scholarly journals Identification of Weather Conditions Associated with the Occurrence, Severity, and Incidence of Black Seed Disease of Strawberry Caused by Mycosphaerella fragariae

2018 ◽  
Vol 108 (1) ◽  
pp. 83-93 ◽  
Author(s):  
Odile Carisse ◽  
Vanessa McNealis
Keyword(s):  
Nonlinear Models ◽  
Weather Conditions ◽  
Total Rainfall ◽  
Crop Losses ◽  
Black Seed ◽  
Management Actions ◽  
Disease Occurrence ◽  
Sporadic Disease ◽  
Mycosphaerella Fragariae ◽  
The Relationship

Black seed disease (BSD) of strawberry is a sporadic disease caused by Mycosphaerella fragariae. Because little is known about potential crop losses or the weather conditions conducive to disease development, fungicides are generally not applied or are applied based on a preset schedule. Data collected from 2000 to 2011 representing 50 farm-years (total of 186 strawberry fields) were used to determine potential crop losses and to study the influence of weather on disease occurrence and development. First, logistic regression was used to model the relationship between occurrence of BSD and weather variables. Second, linear and nonlinear regressions were used to model the number of black seed per berry (severity) and the percentage of diseased berries (incidence). Of the 186 fields monitored, 78 showed black seed symptoms, and the number of black seed per berry ranged from 1 to 10, whereas the percentage of diseased berries ranged from 3 to 32%. The most influential weather variable was total rainfall (in millimeters) in May, with a threshold of 103 mm of rain (absence of BSD < 103 mm < presence of BSD). Similarly, nonlinear models with the total rainfall in May accurately predicted both disease severity and incidence (r = 0.94 and 0.97, respectively). Considering that management actions such as fungicide application are not needed every year in every field, these models could be used to identify fields that are at risk of BSD.

Factors affecting abundance and oviposition rates of a field population of the Old World screw-worm fly, Chrysomya bezziana (Diptera: Calliphoridae)

2004 ◽  
Vol 94 (4) ◽  
pp. 359-368 ◽  
Author(s):  
R.J. Mahon ◽  
H. Ahmad ◽  
K.G. Wardhaugh
Keyword(s):  
Weather Conditions ◽  
Total Rainfall ◽  
Old World ◽  
Factors Affecting ◽  
Malaysian Population ◽  
Early Evening ◽  
Catch Rates ◽  
Trap Catches ◽  
The Relationship ◽  
Chrysomya Bezziana

AbstractSentinel cattle and a grid of swormlure-baited sticky traps were used to monitor a Malaysian population of the Old World screw-worm fly, Chrysomya bezziana Villeneuve. Observations were carried out on an isolated cattle station at monthly intervals during the period August 1996 to June 2000. The number of flies caught was unaffected by weather conditions at the time of trapping, but was positively correlated with the total rainfall and the average daily air temperature prevailing 15–28 days earlier, when trapped flies were still juveniles. Trap catches were biased in favour of females, but daily catch rates of both sexes increased significantly the longer traps were open, suggesting that efficacy was related to the differential volatility of the chemicals comprising swormlure. Oviposition on sentinel cattle occurred mostly in late afternoon or early evening but increased significantly as the wound aged. Oviposition rates were positively correlated with female catch rates, but the relationship was curvilinear, suggesting that fly populations may be subject to some form of density-dependent constraint. Consistent differences in oviposition rates on sentinel cattle at different localities on the cattle station suggested the existence of highly clumped, quasi-stationary populations. Differences in trap catches between traps located in pastoral areas and those sited in nearby oil palm or rubber plantations supported this interpretation of the data. These findings are discussed in relation to the use of the sterile insect technique for the control of screw-worm fly infestations.

scholarly journals Factors affecting waterfowl hunting and harvest at the Evros delta, Greece

