Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.

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Further In Vitro Assessment and Mid-Term Evaluation of Control Strategy of Xylella fastidiosa subsp. pauca in Olive Groves of Salento (Apulia, Italy)

Pathogens ◽

10.3390/pathogens10010085 ◽

2021 ◽

Vol 10 (1) ◽

pp. 85

Author(s):

Giuseppe Tatulli ◽

Vanessa Modesti ◽

Nicoletta Pucci ◽

Valeria Scala ◽

Alessia L’Aurora ◽

...

Keyword(s):

Control Strategy ◽

Xylella Fastidiosa ◽

In Planta ◽

Bacterial Concentration ◽

Infected Area ◽

Olive Groves ◽

Term Evaluation ◽

In Vitro Assessment ◽

Olive Trees

During recent years; Xylella fastidiosa subsp. pauca (Xfp) has spread in Salento causing relevant damage to the olive groves. Measures to contain the spreading of the pathogen include the monitoring of the areas bordering the so-called “infected” zone and the tree eradication in case of positive detection. In order to provide a control strategy aimed to maintain the tree productivity in the infected areas, we further evaluated the in vitro and in planta mid-term effectiveness of a zinc-copper-citric acid biocomplex. The compound showed an in vitro bactericidal activity and inhibited the biofilm formation in representative strains of X. fastidiosa subspecies, including Xfp isolated in Apulia from olive trees. The field mid-term evaluation of the control strategy assessed by quantitative real-time PCR in 41 trees of two olive groves of the “infected” area revealed a low concentration of Xfp over the seasons upon the regular spraying of the biocomplex over 3 or 4 consecutive years. In particular, the bacterial concentration lowered in July and October with respect to March, after six consecutive treatments. The trend was not affected by the cultivar and it was similar either in the Xfp-sensitive cultivars Ogliarola salentina and Cellina di Nardò or in the Xfp-resistant Leccino. Moreover, the scoring of the number of wilted twigs over the seasons confirmed the trend. The efficacy of the treatment in the management of olive groves subjected to a high pathogen pressure is highlighted by the yielded a good oil production

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How Ecosystem Services Can Strengthen the Regeneration Policies for Monumental Olive Groves Destroyed by Xylella fastidiosa Bacterium in a Peri-Urban Area

Sustainability ◽

10.3390/su13168778 ◽

2021 ◽

Vol 13 (16) ◽

pp. 8778

Author(s):

Teodoro Semeraro ◽

Elisa Gatto ◽

Riccardo Buccolieri ◽

Valentina Catanzaro ◽

Luigi De Bellis ◽

...

Keyword(s):

Land Use ◽

Ecosystem Services ◽

Land Cover ◽

Cultural Heritage ◽

Urban Area ◽

Urban Areas ◽

Xylella Fastidiosa ◽

Trade Offs ◽

Olive Groves ◽

Olive Trees

The Apulian Region (Italy) is a socio-ecological system shaped by the millennial co-evolution between human actions and ecological processes. It is characterized by monumental olive groves protected from Regional Law 14/2007 for the cultural value of the landscape, currently threatened by the spread of a devastating phytopathogen, the bacteria Xylella fastidiosa. The aim of this paper is to apply landscape resilience analysis focusing on ecosystem services to understand the potential effects and trade-offs of regeneration policies in a peri-urban area characterized by monumental olive groves land cover. The study involved land-cover and land-use analysis, supported by a survey on the inhabitants and an ecosystem services analysis. The results showed a mismatch between the agroecosystem and the social and economic use linked to leisure or hospitality. The study area was defined as a peri-urban landscape characterized by tourist use. From the interviews of the users, the cultural heritage of olive groves seems linked to the presence of olive trees like a status quo of the landscape and olive oil productions. The culture aspect could thus be preserved by changing the type of olive trees. In addition, the analysis showed that the microclimate could be preserved and enhanced in terms of air temperature and thermal comfort, by replacing the olive trees with varieties resistant to Xylella, such as cv. Leccino. Therefore, regeneration policies that promote replacing dead olive groves with new olive trees could be efficient to stimulate social components of the landscape and improve the resilience of ecosystem services in peri-urban areas in the interest of the cultural heritage of the users and benefits that they provide. An ecosystem services analysis at a local scale could be a strategy for an integrated regenerate approach between land-use and land-cover with social, ecological, and economic evolutions vision orientated to a sustainable and desirable future.

