A Large-Scale Dataset and Deep Learning Model for Detecting and Counting Olive Trees in Satellite Imagery

Since the Pre-Roman era, olive trees have a significant economic and cultural value. In 2019, the Al-Jouf region, in the north of the Kingdom of Saudi Arabia, gained a global presence by entering the Guinness World Records, with the largest number of olive trees in the world. Olive tree detecting and counting from a given satellite image are a significant and difficult computer vision problem. Because olive farms are spread out over a large area, manually counting the trees is impossible. Moreover, accurate automatic detection and counting of olive trees in satellite images have many challenges such as scale variations, weather changes, perspective distortions, and orientation changes. Another problem is the lack of a standard database of olive trees available for deep learning applications. To address these problems, we first build a large-scale olive dataset dedicated to deep learning research and applications. The dataset consists of 230 RGB images collected over the territory of Al-Jouf, KSA. We then propose an efficient deep learning model (SwinTUnet) for detecting and counting olive trees from satellite imagery. The proposed SwinTUnet is a Unet-like network which consists of an encoder, a decoder, and skip connections. Swin Transformer block is the fundamental unit of SwinTUnet to learn local and global semantic information. The results of an experimental study on the proposed dataset show that the SwinTUnet model outperforms the related studies in terms of overall detection with a 0.94% estimation error.

Increase in Fermentable Sugars of Olive Tree Pruning Biomass for Bioethanol Production: Application of an Experimental Design for Optimization of Alkaline Pretreatment

Olive Tree Pruning (OTP) biomass can be considered a suitable source of fermentable sugars for the production of second-generation bioethanol. The present study proposes a remarkable alternative for the valorization of olive tree pruning residues. OTP biomass was processed using a sequential calcium hydroxide pretreatment/enzymatic hydrolysis. A 24–1 half fractional factorial design was adopted for the screening of process variables and a central composite design was used for the optimization stage. Temperature and lime loading resulted statistically significant. The following optimal conditions were obtained: 0.01 g of Ca(OH)2/g of dry material, 20 g of H2O/g of dry material at 160 °C for 2 h. The mathematical model that governs this alkaline pretreatment was obtained with a 76% adjusted determination coefficient, which means that it is a good representation of the process. Under optimal operating conditions, 13% of the cellulose and 88% of the hemicellulose was solubilized. Moreover, the fermentable sugar content increased 1800% compared with the initial conditions, obtaining 240 g of glucose per kg of OTP residue. The fermentable sugars obtained after the calcium hydroxide pretreatment and enzymatic hydrolysis of OTP biomass yielded 2.8 g of ethanol/100 g of raw material.

Innovative Extraction Technologies for Development of Functional Ingredients Based on Polyphenols from Olive Leaves

Olive tree (Olea europea L.) leaves represent around 10% of the total weight of olives arriving at any given mill, which are generally discarded, causing economic and environmental issues. However, these are rich sources of natural bioactive compounds (i.e., polyphenols), which have health-promoting potential. Thus, the valorization of olive leaves by recovering and reusing their components should be a must for food sustainability and circular economy. This review provides an insight into the principal polyphenols present in olive leaves, together with agronomic variables influencing their content. It also summarizes the recent advances in the application of novel extraction technologies that have shown promising extraction efficacy, reducing the volume of extraction solvent and saving time and cost. Moreover, potential industrial uses and international patents filed in the pharmaceutic, food, and cosmetic sectors are discussed.

Estimating Productivity, Detecting Biotic Disturbances and Assessing the Health State of Traditional Olive Groves, Using Nondestructive Phenotypic Techniques

Conservation of traditional olive groves through effective monitoring of their health state is crucial both at a tree and at a population level. In this study, we introduce a comprehensive methodological framework for estimating the traditional olive grove health state, by considering the fundamental phenotypic, spectral, and thermal traits of the olive trees. We obtained phenotypic information from olive trees on the Greek island of Lesvos by combining this with in situ measurement of spectral reflectance and thermal indices to investigate the effect of the olive tree traits on productivity, the presence of the olive leaf spot disease (OLS), and olive tree classification based on their health state. In this context, we identified a suite of important features, derived from linear and logistic regression models, which can explain productivity and accurately evaluate infected and noninfected trees. The results indicated that either specific traits or combinations of them are statistically significant predictors of productivity, while the occurrence of OLS symptoms can be identified by both the olives’ vitality traits and by the thermal variables. Finally, the classification of olive trees into different health states possibly offers significant information to explain traditional olive grove dynamics for their sustainable management.

Analysis of the Manufacturing Variables of Binderless Panels Made of Leaves of Olive Tree (Olea europaea L.) Pruning Waste

While the construction industry consumes more raw materials than any other industrial sector, agriculture generates a large amount of waste that is not managed properly. The olive industry produces more than 7.5 million tons of waste that could be recovered. This paper presents a new method to valorize the leaves of olive tree pruning waste consisting of the manufacture of ecologic boards without adhesives by hot pressing. In order to analyze their influence, three manufacturing variables were varied to obtain the boards: leaf type (shredded and whole leaves), temperature (130, 140 and 150 °C) and time (4, and 12 min). Twenty-four boards were made and were then tested for their mechanical, physical and thermal properties according to the EN standards. The boards showed good results of thickness swelling (TS), water absorption (WA) and of thermal conductivity and can be used as an alternative for manufacturing thermal insulation boards. With a smaller particle size of shredded leaves, longer pressing times and higher pressing temperatures, the mechanical behavior of the boards could improve. The olive leaves are a low-cost renewable resource, and manufacturing products with a long, useful life can be beneficial to the environment.

Antibacterial activity of the phenolic extract of wild virgin olive oil in vitro

Background: The olive tree (Olea europaea L.), the most widespread plant species in the Mediterranean basin, includes two forms: cultivated (var Europaea) and wild (var Sylvestris). Wild olive trees or oleasters cover large areas in Algeria. It has been shown that oil from oleaster has a higher content of phenolic compounds, which could have antimicrobial properties. Objective:: The objective of this study was to assess the antibacterial activity of phenolic extracts from four Algerian oleaster oils and an extra virgin olive oil (EVOO) from Chemlal variety. Methods: Phenolic compounds were determined by UHPLC-MS. Antibacterial activity was tested against six referenced human enteropathogenic bacteria by the agar disc diffusion method by measuring the diameters of the zone of inhibition. Results: The results revealed a similarity between the phenolic composition of oleasters 1 and 3 and between oleaster 4 and EVOO; however, the phenolic composition of oleaster 2 that the poorer was markedly different with a higher content of free phenolic alcohols and lower in secoiridoids.