Identification of Olives Using In-Field Hyperspectral Imaging with Lightweight Models

During the growing season, olives progress through nine different phenological stages, starting with bud development and ending with senescence. During their lifespan, olives undergo changes in their external color and chemical properties. To tackle these properties, we used hyperspectral imaging during the growing season of the olives. The objective of this study was to develop a lightweight model capable of identifying olives in the hyperspectral images using their spectral information. To achieve this goal, we utilized the hyperspectral imaging of olives while they were still on the tree and conducted this process throughout the entire growing season directly in the field without artificial light sources. The images were taken on-site every week from 9:00 to 11:00 a.m. UTC to avoid light saturation and glitters. The data were analyzed using training and testing classifiers, including Decision Tree, Logistic Regression, Random Forest, and Support Vector Machine on labeled datasets. The Logistic Regression model showed the best balance between classification success rate, size, and inference time, achieving a 98% F1-score with less than 1 KB in parameters. A reduction in size was achieved by analyzing the wavelengths that were critical in the decision making, reducing the dimensionality of the hypercube. So, with this novel model, olives in a hyperspectral image can be identified during the season, providing data to enhance a farmer's decision-making process through further automatic applications.

Combined Transcriptomic and Metabolomic Approach Revealed a Relationship between Light Control, Photoprotective Pigments, and Lipid Biosynthesis in Olives

Olive possesses excellent nutritional and economic values for its main healthy products. Among them, a high content of antioxidant compounds, balanced during the ripening process, are produced under genetic and environmental control, resulting in high variability among cultivars. The genes involved in these complex pathways are mainly known, but despite many studies which indicated the key role of light quality and quantity for the synthesis of many metabolites in plants, limited information on these topics is available in olive. We carried out a targeted gene expression profiling in three olive cultivars, Cellina di Nardò, Ruveia, and Salella, which were selected for their contrasting oleic acid and phenolic content. The -omics combined approach revealed a direct correlation between a higher expression of the main flavonoid genes and the high content of these metabolites in 'Cellina di Nardò'. Furthermore, it confirmed the key role of FAD2-2 in the linoleic acid biosynthesis. More interestingly, in all the comparisons, a co-regulation of genes involved in photoperception and circadian clock machinery suggests a key role of light in orchestrating the regulation of these pathways in olive. Therefore, the identified genes in our analyses might represent a useful tool to support olive breeding, although further investigations are needed.

The Potential of Apulian Olive Biodiversity: The Case of Oliva Rossa Virgin Olive Oil

In this study, the drupes and virgin olive oils extracted from the Oliva Rossa landrace are characterized. Oliva Rossa is an old landrace part of the autochthonous Apulian olive germplasm for which only few data have been reported till now. During the study, the maturity patterns of the drupes had been followed. Four samplings per year were planned, one every 14 days starting from the middle of October. The pigmentation index, the oil content and the total phenolic content of the drupes were measured. Simultaneously, virgin olive oils were extracted at the lab scale and analyzed for the fatty acid composition, the basic quality parameters and the content of minor compounds. The pigmentation pattern of the drupes was different among the years and, despite this trend, at the third sampling time the stage of maximum oil accumulation was always over. The extracted virgin olive oils had a medium to high level of oleic acid. With colder temperatures, a higher level of monounsaturated fatty acids, oleic/linoleic ratio and antioxidants was observed. The phenolic profile was dominated by 3,4-DPHEA-EDA and p-HPEA-EDA while the volatile profile by (E)-2-hexenal and 3-ethyl-1,5-octadiene.

Combined Metabolome and Transcriptome Profiling Reveal Optimal Harvest Strategy Model Based on Different Production Purposes in Olive

Olive oil has been favored as high-quality edible oil because it contains balanced fatty acids (FAs) and high levels of minor components. The contents of FAs and minor components are variable in olive fruits of different color at harvest time, which render it difficult to determine the optimal harvest strategy for olive oil producing. Here, we combined metabolome, Pacbio Iso-seq, and Illumina RNA-seq transcriptome to investigate the association between metabolites and gene expression of olive fruits at harvest time. A total of 34 FAs, 12 minor components, and 181 other metabolites (including organic acids, polyols, amino acids, and sugars) were identified in this study. Moreover, we proposed optimal olive harvesting strategy models based on different production purposes. In addition, we used the combined Pacbio Iso-seq and Illumina RNA-seq gene expression data to identify genes related to the biosynthetic pathways of hydroxytyrosol and oleuropein. These data lay the foundation for future investigations of olive fruit metabolism and gene expression patterns, and provide a method to obtain olive harvesting strategies for different production purposes.