2020 ◽  
Vol 150 ◽  
Author(s):  
Savas Kazantzidis ◽  
Christos Astaras ◽  
Ioakim Vasiliadis ◽  
Eleni Makrygianni ◽  
Vassilis Ilias ◽  
...  
Keyword(s):  
Habitat Management ◽  
Weather Conditions ◽  
Abundant Species ◽  
Protected Species ◽  
Factors Affecting ◽  
Management Actions ◽  
Hunting Activity ◽  
Wintering Waterfowl ◽  
Waterfowl Hunting ◽  
The Relationship

The Evros delta is one of the most important wetlands for wintering waterfowl in Greece and the most popular among waterfowl hunters. This study addresses hunting activity and harvest while also investigating the relationship between weather conditions and hunting activity to suggest ways of improving waterfowl management. We counted wintering waterfowl and hunter numbers, and conducted hunter bag surveys during December–February over four hunting seasons. We calculated a 10-day goose and duck Preferential Shooting Index (PSI), which is the ratio of observed number of shot birds to the number of birds expected to have been shot if the birds were shot in proportion to their availability. Common Teal, Mallard and Greater White-fronted Goose were the most abundant species both in the field and in hunter bags. The mean number of hunters/day was 99.9, with each one shooting on average 2.5 birds/day. The overall waterfowl harvested accounted for 1.3% of the total waterfowl population. For geese this proportion was six times higher (8.7%), while for ducks alone and protected species was 1.2% and 1.4% respectively. Geese were shot more often than expected (PSI 6.55), while ducks and protected species were shot according to their availability (PSI 0.86 and 1.02, respectively). Wind speed, precipitation and geese number in the field were the best predictors of overall harvest and number of hunters. To reduce goose overshooting and the probability of protected species being accidentally shot, we suggest habitat management actions for the geese feeding areas and hunters’ awareness raising.

scholarly journals Development of Action Threshold to Manage Common Leaf Spot and Black Seed Disease of Strawberry Caused by Mycosphaerella fragariae

Plant Disease ◽  
2019 ◽  
Vol 103 (3) ◽  
pp. 563-570
Author(s):  
Odile Carisse ◽  
Vanessa McNealis
Keyword(s):  
Leaf Spot ◽  
Binary Data ◽  
Decision Tool ◽  
Black Seed ◽  
Action Threshold ◽  
Significant Difference ◽  
Action Thresholds ◽  
Black Seeds ◽  
Mycosphaerella Fragariae ◽  
The Relationship

The fungus Mycosphaerella fragariae is responsible for two strawberry diseases: common leaf spot (CLS) and black seed disease (BSD). In June-bearing strawberry plantings, CLS influences vigor, yield, and winter survival. During production years, BSD causes black lesions around strawberry seeds, reducing the market value of the berries. The objective of this study was to characterize the relationships between CLS and BSD and to develop action thresholds for the management of BSD. Data on the number of lesions per leaf, number of black seeds per berry, and percentage of diseased berries were collected at two experimental and six commercial sites from 2000 to 2011, corresponding to 50 farm-years. First, logistic regression was used to model the relationship between BSD occurrence in its binary data form and the number of lesions per leaf assessed at 7, 14, 21, and 28 days before 10% bloom. Second, linear regression was used to model the relationship between BSD severity, BSD incidence, and number of lesions per leaf assessed at 7, 14, 21, and 28 days before 10% bloom. Resulting action thresholds of 15, 25, or 33 lesions per leaf at 21, 14, or 7 days before 10% bloom, respectively, were compared with the recommended practice at three commercial sites in 2014, 2015, and 2016. The percentage of diseased berries was significantly (P = 0.0016; least significant difference = 7.140) higher in the sections of the fields that were not managed for BSD, with an average of 15.22% diseased berries, in comparison with 3.22 and 2.44% diseased berries in sections managed according to the recommendations and the thresholds, respectively. Overall, 40% less fungicide was used when the thresholds were applied. Hence, these thresholds can be used as an additional decision tool to optimize fungicide applications during the prebloom period.

