applications, and their strengths and weaknesses. Electrochemical proximal sensors allow continuous monitoring of nutrients in the plant sap or in the soil solution but work on a single spot basis. Instruments based on optical sensors allow immediate measurements and quick analysis, but do not work on a continuous basis. On the other hand, remote sensors, such as drone-mounted cameras and satellite systems, are based on large-area imaging and can be used to estimate crop nutrient status by processing images at different wavelengths. Finally, combining proximal and remote techniques may be needed to achieve very accurate monitoring of plant and nutrient status.

Two different olive cultivars grown under a high-density hedgerow system were studied to compare their fruiting and branch architecture features and to determine the possibility to use ‘Calatina’ olive trees for intensive plantings, as a local alternative to the international reference ‘Arbequina’. Weights of two-year-old branches, fruits and leaves were recorded to estimate the growth partitioning. Growth and architectural parameters, such as shoot length, vector and diameter, branching angle, branch total length, height, width, area, and branching frequency, were determined by digital image analysis. Digital images of the fruits were also used to estimate fruit maturation by peel color analysis. Whole branch and fruit crop weights were similar in the ‘Arbequina’ and ‘Calatina’, while the latter had a greater fruit/leaf ratio, showing a higher production efficiency than ‘Arbequina’. Fruits were fewer but bigger in ‘Calatina’ than in ‘Arbequina’, suggesting an advantage for both trunk-shaking and straddle machine harvesting in the Sicilian cultivar. Leaf/wood ratio, branching frequency and branching angle were similar in the two cultivars. ‘Calatina’ shoots exhibited a greater bending degree than those of ‘Arbequina’ and this trait particularly favors straddle harvesting. In addition to many similarities between the two cultivars, the present study indicates that ‘Calatina’ is more efficient in terms of yield and harvesting than ‘Arbequina’. This qualifies ‘Calatina’ as a superior, yield-efficient olive cultivar suitable for intensive hedgerow plantings to be harvested with straddle or side-by-side trunk shaker machines.

Exploiting biodiversity must be considered today an effective strategy to improve the sustainability of olive production systems. The evaluation of local cultivars, based on their vegetative and fruiting traits, along with an analysis of product quality, may contribute significantly to the development and diffusion of new olive-growing systems. The aim of this study was to evaluate growth, productivity, and olive oil quality of three Sicilian cultivars with different vigor/growth habit grown in four different combinations of training form and planting density. ‘Abunara’, ‘Calatina’, and ‘Nocellara del Belice’ olive trees were planted in four different intensive planting systems: 2 × 5 m trained to central leader (CLx2), 3 × 5 m trained to free palmette (FPx3), 4 × 5 m trained to small globe vase (GVx4), and 5 × 5 m trained to poly-conic vase (PVx5) and evaluated for seven years. Planting systems with low-density showed faster growth (trunk cross section area and canopy volume) than high-density systems. High-density systems had higher yield per hectare but lower yield per tree than low-density systems. ‘Calatina’ was the least vigorous but most productive cultivar. ‘Abunara’ and ‘Nocellara’ were relatively vigorous and suffered the tight spacings of high-density systems. Yield efficiency was generally high in ‘Calatina’, and it showed an increase with time in ‘Abunara’ and ‘Nocellara’ grown under the GVx4 and PVx5 systems. Fruit yield per hectare was highest in ‘Calatina’ grown under high-density systems. Oil yield was lower in ‘Nocellara’ than in ‘Abunara’ and ‘Calatina’. In terms of oil quality, ‘Calatina’ and ‘Abunara’ produced oils with higher oleic acid content than ‘Nocellara’. Generally, ‘Calatina’ has production characteristics of considerable interest, which, combined with low canopy volume and vigor, make it suitable for intensive pedestrian olive orchards with high levels of harvest and pruning mechanization and using different strategies and machines. Overall, for their management flexibility, these planting systems can contribute to improve sustainability of the olive industry even in sloping, dry areas of the Mediterranean.