scholarly journals Comparison of Three Fungicide Spray Advisories for Lettuce Downy Mildew

Plant Disease ◽  
2001 ◽  
Vol 85 (8) ◽  
pp. 895-900 ◽  
Author(s):  
B. M. Wu ◽  
K. V. Subbarao ◽  
A. H. C. van Bruggen ◽  
S. T. Koike
Keyword(s):  
Downy Mildew ◽  
Drip Irrigation ◽  
Leaf Wetness ◽  
Lettuce Downy Mildew ◽  
Advisory System ◽  
System 2 ◽  
Forecasting System ◽  
Low Incidence ◽  
System 1 ◽  
First Time

Lettuce growers in coastal California have relied mainly on protective fungicide sprays to control downy mildew. Thus, timing of sprays before infection is critical for optimal results. A leaf-wetness-driven, infection-based advisory system, previously developed, did not always perform satisfactorily. In this study, the advisory system was modified by incorporating a pathogen survival component (system 1) or both survival and sporulation components (system 2). These systems were then evaluated in commercial lettuce fields in coastal California during 1996-1998. Three or four treatments were carried out in each field: (i) no spray; (ii) sprays as scheduled by the growers; (iii) sprays following modified system 1; and (iv) sprays following the original advisory system (1996) or modified system 2 (1998). Downy mildew incidence was evaluated every 2 to 9 days. In fields with drip irrigation, the number of fungicide applications was reduced by one or two regardless of the advisory system used compared to the grower's calendar-based schedule, although one unnecessary spray was recommended in 1996 at Soledad and 1997 at Salinas. Under all three systems, disease levels were low (incidence <25% and about 1 lesion per plant) for fields with drip irrigation, but not for fields with sprinklers (incidence up to 100% and 5 to 10 lesions per plant). For the first time, we established that survival and sporulation components are not needed for a lettuce downy mildew forecasting system. Instead, a threshold with a shorter period of morning leaf wetness and high temperatures were found to have potential for improving forecasting efficiency.

Validation of weather and leaf wetness forecasts for a lettuce downy mildew warning system

2001 ◽  
Vol 23 (4) ◽  
pp. 371-383 ◽  
Author(s):  
B.M. Wu ◽  
K.V. Subbarao ◽  
A.H.C.van Bruggen ◽  
G.G.H. Pennings
Keyword(s):  
Downy Mildew ◽  
Warning System ◽  
Leaf Wetness ◽  
Lettuce Downy Mildew

scholarly journals Analyses of the Relationships Between Lettuce Downy Mildew and Weather Variables Using Geographic Information System Techniques

Plant Disease ◽  
2005 ◽  
Vol 89 (1) ◽  
pp. 90-96 ◽  
Author(s):  
B. M. Wu ◽  
K. V. Subbarao ◽  
A. H. C. van Bruggen
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Downy Mildew ◽  
Disease Incidence ◽  
Geographic Information ◽  
Leaf Wetness ◽  
Weather Variables ◽  
Leaf Wetness Duration ◽  
Lettuce Downy Mildew ◽  
Weather Stations

Previous studies in coastal California suggested that morning leaf wetness duration and temperature immediately after the prolonged leaf wetness period affect infection of lettuce by the downy mildew pathogen, Bremia lactucae. In this study, spatial analysis tools in a geographic information system were used to interpolate disease assessment data and then relate them to weather variables measured in 1995 and 1997 at weather stations in the Salinas Valley. Among the variables monitored at these weather stations, midday temperature (10:00 A.M. to 2:00 P.M.) was related most strongly to the interpolated downy mildew incidence in a circular area (radius = 5 km) around each station (r = 0.52, P < 0.0001); the higher the midday temperature, the lower the disease incidence. High humidity and prolonged morning leaf wetness duration also were associated with high downy mildew incidence. Cluster analysis resulted in distinct regions with different midday temperatures, which overlapped well (92.2% of the total area) with regions distinguished in previous cluster analyses of downy mildew incidence. Clusters of morning relative humidity showed similar patterns, although they overlapped less well with clusters of disease incidence. These results confirmed that midday temperature is an important determining factor for lettuce downy mildew, and its effects should be incorporated into a disease warning system for coastal California. Cluster analyses based on the effects of temperature have great potential for use in regional downy mildew risk assessment.

Peronosporales of Skadovsky Zvenigorod Biological Station (Moscow Region)

2018 ◽  
Vol 52 (1) ◽  
pp. 91-100
Author(s):  
E. Yu. Blagoveshchenskaya
Keyword(s):  
Downy Mildew ◽  
European Part ◽  
Moscow Region ◽  
State University ◽  
Biological Station ◽  
Annotated List ◽  
European Part Of Russia ◽  
First Time ◽  
Moscow State University

The paper provides the results of seven-year study of downy mildew on Skadovsky Zvenigorod Biological Station of Moscow State University (ZBS MSU, Moscow Region). A total of 29 species of Peronosporales (Oomycota) were revealed during the study. An annotated list of species is presented, among them Peronospora anemones is recorded for the first time for Russia, P. chelidonii and P. stachydis are new for the European part of Russia, 8 species are new for the Moscow Region.

scholarly journals Milk Production, Body Weight, Body Condition Score, Activity, and Rumination of Organic Dairy Cattle Grazing Two Different Pasture Systems Incorporating Cool- and Warm-Season Forages

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 264
Author(s):  
Kathryn E. Ritz ◽  
Bradley J. Heins ◽  
Roger D. Moon ◽  
Craig C. Sheaffer ◽  
Sharon L. Weyers
Keyword(s):  
Body Weight ◽  
Milk Production ◽  
Body Condition Score ◽  
Warm Season ◽  
Cool Season ◽  
Organic Dairy ◽  
Condition Score ◽  
Annual Grasses ◽  
System 2 ◽  
System 1