Tree Planting Density and Canopy Position Affect ‘Cerasuola’ and ‘Koroneiki’ Olive Oil Quality

To maximize orchard production and tree crop efficiency, optimization of both maximum orchard light interception and radiation distribution within the tree canopy are important strategies. To study the influence of planting density and fruit position within the canopy on oil quality from ‘Cerasuola’ and ‘Koroneiki’ olive (Olea europaea L.), fruits were harvested from the upper and lower canopy layers of trees in hedgerow planting systems at two densities: High at 1000 trees ha−1 (HD) and Medium at 500 trees ha−1 (MD). Tree crop efficiency and fruit weight, water and fat content were measured together with olive oil standard quality parameters, phenolic and volatile composition. Fruits in the upper layers of the canopy always showed a higher maturity index, 6% more fat content, and 4% less water content than lower layers. Upper layers of HD trees showed the highest phenol content, whereas lower layers of MD trees showed the lowest phenol content (36% less than the upper layers of HD). HD trees showed the largest differences in fruit maturation, water and fat content between upper and lower canopy positions, increasing quality and oil yield variability at harvest. ‘Koroneiki’ showed more stable oils with a 28% higher MUFA/PUFA ratio and 12% higher phenol content than ‘Cerasuola’ oils. This study provides further evidence of the fact that cultivar, planting density, and canopy architecture may be strong determinants of olive oil yield and composition in hedgerow planting systems.

Filtration Scheduling: Quality Changes in Freshly Produced Virgin Olive Oil

Filtration is the most widespread stabilisation operation for extra virgin olive oil, preventing microbial and enzymatic changes. However, during the harvest, the workload of olive mills is at its peak. This results in two approaches to filtration: (i) delays it until after harvesting, increasing the risk of degraded oil quality, and (ii) filters it immediately, increasing the workload. The aim of our experiment is to assess the risk of delaying filtration and establish a safe delay time. Changes in the sensory profile and volatile compound contents were evaluated during 30 days in filtered and unfiltered samples. Significant differences were related to filtration: both turbidity grade and microbial contamination; no differences for the legal parameters were found. Two, contrasting, results were obtained with respect to oil quality: (i) the fusty defect, appearing in less than five days in unfiltered oils, leading to the downgrade of the oil’s commercial category, and (ii) filtration removing some lipoxygenase volatile compounds. Consequently, a fruity attribute was more pronounced in unfiltered samples until day five of storage; it seems that, from this point, the fusty defect masked a fruity attribute. Hence, filtering within a few days strongly reduced the risk of degraded oil quality compared to a delayed filtration.

Phenolic Profile Characterization of ‘Galega Vulgar’ and ‘Cobrançosa’ Portuguese Olive Cultivars along the Ripening Stages

The phenolic composition of olive fruits represents a vast and unique source of health beneficial molecules due to the presence of specific phenolic compounds (PCs), such as verbascoside (VERB), oleuropein (OLE) and its derivative molecules. Despite of being some of the most critical compounds regarding olive oil quality, these PCs are mostly abundant in olive fruits and leafs due to their hydrophilic nature. In olives, the phenolic profile suffers a deep and constant change along fruit ripening being the phenolic alcohols, such as hydroxytyrosol (HT), mainly formed by OLE, and/or OLE aglycone molecules degradation. The present work aims to study the maturation evolution of olive fruits from two major traditional Portuguese cultivars, ‘Galega Vulgar’ and ‘Cobrançosa’, in regard to their specific phenolic profile, as well as caliber (C), moisture (H), fat content in dry matter (OPDW) and maturity index (MI). Results show that both cultivars present distinct phenolic profiles along their ripening, with ‘Galega Vulgar’ reaching a high MI and OPDW at a much earlier ripening stage (S3), in agreement with the moment when a maximum OLE accumulation was registered. On the other hand, ‘Cobrançosa’ cultivar reached its higher MI and OPDW at S6 (harvest period), coinciding also with high OLE concentrations. MI may be used as a prediction tool for ’Galega Vulgar’ optimal harvesting time evaluation, associated with higher OLE and VERB concentrations, which will confer an additional protection towards diseases, that normally affect olive orchards.

