scholarly journals Minimizing Crop Damage Through Understanding Relationships Between Pyrethrum Phenology and Ray Blight Disease Severity

Plant Disease ◽  
2013 ◽  
Vol 97 (11) ◽  
pp. 1431-1437 ◽  
Author(s):  
Sarah J. Pethybridge ◽  
David H. Gent ◽  
Tim Groom ◽  
Frank S. Hay
Keyword(s):  
Disease Management ◽  
Prediction Error ◽  
Stem Elongation ◽  
Crop Damage ◽  
Economic Losses ◽  
Logistic Growth ◽  
Degree Days ◽  
Degree Day ◽  
Ray Blight ◽  
Mean Prediction Error

The most damaging foliar disease of pyrethrum in Australia is ray blight caused by Stagonosporopsis tanaceti. The probability of growers incurring economic losses caused by this disease has been substantially reduced by the implementation of a prophylactically applied spring fungicide program. This has been traditionally initiated when 50% of the stems have reached between 5 and 10 cm in height. Data collected on the emergence of stems from semidormant plants over late winter from 27 fields across northern Tasmania from 2009 to 2011 were used to develop a degree-day model to assist with initiation of the fungicide program. Temporal changes in cumulative proportion of plants with elongated stems were well described by a logistic growth model (R2 ≥ 0.97 across all fields). These models were used to calculate the number of days until 50% of the sampling units had at least one elongated stem for the calculation of simple degree-days, assuming a nominal biofix date of the austral winter solstice. The median date for 50% stem elongation was estimated as 30 August in these data sets. Mean error and root mean square error of degree-day models were minimized when a base of 0°C was selected. Mixed-model analysis found prediction errors to be significantly affected by geographic region, requiring the use of scalar correction factors for specific production regions. In the Western region, 50% stem emergence was predicted at 590.3 degree-days (mean prediction error = 0.7 days), compared with 644.6 (mean prediction error = 7.7 days) in the Coastal region and 684.7 (mean prediction error = 0.7 days) degree-days in the Inland region. The importance of fungicide timing for initiation of the spring disease management program in minimizing losses (expressed as percent disease control in October) was also quantified. This relationship was best explained by a split-line regression with a significant break-point of 513.8 degree-days, which corresponded to 10.7% of sampling units with elongated stems. Overall, this research indicated that disease management may be improved by applying the first fungicide of the program substantially earlier in phenological development of the stems than currently recommended.

scholarly journals Does Every Calculation Formula Fit for All Types of Intraocular Lenses? Optimization of Constants for Tecnis ZA9003 and ZCB00 Is Necessary

Medicina ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 319
Author(s):  
Ivajlo Popov ◽  
Veronika Popova ◽  
Juraj Sekac ◽  
Vladimir Krasnik
Keyword(s):  
Prediction Error ◽  
Poor Performance ◽  
Intraocular Lenses ◽  
Power Calculation ◽  
Universal Formula ◽  
Aspheric Iol ◽  
Different Types ◽  
The Mean ◽  
Clinically Significant ◽  
Mean Prediction Error

Background and Objectives: To evaluate the performance of intraocular lenses (IOLs) using power calculation formulas on different types of IOL. Materials and Methods: 120 eyes and four IOL types (BioLine Yellow Accurate Aspheric IOL (i-Medical), TECNIS ZCB00, TECNIS ZA9003 (Johnson & Johnson) (3-piece IOL) and Softec HD (Lenstec)) were analyzed. The performance of Haigis, Barret Universal II and SKR-II formulas were compared between IOL types. The mean prediction error (ME) and mean absolute prediction error (MAE) were analyzed. Results: The overall percentage of eyes predicted within ±0.25 diopters (D) was 40.8% for Barret; 39.2% Haigis and 31.7% for SRK-II. Barret and Haigis had a significantly lower MAE than SRK-II (p < 0.05). The results differed among IOL types. The largest portion of eyes predicted within ±0.25 D was with the Barret formula in ZCB00 (33.3%) and ZA9003 (43.3%). Haigis was the most accurate in Softec HD (50%) and SRK-II in Biolline Yellow IOL (50%). ZCB00 showed a clinically significant hypermetropic ME compared to other IOLs. Conclusions: In general, Barret formulas had the best performance as a universal formula. However, the formula should be chosen according to the type of IOL in order to obtain the best results. Constant optimizations are necessary for the Tecnis IOL ZCB00 and ZA9003, as all of the analyzed formulas achieved a clinically significant poor performance in this type of IOL. ZCB00 also showed a hypermetropic shift in ME in all the formulas.