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Xf-Rovim. A Field Robot to Detect Olive Trees Infected by Xylella Fastidiosa Using Proximal Sensing

Remote Sensing ◽

10.3390/rs11030221 ◽

2019 ◽

Vol 11 (3) ◽

pp. 221 ◽

Cited By ~ 7

Author(s):

Beatriz Rey ◽

Nuria Aleixos ◽

Sergio Cubero ◽

José Blasco

Keyword(s):

Structural Information ◽

Xylella Fastidiosa ◽

Low Cost ◽

Plant Diseases ◽

Remotely Operated Vehicle ◽

Proximal Sensing ◽

Leaf Level ◽

Olive Groves ◽

Olive Trees ◽

Field Robot

The use of remote sensing to map the distribution of plant diseases has evolved considerably over the last three decades and can be performed at different scales, depending on the area to be monitored, as well as the spatial and spectral resolution required. This work describes the development of a small low-cost field robot (Remotely Operated Vehicle for Infection Monitoring in orchards, XF-ROVIM), which is intended to be a flexible solution for early detection of Xylella fastidiosa (X. fastidiosa) in olive groves at plant to leaf level. The robot is remotely driven and fitted with different sensing equipment to capture thermal, spectral and structural information about the plants. Taking into account the height of the olive trees inspected, the design includes a platform that can raise the cameras to adapt the height of the sensors to a maximum of 200 cm. The robot was tested in an olive grove (4 ha) potentially infected by X. fastidiosa in the region of Apulia, southern Italy. The tests were focused on investigating the reliability of the mechanical and electronic solutions developed as well as the capability of the sensors to obtain accurate data. The four sides of all trees in the crop were inspected by travelling along the rows in both directions, showing that it could be easily adaptable to other crops. XF-ROVIM was capable of inspecting the whole field continuously, capturing geolocated spectral information and the structure of the trees for later comparison with the in situ observations.

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Distribution and Relative Abundance of Insect Vectors of Xylella fastidiosa in Olive Groves of the Iberian Peninsula

Insects ◽

10.3390/insects9040175 ◽

2018 ◽

Vol 9 (4) ◽

pp. 175 ◽

Cited By ~ 28

Author(s):

Marina Morente ◽

Daniele Cornara ◽

María Plaza ◽

José Durán ◽

Carmen Capiscol ◽

...

Keyword(s):

Sampling Method ◽

Sampling Methods ◽

Xylella Fastidiosa ◽

Ground Cover ◽

Ground Vegetation ◽

Insect Vectors ◽

Central Spain ◽

Tree Canopies ◽

Olive Groves ◽

Olive Trees

The phytosanitary emergency caused by the spread of Xylella fastidiosa in the Mediterranean has raised demands for a better understanding of the ecology of its presumed and candidate insect vectors. Here, we present the results of a two-year survey carried out in olive groves across southern, eastern and Central Spain and northeastern Portugal. Several sampling methods were tested and compared to select the most appropriate to estimate population levels of potential vectors of X. fastidiosa. The spittlebugs Philaenus spumarius and Neophilaenus campestris (Hemiptera: Aphrophoridae) were the main species associated with olive groves. Both species were widely present on herbaceous ground vegetation within the olive groves; P. spumarius mainly associated with Asteraceae and N. campestris with Poaceae. Due to the patchy distribution of spittlebugs within the olive groves, sweep nets were the most effective and least time-consuming sampling method for the estimation of population size both in the ground cover and tree canopies. Trends in population density showed that spittlebugs can be abundant on ground vegetation but very rare on olive canopies. Spittlebugs disperse in late spring to non-cultivated hosts that act as natural reservoirs. In late fall, adults return to the olive groves for oviposition. However, olive trees may act as transient hosts for spittlebugs and high population densities of these insect vectors should be avoided in areas where X. fastidiosa is present.

