5 research outputs found
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Regression kriging for improving crop height models fusing ultra-sonic sensing with UAV imagery
A crop height model (CHM) can be an important element of the decision making process in
agriculture, because it relates well with many agronomic parameters, e.g., crop height, plant biomass
or crop yield. Today, CHMs can be inexpensively obtained from overlapping imagery captured
from unmanned aerial vehicle (UAV) platforms or from proximal sensors attached to ground-based
vehicles used for regular management. Both approaches have their limitations and combining them
with a data fusion may overcome some of these limitations. Therefore, the objective of this study was
to investigate if regression kriging, as a geostatistical data fusion approach, can be used to improve the
interpolation of ground-based ultrasonic measurements with UAV imagery as covariate. Regression
kriging might be suitable because we have a sparse data set (ultrasound) and an exhaustive data
set (UAV) and both data sets have favorable properties for geostatistical analysis. To confirm this,
we conducted four missions in two different fields in total, where we collected UAV imagery and
ultrasonic data alongside. From the overlapping UAV images, surface models and ortho-images were
generated with photogrammetric processing. The maps generated by regression kriging were of
much higher detail than the smooth maps generated by ordinary kriging, because regression kriging
ensures that for each prediction point information from the UAV, imagery is given. The relationship
with crop height, fresh biomass and, to a lesser extent, with crop yield, was stronger using CHMs
generated by regression kriging than by ordinary kriging. The use of UAV data from the prior
mission was also of benefit and could improve map accuracy and quality. Thus, regression kriging is
a flexible approach for the integration of UAV imagery with ground-based sensor data, with benefits
for precision agriculture-oriented farmers and agricultural service providers
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Zielflächenorientierte, präzise Echtzeit-Fungizidapplikation in Getreide
Im Rahmen eines Verbundprojektes wurden Echtzeit-Applikationstechnologien mit berĂĽhrungslosen
Sensoren für präzise Fungizid-Spritzungen in Getreide entwickelt. Das Entscheidungshilfe-
System proPlant expert.classic bzw. die Internetversion proPlant expert.com
(proPlant GmbH) empfiehlt geeignete Fungizide und Dosierungen fĂĽr ein bestimmtes Infektionsszenario
der acht wichtigsten Blatt- und Ă„hrenkrankheiten von Winterweizen. Das Precision-
Farming-Modul „Fungizid“, welches auf dem Terminal in der Traktorenkabine läuft, steuert
das präzise Spritzverfahren. Das Modul bestimmt die lokale Zielapplikationsmenge während
des Spritzens durch Nutzung des lokalen Ultraschallsensorwerts als Eingabeparameter.
In den Jahren 2013 und 2014 wurden Feldversuche in Winterweizen durchgefĂĽhrt, um die
Beziehung zwischen den Sensorwerten (Ultraschall- und Kamerasensor) und den Pflanzenparametern
Pflanzenoberfläche (Leaf Area Index, LAI) sowie Biomasse zu analysieren. Diese
sind für einen örtlich angepassten variablen Fungizideinsatz zur Bemessung der Spritzmenge
wichtig. Die Messungen wurden mehrmals während der Vegetationsperiode an visuell ausgewählten
Stichprobenpunkten entsprechend der unterschiedlichen Bestandsdichte durchgefĂĽhrt.
Nach Ă„nderungen an der Sensortechnik konnten fĂĽr 2014 signifikante lineare Regressionsmodelle
zur Beschreibung der Beziehung zwischen den Sensorwerten und den zwei
Pflanzenparametern LAI sowie Biomasse gefunden werden.Real-time application technologies based on the target crop, crop surface area and biomass
using non-contact sensors for precise fungicide spraying in winter wheat have been developed
in a joint research project. The decision support system proPlant expert.classic and the internet-
version proPlant expert.com (proPlant GmbH) suggest appropriate fungicides and dosages
for certain infection scenarios of eight important leaf and ear diseases of winter wheat. The
Precision Farming Module “Fungicide”, which runs on the on-board terminal in the tractor cabin,
controls the spraying process. During the spraying process, the module defines the local
target application amount using a local ultrasonic sensor value as an input parameter.
Winter wheat field experiments were conducted in 2013 and 2014 (Agri Con Co., ATB) to
analyse the relationship between the sensor values (ultrasonic and camera) and the leaf area
index (LAI) and biomass crop parameters that are important for a locally adapted and variable
fungicide application rate. Measurements were performed several times during the vegetation
period at sampling points that were visually selected based on crop density. Regression
analyses showed that after technical changes in 2014, a linear relationship was obtained
between the sensor values and the two crop parameters
SAMHD1-Deficient CD14+ Cells from Individuals with Aicardi-Goutières Syndrome Are Highly Susceptible to HIV-1 Infection
Myeloid blood cells are largely resistant to infection with human immunodeficiency virus type 1 (HIV-1). Recently, it was reported that Vpx from HIV-2/SIVsm facilitates infection of these cells by counteracting the host restriction factor SAMHD1. Here, we independently confirmed that Vpx interacts with SAMHD1 and targets it for ubiquitin-mediated degradation. We found that Vpx-mediated SAMHD1 degradation rendered primary monocytes highly susceptible to HIV-1 infection; Vpx with a T17A mutation, defective for SAMHD1 binding and degradation, did not show this activity. Several single nucleotide polymorphisms in the SAMHD1 gene have been associated with Aicardi-Goutières syndrome (AGS), a very rare and severe autoimmune disease. Primary peripheral blood mononuclear cells (PBMC) from AGS patients homozygous for a nonsense mutation in SAMHD1 (R164X) lacked endogenous SAMHD1 expression and support HIV-1 replication in the absence of exogenous activation. Our results indicate that within PBMC from AGS patients, CD14+ cells were the subpopulation susceptible to HIV-1 infection, whereas cells from healthy donors did not support infection. The monocytic lineage of the infected SAMHD1 -/- cells, in conjunction with mostly undetectable levels of cytokines, chemokines and type I interferon measured prior to infection, indicate that aberrant cellular activation is not the cause for the observed phenotype. Taken together, we propose that SAMHD1 protects primary CD14+ monocytes from HIV-1 infection confirming SAMHD1 as a potent lentiviral restriction factor