scholarly journals Pengaruh Suhu terhadap Perkembangan Pradewasa Parasitoid Eriborus argenteopilosus Cameron (Hymenoptera: Ichneumonidae)

2012 ◽  
Vol 13 (3) ◽  
pp. 250
Author(s):  
Novri Nelly ◽  
Trimurti Habazar ◽  
Rahmat Syahni ◽  
Damayanti Buchori
Keyword(s):  
Survival Rate ◽  
Temperature Effect ◽  
Development Time ◽  
Degree Days ◽  
Degree Day ◽  
Adult Parasitoid ◽  
Different Temperatures ◽  
Lepidoptera Pyralidae

Temperature effect on development time of the preadult parasitoid Eriborus argenteopilosus Cameron(Hymenoptera: Ichneumonidae) were studied to know development time, degree days and survival rate.Crocidolomia pavonana (Fabricius)(Lepidoptera: Pyralidae) larvae was exposed to E. argenteopilosus female andreared at four different temperatures i.e 160C, 200C, 250C and 300C. Data were analyzed using anova and linearregression to calculate degree day. At 200C E. argenteopilosus showed the highest degree day and survival rate(18.67 %), while at 300C nothing adult parasitoid emergenced. Degree day to development time of parasitoid attemperature 200C i.e fase egg-adult: 300.05; egg-pupae 173.35; pupae-adult 171.

Accuracy of predicting the vancomycin concentration in Japanese cancer patients by the Sawchuk–Zaske method or Bayesian method

2019 ◽  
Vol 26 (3) ◽  
pp. 543-548
Author(s):  
Toshihisa Nakashima ◽  
Takayuki Ohno ◽  
Keiichi Koido ◽  
Hironobu Hashimoto ◽  
Hiroyuki Terakado
Keyword(s):  
Cancer Patients ◽  
Prediction Error ◽  
Bayesian Method ◽  
Predictive Accuracy ◽  
Pharmacokinetic Parameters ◽  
Population Pharmacokinetic ◽  
Squared Prediction Error ◽  
Trough Concentrations ◽  
The Mean ◽  
Mean Prediction Error

Background In cancer patients treated with vancomycin, therapeutic drug monitoring is currently performed by the Bayesian method that involves estimating individual pharmacokinetics from population pharmacokinetic parameters and trough concentrations rather than the Sawchuk–Zaske method using peak and trough concentrations. Although the presence of malignancy influences the pharmacokinetic parameters of vancomycin, it is unclear whether cancer patients were included in the Japanese patient populations employed to estimate population pharmacokinetic parameters for this drug. The difference of predictive accuracy between the Sawchuk–Zaske and Bayesian methods in Japanese cancer patients is not completely understood. Objective To retrospectively compare the accuracy of predicting vancomycin concentrations between the Sawchuk–Zaske method and the Bayesian method in Japanese cancer patients. Methods Using data from 48 patients with various malignancies, the predictive accuracy (bias) and precision of the two methods were assessed by calculating the mean prediction error, the mean absolute prediction error, and the root mean squared prediction error. Results Prediction of the trough and peak vancomycin concentrations by the Sawchuk–Zaske method and the peak concentration by the Bayesian method showed a bias toward low values according to the mean prediction error. However, there were no significant differences between the two methods with regard to the changes of the mean prediction error, mean absolute prediction error, and root mean squared prediction error. Conclusion The Sawchuk–Zaske method and Bayesian method showed similar accuracy for predicting vancomycin concentrations in Japanese cancer patients.

scholarly journals Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5922
Author(s):  
Yu Zhang ◽  
Xiaohui Song ◽  
Yong Li ◽  
Zilong Zeng ◽  
Chenchen Yong ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Error ◽  
Reactive Power ◽  
Distribution Network ◽  
Constant Current ◽  
Economic Losses ◽  
Time Varying ◽  
Two Stage ◽  
Active Distribution Network ◽  
Active And Reactive Power

A high proportion of renewable energy connected to the power grid has caused power quality problems. Voltage-sensitive loads are extremely susceptible to voltage fluctuations, causing power system safety issues and economic losses. Considering the uncertainty factor and the time-varying characteristic, a linearized random ZIP model (constant impedance (Z), constant current (I), and constant power (P)) with time-varying characteristics was proposed. In order to improve the voltage quality of the voltage-sensitive loads in the day-here stage in an active distribution network (ADN), a linearized two-stage active and reactive power coordinated stochastic optimization model was established. The day-ahead active and reactive power coordination optimization was to smooth the large voltage fluctuation and develop a reserve plan to eliminate the unbalanced power caused by the prediction error in the day-here optimization. In the day-here real-time redispatch, the voltage was further improved by the continuous reactive power compensation device. Finally, the simulation results on the IEEE-33 bus system showed that the control strategy could better eliminate the unbalanced power caused by the prediction error and obviously improve the voltage of sensitive loads in the real-time stage on the premise of maintaining economic optimality.