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The Multi-Millennial Olive Agroecosystem of Salento (Apulia, Italy) Threatened by Xylella Fastidiosa Subsp. Pauca: A Working Possibility of Restoration

Sustainability ◽

10.3390/su12176700 ◽

2020 ◽

Vol 12 (17) ◽

pp. 6700

Author(s):

Marco Scortichini

Keyword(s):

Cell Concentration ◽

Control Strategies ◽

Xylella Fastidiosa ◽

First Record ◽

Interdisciplinary Studies ◽

Insect Vector ◽

Infected Area ◽

Olive Groves ◽

Olive Trees ◽

Spray Treatment

In Salento, the olive agro-ecosystem has lasted more than 4000 years, and represents an invaluable local heritage for landscape, trade, and social traditions. The quarantine bacterium Xylella fastidiosa subsp. pauca was introduced in the area from abroad and has been widely threatening olive groves in the area. The successful eradication of quarantine phytopathogens requires a prompt identification of the causative agent at the new site, a restricted infected area, a highly effective local organization for crop uprooting and biological features of the micro-organism that would guarantee its complete elimination. However, at the time of the first record, these criteria were not met. Interdisciplinary studies showed that a zinc-copper-citric acid biocomplex allowed a consistent reduction of field symptoms and pathogen cell concentration within infected olive trees. In this perspective article, it is briefly described the implementation of control strategies in some olive farms of Salento. The protocol includes spray treatment with the biocomplex during spring and summer, regular pruning of the trees and mowing of soil between February and April to reduce the juvenile of the insect vector(s). Thus far, more than 500 ha have begun to follow this eco-friendly strategy within the “infected” and “containment” areas of Salento.

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Soil water content and olive tree yield responses to soil management, irrigation, and precipitation in a hilly Mediterranean area

Journal of Water and Climate Change ◽

10.2166/wcc.2018.224 ◽

2018 ◽

Vol 9 (4) ◽

pp. 672-678 ◽

Cited By ~ 6

Author(s):

G. Arampatzis ◽

E. Hatzigiannakis ◽

V. Pisinaras ◽

N. Kourgialas ◽

G. Psarras ◽

...

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Soil Management ◽

Olive Tree ◽

Mediterranean Area ◽

Mediterranean Countries ◽

Olive Groves ◽

Intensively Managed ◽

Olive Trees

Abstract Olive trees constitute one of the most dynamic cultivations for Mediterranean countries, while their economic importance is high. As water constitutes a fundamental factor affecting olive tree production, soil water content is a most critical parameter that must be monitored to improve olive trees’ cultivation management. Effects of precipitation, irrigation, and soil management on water content in four soil depths (10, 20, 30, 40 cm), four periods of the year (February–March, April–May, June–July, August–September) and three successive years were determined in 12 Mediterranean olive groves (Trifilia, southern Greece) as well as their respective fruit and olive oil yields. Significantly higher soil water content was recorded in the first (+16.8%) and third (+27.4%) year compared to the second year. Higher (+6.8%) water content was observed in irrigated olive groves compared to rainfed fields. Higher (+5.6%) water content was observed in sustainable olive groves compared to intensively managed fields. Significantly, higher soil moisture was recorded at 40 and 30 cm depth compared to 10 cm depth while intermediate values were observed at 20 cm. Marked increase in fruit yield was achieved through sustainable management (+39%) compared to intensive olive groves. The potential to improve irrigation practices in the area was also indicated by results of the present study.

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Automated Assay of a Four-Protein Biomarker Panel for Improved Detection of Ovarian Cancer

Cancers ◽

10.3390/cancers13020325 ◽

2021 ◽

Vol 13 (2) ◽

pp. 325

Author(s):

Christopher Walker ◽

Tuan-Minh Nguyen ◽

Shlomit Jessel ◽

Ayesha B. Alvero ◽

Dan-Arin Silasi ◽

...

