scholarly journals Data mining and non-invasive proximal sensing for precision viticulture

2015 ◽  
Author(s):  
Maria Diago ◽  
Salvador Gutiérrez ◽  
Javier Tardaguila ◽  
Juan Fernández-Novales
Keyword(s):  
Data Mining ◽  
Proximal Sensing ◽  
Non Invasive ◽  
Precision Viticulture

scholarly journals Decay Detection in an Ancient Column with Combined Close-Range Photogrammetry (CRP) and Ultrasonic Tomography

Minerals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1114
Author(s):  
Giuseppe Casula ◽  
Silvana Fais ◽  
Francesco Cuccuru ◽  
Maria Giovanna Bianchi ◽  
Paola Ligas ◽  
...  
Keyword(s):  
High Resolution ◽  
Low Frequency ◽  
Ultrasonic Tomography ◽  
Proximal Sensing ◽  
Non Invasive ◽  
Close Range Photogrammetry ◽  
Resolution Model ◽  
Close Range ◽  
Ultrasonic Techniques ◽  
High Resolution Model

This study presents the integrated application of a few non-destructive techniques, i.e., Close Range Photogrammetry (CRP), and low frequency (24 kHz) ultrasonic tomography complemented by petrographical analysis. The aim here is to assess the conservation state of a Carrara marble column in the Basilica of San Saturnino, which is part of a V-VI century Palaeo Christian complex in the city of Cagliari (Italy). The high resolution 3D modelling of the studied artifact was computed starting from the integration of proximal sensing techniques, such as CRP based on the Structure from Motion (SfM) technique, which provided information on the geometrical anomalies and reflectivity of the investigated marble column surface. The inner parts of the studied body were inspected successfully in a non-invasive way by computing the velocity pattern of the ultrasonic signal through the investigated materials, using 3D ultrasonic tomography. The latter was optimally designed based on the 3D CRP analysis and the locations of the source and receiver points were detected as accurately as possible. The integrated application of in situ CRP and ultrasonic techniques provided a full 3D high resolution model of the investigated artifact, which made it possible to evaluate the material characteristics and its degradation state, affecting mainly the shallower parts of the column. The 3D visualisation improves the efficiency, accuracy, and completeness of the interpretative process of data of a different nature in quite easily understood displays, as well as the communication between different technicians.

scholarly journals State of the Art of Monitoring Technologies and Data Processing for Precision Viticulture

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 201
Author(s):  
Marco Ammoniaci ◽  
Simon-Paolo Kartsiotis ◽  
Rita Perria ◽  
Paolo Storchi
Keyword(s):  
New Technologies ◽  
State Of The Art ◽  
Variable Rate ◽  
Proximal Sensing ◽  
Use Of Resources ◽  
Yield And Quality ◽  
Monitoring Tools ◽  
Precision Viticulture ◽  
Monitoring Technologies ◽  
The Right

Precision viticulture (PV) aims to optimize vineyard management, reducing the use of resources, the environmental impact and maximizing the yield and quality of the production. New technologies as UAVs, satellites, proximal sensors and variable rate machines (VRT) are being developed and used more and more frequently in recent years thanks also to informatics systems able to read, analyze and process a huge number of data in order to give the winegrowers a decision support system (DSS) for making better decisions at the right place and time. This review presents a brief state of the art of precision viticulture technologies, focusing on monitoring tools, i.e., remote/proximal sensing, variable rate machines, robotics, DSS and the wireless sensor network.

scholarly journals A data mining methodology for predicting early stage Parkinson's disease using non-invasive, high-dimensional gait sensor data

2015 ◽  
Vol 5 (4) ◽  
pp. 238-254 ◽  
Author(s):  
Conrad Tucker ◽  
Yixiang Han ◽  
Harriet Black Nembhard ◽  
Wang-Chien Lee ◽  
Mechelle Lewis ◽  
...  
Keyword(s):  
Data Mining ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Early Stage ◽  
Sensor Data ◽  
High Dimensional ◽  
Non Invasive

scholarly journals Remote Sensing Vegetation Indices in Viticulture: A Critical Review

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 457
Author(s):  
Rigas Giovos ◽  
Dimitrios Tassopoulos ◽  
Dionissios Kalivas ◽  
Nestor Lougkos ◽  
Anastasia Priovolou
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Regional Scale ◽  
Vegetation Indices ◽  
Proximal Sensing ◽  
Spectral Bands ◽  
Sensing Platforms ◽  
Precision Viticulture ◽  
Remote Sensing Methods

One factor of precision agriculture is remote sensing, through which we can monitor vegetation health and condition. Much research has been conducted in the field of remote sensing and agriculture analyzing the applications, while the reviews gather the research on this field and examine different scientific methodologies. This work aims to gather the existing vegetation indices used in viticulture, which were calculated from imagery acquired by remote sensing platforms such as satellites, airplanes and UAVs. In this review we present the vegetation indices, the applications of these and the spatial distribution of the research on viticulture from the early 2000s. A total of 143 publications on viticulture were reviewed; 113 of them had used remote sensing methods to calculate vegetation indices, while the rejected ones have used proximal sensing methods. The findings show that the most used vegetation index is NDVI, while the most frequently appearing applications are monitoring and estimating vines water stress and delineation of management zones. More than half of the publications use multitemporal analysis and UAVs as the most used among remote sensing platforms. Spain and Italy are the countries with the most publications on viticulture with one-third of the publications referring to regional scale whereas the others to site-specific/vineyard scale. This paper reviews more than 90 vegetation indices that are used in viticulture in various applications and research topics, and categorized them depending on their application and the spectral bands that they are using. To summarize, this review is a guide for the applications of remote sensing and vegetation indices in precision viticulture and vineyard assessment.

scholarly journals Comparison of the Non-Invasive Monitoring of Fresh-Cut Lettuce Condition with Imaging Reflectance Hyperspectrometer and Imaging PAM-Fluorimeter

2021 ◽  
Author(s):  
Boris Shurygin ◽  
Olga Chivkunova ◽  
Olga Solovchenko ◽  
Alexei Solovchenko ◽  
Alexey Dorokhov ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Hyperspectral Data ◽  
Invasive Monitoring ◽  
Proximal Sensing ◽  
Leaf Quality ◽  
Non Invasive ◽  
Quality Degradation ◽  
Advanced Stages ◽  
Fresh Cut

We compared two approaches to non-invasive proximal sensing of the early changes in fresh-cut lettuce leaf quality: hyperspectral imaging and imaging PAM-fluorometry of chlorophyll contained in the leaves. The assessments made by the imaging techniques were confronted with the quality assessments made by traditional biochemical assays: relative water content and foliar pigment (chlorophyll and carotenoid) composition. The hyperspectral imaging-based approach provided the highest sensitivity to the decline of fresh-cut lettuce leaf quality taking place within 24 h from cutting. Using of the imaging PAM was complicated by (i) weak correlation of the spatial distribution pattern of the Qy parameter with the actual physiological condition of the plant object and (ii) its high degree of heterogeneity. Accordingly, the imaging PAM-based approach was sensitive only to the manifestations of leaf quality degradation only at advanced stages of the process. Sealing the leaves in the polyethylene bags slowed down the leaf quality degradation at the initial stages (< 3 days) but promoted its rate at more advanced stages, likely due to build-up of ethylene in the bags. An approach was developed to the processing of hyperspectral data for non-invasive monitoring of the lettuce leaves with a potential for implementation in greenhouses and packinghouses.

Sign in / Sign up

Export Citation Format

Share Document