scholarly journals Fail to Yield? An Analysis of Ambulance Crashes in Taiwan

2021 ◽  
Vol 13 (3) ◽  
pp. 1566
Author(s):  
Rong-Chang Jou ◽  
Ming-Che Chao
Keyword(s):  
Public Education ◽  
Weather Conditions ◽  
Medical Emergency ◽  
Transportation Safety ◽  
Emergency Vehicle ◽  
The Road ◽  
Mnl Model ◽  
On The Road ◽  
Crash Injuries ◽  
The Relationship

Introduction—Medical emergency vehicles help patients get to the hospital quickly. However, there were more and more ambulance crashes on the road in Taiwan during the last decade. This study investigated the characteristics of medical emergency vehicle crashes in Taiwan from January 2003 to December 2016. Methods—The ordered logit (OL) model, multinominal logit (MNL) model, and partial proportional odds (PPO) model were applied to investigate the relationship between the severity of ambulance crash injuries and its risk factors. Results—We found the various factors have different effects on the overall severity of ambulance crashes, such as ambulance drivers’ characteristics and road and weather conditions. When another car was involved in ambulance crashes, there was a disproportionate effect on the different overall severity, as found by the PPO model. Conclusions—The results showed that male ambulance drivers and car drivers who failed to yield to an ambulance had a higher risk of severe injury from ambulance crashes. Ambulance crashes are an emerging issue and need further policies and public education regarding Taiwan’s ambulance transportation safety.

scholarly journals It’s the Weather: Quantifying the Impact of Weather on Retail Sales

2021 ◽  
Author(s):  
Natalie Rose ◽  
Les Dolega
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Influential Factor ◽  
Retail Sector ◽  
Retail Sales ◽  
Weather Impact ◽  
High Street ◽  
Sector Decision ◽  
The Impact ◽  
The Relationship

AbstractThe weather is considered as an influential factor on consumer purchasing behaviours and plays a significant role in many aspects of retail sector decision making. As a result, better understanding of the magnitude and nature of the influence of variable UK weather conditions can be beneficial to many retailers and other stakeholders. This study addresses the dearth of research in this area by quantifying the relationship between different weather conditions and trading outcomes. By employing comprehensive daily sales data for a major high street retailer with over 2000 stores across England and adopting a random forest methodology, the study quantifies the influence of various weather conditions on daily retail sales. Results indicate that weather impact is greatest in the summer and spring months and that wind is consistently found to be the most influential weather condition. The top five most weather-dependent categories cover a range of different product types, with health foods emerging as the most susceptible to the weather. Also, sales from out-of-town stores show a far more complex relationship with the weather than those from traditional high street stores with the regions London and the South East experiencing the greatest levels of influence. Various implications of these findings for retail stakeholders are discussed and the scope for further research outlined.

scholarly journals Eight Simple Guidelines for Improved Understanding of Transformations and Nonlinear Effects

2021 ◽  
pp. 109442812199190
Author(s):  
Mikko Rönkkö ◽  
Eero Aalto ◽  
Henni Tenhunen ◽  
Miguel I. Aguirre-Urreta
Keyword(s):  
Generalized Linear Model ◽  
Functional Form ◽  
Nonlinear Models ◽  
Nonlinear Effects ◽  
Recent Past ◽  
Organizational Research ◽  
Common Practices ◽  
Individual Variables ◽  
The Individual ◽  
The Relationship

Transforming variables before analysis or applying a transformation as a part of a generalized linear model are common practices in organizational research. Several methodological articles addressing the topic, either directly or indirectly, have been published in the recent past. In this article, we point out a few misconceptions about transformations and propose a set of eight simple guidelines for addressing them. Our main argument is that transformations should not be chosen based on the nature or distribution of the individual variables but based on the functional form of the relationship between two or more variables that is expected from theory or discovered empirically. Building on a systematic review of six leading management journals, we point to several ways the specification and interpretation of nonlinear models can be improved.

scholarly journals On the Relationship between Intensity and Rainfall Distribution in Tropical Cyclones Making Landfall over China