Keyword(s):

Ovarian Cancer ◽

Early Detection ◽

Predictive Value ◽

Early Stage ◽

Ca 125 ◽

Healthy Controls ◽

Classification Models ◽

Serum Samples ◽

Protein Biomarker ◽

Biomarker Panel

Background: Mortality from ovarian cancer remains high due to the lack of methods for early detection. The difficulty lies in the low prevalence of the disease necessitating a significantly high specificity and positive-predictive value (PPV) to avoid unneeded and invasive intervention. Currently, cancer antigen- 125 (CA-125) is the most commonly used biomarker for the early detection of ovarian cancer. In this study we determine the value of combining macrophage migration inhibitory factor (MIF), osteopontin (OPN), and prolactin (PROL) with CA-125 in the detection of ovarian cancer serum samples from healthy controls. Materials and Methods: A total of 432 serum samples were included in this study. 153 samples were from ovarian cancer patients and 279 samples were from age-matched healthy controls. The four proteins were quantified using a fully automated, multi-analyte immunoassay. The serum samples were divided into training and testing datasets and analyzed using four classification models to calculate accuracy, sensitivity, specificity, PPV, negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). Results: The four-protein biomarker panel yielded an average accuracy of 91% compared to 85% using CA-125 alone across four classification models (p = 3.224 × 10−9). Further, in our cohort, the four-protein biomarker panel demonstrated a higher sensitivity (median of 76%), specificity (median of 98%), PPV (median of 91.5%), and NPV (median of 92%), compared to CA-125 alone. The performance of the four-protein biomarker remained better than CA-125 alone even in experiments comparing early stage (Stage I and Stage II) ovarian cancer to healthy controls. Conclusions: Combining MIF, OPN, PROL, and CA-125 can better differentiate ovarian cancer from healthy controls compared to CA-125 alone.

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Health Insurance Status as a Predictor of Mode of Colon Cancer Detection but Not Stage at Diagnosis: Implications for Early Detection

Public Health Reports ◽

10.1177/0033354921999173 ◽

2021 ◽

pp. 003335492199917

Author(s):

Lindsey A. Jones ◽

Katherine C. Brewer ◽

Leslie R. Carnahan ◽

Jennifer A. Parsons ◽

Blase N. Polite ◽

...

Keyword(s):

Colon Cancer ◽

Health Insurance ◽

Early Detection ◽

Late Stage ◽

Early Stage ◽

Insurance Status ◽

Stage At Diagnosis ◽

Health Insurance Status ◽

Percentage Point Increase ◽

Point Increase

Objective For colon cancer patients, one goal of health insurance is to improve access to screening that leads to early detection, early-stage diagnosis, and polyp removal, all of which results in easier treatment and better outcomes. We examined associations among health insurance status, mode of detection (screen detection vs symptomatic presentation), and stage at diagnosis (early vs late) in a diverse sample of patients recently diagnosed with colon cancer from the Chicago metropolitan area. Methods Data came from the Colon Cancer Patterns of Care in Chicago study of racial and socioeconomic disparities in colon cancer screening, diagnosis, and care. We collected data from the medical records of non-Hispanic Black and non-Hispanic White patients aged ≥50 and diagnosed with colon cancer from October 2010 through January 2014 (N = 348). We used logistic regression with marginal standardization to model associations between health insurance status and study outcomes. Results After adjusting for age, race, sex, and socioeconomic status, being continuously insured 5 years before diagnosis and through diagnosis was associated with a 20 (95% CI, 8-33) percentage-point increase in prevalence of screen detection. Screen detection in turn was associated with a 15 (95% CI, 3-27) percentage-point increase in early-stage diagnosis; however, nearly half (47%; n = 54) of the 114 screen-detected patients were still diagnosed at late stage (stage 3 or 4). Health insurance status was not associated with earlier stage at diagnosis. Conclusions For health insurance to effectively shift stage at diagnosis, stronger associations are needed between health insurance and screening-related detection; between screening-related detection and early stage at diagnosis; or both. Findings also highlight the need to better understand factors contributing to late-stage colon cancer diagnosis despite screen detection.