Organic dairy cows were used to evaluate the effect of two organic pasture production systems (temperate grass species and warm-season annual grasses and cool-season annuals compared with temperate grasses only) across two grazing seasons (May to October of 2014 and 2015) on milk production, milk components (fat, protein, milk urea nitrogen (MUN), somatic cell score (SCS)), body weight, body condition score (BCS), and activity and rumination (min/day). Cows were assigned to two pasture systems across the grazing season at an organic research dairy in Morris, Minnesota. Pasture System 1 was cool-season perennials (CSP) and Pasture System 2 was a combination of System 1 and warm-season grasses and cool-season annuals. System 1 and System 2 cows had similar milk production (14.7 and 14.8 kg d−1), fat percentage (3.92% vs. 3.80%), protein percentage (3.21% vs. 3.17%), MUN (12.5 and 11.5 mg dL−1), and SCS (4.05 and 4.07), respectively. Cows in System 1 had greater daily rumination (530 min/day) compared to cows in System 2 (470 min/day). In summary, warm-season annual grasses may be incorporated into grazing systems for pastured dairy cattle.

scholarly journals Performance of deep learning technology for evaluation of positioning quality in periapical radiography of the maxillary canine

2021 ◽  
Author(s):  
Mizuho Mori ◽  
Yoshiko Ariji ◽  
Motoki Fukuda ◽  
Tomoya Kitano ◽  
Takuma Funakoshi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Characteristic Curve ◽  
Classification Performance ◽  
Learning Systems ◽  
Learning Technology ◽  
System 2 ◽  
Potential Benefits ◽  
System 1 ◽  
Periapical Radiography

Abstract Objectives The aim of the present study was to create and test an automatic system for assessing the technical quality of positioning in periapical radiography of the maxillary canines using deep learning classification and segmentation techniques. Methods We created and tested two deep learning systems using 500 periapical radiographs (250 each of good- and bad-quality images). We assigned 350, 70, and 80 images as the training, validation, and test datasets, respectively. The learning model of system 1 was created with only the classification process, whereas system 2 consisted of both the segmentation and classification models. In each model, 500 epochs of training were performed using AlexNet and U-net for classification and segmentation, respectively. The segmentation results were evaluated by the intersection over union method, with values of 0.6 or more considered as success. The classification results were compared between the two systems. Results The segmentation performance of system 2 was recall, precision, and F measure of 0.937, 0.961, and 0.949, respectively. System 2 showed better classification performance values than those obtained by system 1. The area under the receiver operating characteristic curve values differed significantly between system 1 (0.649) and system 2 (0.927). Conclusions The deep learning systems we created appeared to have potential benefits in evaluation of the technical positioning quality of periapical radiographs through the use of segmentation and classification functions.

scholarly journals Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić
Keyword(s):  
Downy Mildew ◽  
Fire Blight ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Plasmopara Viticola ◽  
Forecasting System ◽  
Nwp Model ◽  
The Impact

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

A New Class of Oxide Superconductor (Nd, Ce, Sr)2CuO4

1989 ◽  
Vol 156 ◽  
Author(s):  
E. Takayama-Muromachi
Keyword(s):  
Crystal Structure ◽  
Crystal Chemistry ◽  
Superconducting Phase ◽  
Type Structure ◽  
Oxide Superconductor ◽  
New Class ◽  
System 2 ◽  
New Type ◽  
System 1 ◽  
Tetragonal Cell

ABSTRACTSince the discovery of the high-Tc superconductor in the La-Ba-Cu-O system [1], a great deal of experimental and theoretical effort have been made to clarify the nature of the Cu-based oxides. In order to elucidate mechanism of the high-Tc superconductivity, discovery of a new type of superconductor is no doubt of great importance. Recently, Akimitsu et al. found a new oxide superconductor in the Nd-Ce-Sr-Cu-O system [2]. Soon after their discovery, the superconducting phase was isolated and identified [3]. It has a tetragonal cell with space group P4/nmm and has a structure closely related to but different from the K2NiF4− or T'-Nd2CuO4− -type structure. Although, Tc of the Nd-Ce-Sr-Cu oxide is not so high (ca. 20 K) compared with the 1–2–3 or Bi(Tl)-based superconductors, it has aroused interest widely due to a very simple crystal structure. In this article, I will discuss superconductivity and crystal chemistry of the Nd-Ce-Sr-Cu oxide. Also, various compounds isostructural to it will be presented.

scholarly journals Three levels of naturalistic knowledge

2019 ◽  
Author(s):  
Andreas Stephens
Keyword(s):  
Semantic Memory ◽  
Conceptual Knowledge ◽  
Procedural Knowledge ◽  
Dual Process ◽  
Long Term Memory ◽  
Cognitive Ethology ◽  
System 2 ◽  
System 1 ◽  
Level Of Analysis

A recent naturalistic epistemological account suggests that there are three nested basic forms of knowledge: procedural knowledge-how, conceptual knowledge-what, and propositional knowledge-that. These three knowledge-forms are grounded in cognitive neuroscience and are mapped to procedural, semantic, and episodic long-term memory respectively. This article investigates and integrates the neuroscientifically grounded account with knowledge-accounts from cognitive ethology and cognitive psychology. It is found that procedural and semantic memory, on a neuroscientific level of analysis, matches an ethological reliabilist account. This formation also matches System 1 from dual process theory on a psychological level, whereas the addition of episodic memory, on the neuroscientific level of analysis, can account for System 2 on the psychological level. It is furthermore argued that semantic memory (conceptual knowledge-what) and the cognitive ability of categorization are linked to each other, and that they can be fruitfully modeled within a conceptual spaces framework.

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