An effective HPLC-based approach for the evaluation of the content of total phenolic compounds transferred from olives to virgin olive oil during the olive milling process

BACKGROUND

Several studies demonstrate a strong interest in learning more about phenolic transfer during oil extraction, with the main goal of increasing the phenolic concentration in olive oils. We aimed to propose and apply a new methodological approach for evaluating phenolic transfer from olives into oil during milling, based on the quantification of phenolic content in whole lyophilized fruits and the corresponding oils and considering the oil extraction yields.

RESULTS

We investigated the phenols transferred into the oil during olive milling in continuous extraction systems in Tuscany. In 2012, oils were extracted from cultivar Frantoio by a two-phase extraction system; in 2016, oils were extracted from cultivars Leccio del Corno and Arbequina by a three-phase extraction system. Results highlighted very low percentages of extracted phenols: up to 0.40% by the two-phase system and up to 0.19% by the three-phase system (0.08% for cultivar Arbequina and 0.19% for cultivar Leccio del Corno).

CONCLUSION

The usefulness of a simple and effective methodological approach for evaluating the extracted phenols was highlighted. Values of extracted phenols were up to 25 times lower than previous literature data. The proposed approach is applicable in all types of milling processes. © 2017 Society of Chemical Industry.

Recovery and stability over time of phenolic fractions by an industrial filtration system of olive mill wastewaters: a three-year study

BACKGROUND

The recovery of phenolic compounds from olive milling is recognized as strategic for producers. The aim of this work was to evaluate the quality and stability of retentates obtained from olive mill wastewaters treated with a membrane filtration system constituted by a micro-, ultra- and nanofiltration, followed by a final reverse osmosis, over three crop seasons. Efficiency was evaluated in terms of phenolic amount in the retentates and of organic load in the final discarded waters. Phenolic compounds were quantified using tyrosol as external standard.

RESULTS

Our study highlighted a reproducibility of the process over years and a low organic load in permeates from reverse osmosis. Hydroxytyrosol was very stable in the liquid products at 18-28 °C over 24 months of storage. The retentates from reverse osmosis showed the highest phenolic content (78.6 mg g^-1 dry matter in 2015), associated with a potassium content of 22 g kg^-1 .

CONCLUSIONS

The liquid concentrated retentates showed an unexpected stability over time of their bioactive phenolic compounds, particularly of hydroxytyrosol. These samples recovered from olive mill wastewaters can be good sources of natural antioxidants and potassium to guarantee the correct intake and to formulate new food ingredients or food products. © 2017 Society of Chemical Industry.

USA National Phenology Network's volunteer-contributed observations yield predictive models of phenological transitions

Purpose

In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. The aim of this study was to explore the potential that exists in the broad and rich volunteer-collected dataset maintained by the USA-NPN for constructing models predicting the timing of phenological transition across species’ ranges within the continental United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth (2009-present). Whether data exhibiting such limitations can be used to develop predictive models appropriate for use across large geographic regions has not yet been explored.

Methods

We constructed predictive models for phenophases that are the most abundant in the database and also relevant to management applications for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation—thermal time models with a fixed start date.

Results

Sufficient data were available to construct 107 individual species × phenophase models. Remarkably, given the limited temporal depth of this dataset and the simple modeling approach used, fifteen of these models (14%) met our criteria for model fit and error. The majority of these models represented the “breaking leaf buds” and “leaves” phenophases and represented shrub or tree growth forms. Accumulated growing degree day (GDD) thresholds that emerged ranged from 454 GDDs (Amelanchier canadensis-breaking leaf buds) to 1,300 GDDs (Prunus serotina-open flowers). Such candidate thermal time thresholds can be used to produce real-time and short-term forecast maps of the timing of these phenophase transition. In addition, many of the candidate models that emerged were suitable for use across the majority of the species’ geographic ranges. Real-time and forecast maps of phenophase transitions could support a wide range of natural resource management applications, including invasive plant management, issuing asthma and allergy alerts, and anticipating frost damage for crops in vulnerable states.

Implications

Our finding that several viable thermal time threshold models that work across the majority of the species ranges could be constructed from the USA-NPN database provides clear evidence that great potential exists this dataset to develop more enhanced predictive models for additional species and phenophases. Further, the candidate models that emerged have immediate utility for supporting a wide range of management applications.