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HPLC-MS/MS method applied to an untargeted metabolomics approach for the diagnosis of “olive quick decline syndrome”

Analytical and Bioanalytical Chemistry ◽

10.1007/s00216-021-03279-7 ◽

2021 ◽

Author(s):

Sabrina Di Masi ◽

Giuseppe E. De Benedetto ◽

Cosimino Malitesta ◽

Maria Saponari ◽

Cinzia Citti ◽

...

Keyword(s):

Bacterial Infections ◽

High Performance ◽

High Resolution Mass Spectrometry ◽

Xylella Fastidiosa ◽

Long Chain Fatty Acids ◽

Powerful Approach ◽

Diffusible Signal Factor ◽

Profile Changes ◽

Olive Quick Decline Syndrome ◽

Olive Trees

AbstractOlive quick decline syndrome (OQDS) is a disorder associated with bacterial infections caused by Xylella fastidiosa subsp. pauca ST53 in olive trees. Metabolic profile changes occurring in infected olive trees are still poorly investigated, but have the potential to unravel reliable biomarkers to be exploited for early diagnosis of infections. In this study, an untargeted metabolomic method using high-performance liquid chromatography coupled to quadrupole-time-of-flight high-resolution mass spectrometry (HPLC-ESI-Q-TOF-MS) was used to detect differences in samples (leaves) from healthy (Ctrl) and infected (Xf) olive trees. Both unsupervised and supervised data analysis clearly differentiated the groups. Different metabolites have been identified as potential specific biomarkers, and their characterization strongly suggests that metabolism of flavonoids and long-chain fatty acids is perturbed in Xf samples. In particular, a decrease in the defence capabilities of the host after Xf infection is proposed because of a significant dysregulation of some metabolites belonging to flavonoid family. Moreover, oleic acid is confirmed as a putative diffusible signal factor (DSF). This study provides new insights into the host-pathogen interactions and confirms LC-HRMS-based metabolomics as a powerful approach for disease-associated biomarkers discovery in plants. Graphical abstract

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Early Detection of Alzheimer’s Disease Using Polar Harmonic Transforms and Optimized Wavelet Neural Network

Applied Sciences ◽

10.3390/app11041574 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1574

Author(s):

Shabana Urooj ◽

Satya P. Singh ◽

Areej Malibari ◽

Fadwa Alrowais ◽

Shaeen Kalathil

Keyword(s):

Neural Network ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Early Detection ◽

Differential Evolution ◽

Early Stage ◽

Selection Process ◽

Parameter Tuning ◽

Wavelet Neural Network ◽

Tuning Parameter

Effective and accurate diagnosis of Alzheimer’s disease (AD), as well as early-stage detection, has gained more and more attention in recent years. For AD classification, we propose a new hybrid method for early detection of Alzheimer’s disease (AD) using Polar Harmonic Transforms (PHT) and Self-adaptive Differential Evolution Wavelet Neural Network (SaDE-WNN). The orthogonal moments are used for feature extraction from the grey matter tissues of structural Magnetic Resonance Imaging (MRI) data. Irrelevant features are removed by the feature selection process through evaluating the in-class and among-class variance. In recent years, WNNs have gained attention in classification tasks; however, they suffer from the problem of initial parameter tuning, parameter setting. We proposed a WNN with the self-adaptation technique for controlling the Differential Evolution (DE) parameters, i.e., the mutation scale factor (F) and the cross-over rate (CR). Experimental results on the Alzheimer’s disease Neuroimaging Initiative (ADNI) database indicate that the proposed method yields the best overall classification results between AD and mild cognitive impairment (MCI) (93.7% accuracy, 86.0% sensitivity, 98.0% specificity, and 0.97 area under the curve (AUC)), MCI and healthy control (HC) (92.9% accuracy, 95.2% sensitivity, 88.9% specificity, and 0.98 AUC), and AD and HC (94.4% accuracy, 88.7% sensitivity, 98.9% specificity and 0.99 AUC).

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