The development of reliable methods for the estimation of crown architecture parameters is a key issue for the quantitative evaluation of tree crop adaptation to environment conditions and/or growing system. In the present work, we developed and tested the performance of a method based on low-cost unmanned aerial vehicle (UAV) imagery for the estimation of olive crown parameters (tree height and crown diameter) in the framework of olive tree breeding programs, both on discontinuous and continuous canopy cropping systems. The workflow involved the image acquisition with consumer-grade cameras on board a UAV and orthomosaic and digital surface model generation using structure-from-motion image reconstruction (without ground point information). Finally, geographical information system analyses and object-based classification were used for the calculation of tree parameters. Results showed a high agreement between remote sensing estimation and field measurements of crown parameters. This was observed both at the individual tree/hedgerow level (relative RMSE from 6% to 20%, depending on the particular case) and also when average values for different genotypes were considered for phenotyping purposes (relative RMSE from 3% to 16%), pointing out the interest and applicability of these data and techniques in the selection scheme of breeding programs.

Phenolic compounds are responsible of the nutritional and sensory quality of extra-virgin olive oil (EVOO). The composition of phenolic compounds in EVOO is related to the initial content of phenolic compounds in the olive-fruit tissues and the activity of enzymes acting on these compounds during the industrial process to produce the oil. In this work, the phenolic composition was studied in six major cultivars grown in the same orchard under the same agronomical and environmental conditions in an effort to test the effects of cultivars on phenolic composition in fruits and oils as well as on transfer between matrices. The phenolic fractions were identified and quantified using high-performance liquid chromatography-diode array detector-time-of-flight-mass spectrometry. A total of 33 phenolic compounds were determined in the fruit samples and a total of 20 compounds in their corresponding oils. Qualitative and quantitative differences in phenolic composition were found among cultivars in both matrices, as well as regarding the transfer rate of phenolic compounds from fruits to oil. The results also varied according to the different phenolic groups evaluated, with secoiridoids registering the highest transfer rates from fruits to oils. Moreover, wide-ranging differences have been noticed between cultivars for the transfer rates of secoiridoids (4.36%–65.63% of total transfer rate) and for flavonoids (0.18%–0.67% of total transfer rate). ‘Picual’ was the cultivar that transferred secoiridoids to oil at the highest rate, whereas ‘Changlot Real’ was the cultivar that transferred flavonoids at the highest rates instead. Principal-component analysis confirmed a strong genetic effect on the basis of the phenolic profile both in the olive fruits and in the oils.

A first attempt to determine the effect of vigor and parents on the length of the juvenile period of olive seedlings is here reported. Vigor seems to have a significant influence on the percentage of flowering seedlings, especially in the first 2 years of bearing. The different parents used have produced differences in the juvenile period of their descendants. A correspondence between the length of the unproductive period of the parents and the length of the juvenile period that they transmit to their descendants has been observed. The seedling forcing growth protocol described here has been able to produce flowering seedlings 28 months after germination, with >93% of seedlings flowering 65 months after germination.

Near-infrared transflectance spectroscopy was used to detect adulteration of apple juice samples. A total of 150 apple samples from 19 different varieties were collected in two consecutive years from orchards throughout the main cultivation areas in Ireland. Adulterant samples at 10, 20, 30, and 40% w/w were prepared using two types of adulterants: a high fructose corn syrup (HFCS) with 45% fructose and 55% glucose, and a sugars solution (SUGARS) made with 60% fructose, 25% glucose, and 15% sucrose (the average content of these sugars in apple juice). The results show that NIR analysis can be used to predict adulteration of apple juices by added sugars with a detection limit of 9.5% for samples adulterated with HFCS, 18.5% for samples adulterated with SUGARS, and 17% for the combined (HFCS + SUGARS) adulterants. Discriminant partial least squares (PLS) regression can detect authentic apple juice with an accuracy of 86–100% and adulterant apple juice with an accuracy of 91–100% depending on the adulterant type and level of adulteration considered. This method could provide a rapid screening technique for the detection of this type of apple juice adulteration, although further work is required to demonstrate model robustness.