2017 ◽  
Vol 56 (10) ◽  
pp. 2883-2901 ◽  
Author(s):  
Zifeng Yu ◽  
Yuqing Wang ◽  
Haiming Xu ◽  
Noel Davidson ◽  
Yandie Chen ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Rain Rate ◽  
Vertical Wind Shear ◽  
Intensity Change ◽  
Total Rainfall ◽  
Rainfall Distribution ◽  
Rain Area ◽  
Maximum Rainfall ◽  
Rain Rates ◽  
The Relationship

AbstractTRMM satellite 3B42 rainfall estimates for 133 landfalling tropical cyclones (TCs) over China during 2001–15 are used to examine the relationship between TC intensity and rainfall distribution. The rain rate of each TC is decomposed into axisymmetric and asymmetric components. The results reveal that, on average, axisymmetric rainfall is closely related to TC intensity. Stronger TCs have higher averaged peak axisymmetric rain rates, more averaged total rain, larger averaged rain areas, higher averaged rain rates, higher averaged amplitudes of the axisymmetric rainfall, and lower amplitudes of wavenumbers 1–4 relative to the total rainfall. Among different TC intensity change categories, rapidly decaying TCs show the most rapid decrease in both the total rainfall and the axisymmetric rainfall relative to the total rain. However, the maximum total rain, maximum rain area, and maximum rain rate are not absolutely dependent on TC intensity, suggesting that stronger TCs do not have systematically higher maximum rain rates than weaker storms. Results also show that the translational speed of TCs has little effect on the asymmetric rainfall distribution in landfalling TCs. The maximum rainfall of both the weaker and stronger TCs is generally located downshear to downshear left. However, when environmental vertical wind shear (VWS) is less than 5 m s−1, the asymmetric rainfall maxima are more frequently located upshear and onshore, suggesting that in weak VWS environments the coastline could have a significant effect on the rainfall asymmetry in landfalling TCs.

scholarly journals Exploring the relation between aerosol optical depth and PM<sub>2.5</sub> at Cabauw, the Netherlands

2008 ◽  
Vol 8 (5) ◽  
pp. 17939-17986 ◽  
Author(s):  
M. Schaap ◽  
A. Apituley ◽  
R. M. A. Timmermans ◽  
R. B. A. Koelemeijer ◽  
G. de Leeuw
Keyword(s):  
The Netherlands ◽  
Ground Level ◽  
Weather Conditions ◽  
Fair Weather ◽  
Modis Aod ◽  
Data Points ◽  
Set Up ◽  
The Relationship ◽  
Lidar Observations ◽  
Pm2.5 Concentration

Abstract. To acquire daily estimates of PM2.5 distributions based on satellite data one depends critically on an established relation between AOD and ground level PM2.5. In this study we aimed to experimentally establish the AOD-PM2.5 relationship for the Netherlands. For that purpose an experiment was set-up at the AERONET site Cabauw. The average PM2.5 concentration during this ten month study was 18 μg/m3, which confirms that the Netherlands are characterised by a high PM burden. A first inspection of the AERONET level 1.5 (L1.5) AOD and PM2.5 data at Cabauw showed a low correlation between the two properties. However, after screening for cloud contamination in the AERONET L1.5 data, the correlation improved substantially. When also constraining the dataset to data points acquired around noon, the correlation between AOD and PM2.5 amounted to R2=0.6 for situations with fair weather. This indicates that AOD data contain information about the temporal evolution of PM2.5. We had used LIDAR observations to detect residual cloud contamination in the AERONET L1.5 data. Comparison of our cloud-screed L1.5 with AERONET L2 data that became available near the end of the study showed favorable agreement. The final relation found for Cabauw is PM2.5=124.5*AOD–0.34 (with PM2.5 in μg/m3) and is valid for fair weather conditions. The relationship determined between MODIS AOD and ground level PM2.5 at Cabauw is very similar to that based on the much larger dataset from the sun photometer data, after correcting for a systematic overestimation of the MODIS data of 0.05. We applied the relationship to a MODIS composite map to assess the PM2.5 distribution over the Netherlands. Spatial dependent systematic errors in the MODIS AOD, probably related to variability in surface reflectance, hamper a meaningful analysis of the spatial distribution of PM2.5 using AOD data at the scale of the Netherlands.

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