DEGREE-DAY RELATIONSHIPS TO THE DEVELOPMENT OF LITHOCOLLETIS BLANCARDELLA (LEPIDOPTERA: GRACILLARIIDAE) AND ITS PARASITE APANTELES ORNIGIS (HYMENOPTERA: BRACONIDAE)

1979 ◽  
Vol 111 (10) ◽  
pp. 1177-1184 ◽  
Author(s):  
E. F. Johnson ◽  
R. Trottier ◽  
J. E. Laing
Keyword(s):  
Pest Management ◽  
Natural Enemy ◽  
Field Studies ◽  
Management Programme ◽  
Seasonal Development ◽  
Daily Maximum ◽  
Degree Days ◽  
Degree Day ◽  
Temperature Thresholds ◽  
Stevenson Screen

AbstractDegree-day relationships in the development of Lithocolletis blancardella (Fab.) and Apanteles ornigis Weed, its major parasite, were established from laboratory and field studies in Ontario apple orchards during 1973, 1974, and 1975. Under constant laboratory conditions, temperature thresholds for development of overwintering pupae were estimated by three methods, and found to be 6.3°, 6.7°, and 5.7°C for L. blancardella, and 10.4°, 10.4°, and 11.3°C for A. ornigis. Degree-day accumulations in the field were calculated by two methods using daily maximum and minimum temperatures recorded from the pupal habitat and a Stevenson screen. Degree-days in the pupal habitat accumulated from 1 January, above 5.7°C for L. blancardella and 11.3°C for A. ornigis were more accurate than Stevenson screen degree-day accumulations for predicting first emergence; however, after emergence, seasonal development was best related to Stevenson screen degree-days accumulated from 1 April, above 6.7°C for L. blancardella and 10.4°C for A. ornigis. This study shows that degree-day relationships can be used in an apple pest management programme to optimize timing of insecticide applications against L. blancardella and preserve A. ornigis, its major natural enemy.

Effect of weather station logging interval on the precision of degree-day estimates

1995 ◽  
Vol 35 (6) ◽  
pp. 795 ◽  
Author(s):  
DM Watson ◽  
GAC Beattie
Keyword(s):  
Weather Station ◽  
Data Logging ◽  
Degree Days ◽  
Degree Day ◽  
The Relationship

The relationship between data-logging intervals and degree-day estimates was examined to determine the longest interval giving equivalent information to estimates based on 12-min intervals and, so, the most efficient interval for estimation of degree-days

scholarly journals External Validation of the Dutch SOURCE Survival Prediction Model in Belgian Metastatic Oesophageal and Gastric Cancer Patients

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 834
Author(s):  
J.J. van Kleef ◽  
H.G. van den Boorn ◽  
R.H.A. Verhoeven ◽  
K. Vanschoenbeek ◽  
A. Abu-Hanna ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prediction Model ◽  
Oesophageal Cancer ◽  
Prediction Error ◽  
Prediction Models ◽  
Mean Difference ◽  
Survival Prediction ◽  
Cancer Model ◽  
The Mean ◽  
Mean Prediction Error

The SOURCE prediction model predicts individualised survival conditional on various treatments for patients with metastatic oesophageal or gastric cancer. The aim of this study was to validate SOURCE in an external cohort from the Belgian Cancer Registry. Data of Belgian patients diagnosed with metastatic disease between 2004 and 2014 were extracted (n = 4097). Model calibration and discrimination (c-indices) were determined. A total of 2514 patients with oesophageal cancer and 1583 patients with gastric cancer with a median survival of 7.7 and 5.4 months, respectively, were included. The oesophageal cancer model showed poor calibration (intercept: 0.30, slope: 0.42) with an absolute mean prediction error of 14.6%. The mean difference between predicted and observed survival was −2.6%. The concordance index (c-index) of the oesophageal model was 0.64. The gastric cancer model showed good calibration (intercept: 0.02, slope: 0.91) with an absolute mean prediction error of 2.5%. The mean difference between predicted and observed survival was 2.0%. The c-index of the gastric cancer model was 0.66. The SOURCE gastric cancer model was well calibrated and had a similar performance in the Belgian cohort compared with the Dutch internal validation. However, the oesophageal cancer model had not. Our findings underscore the importance of evaluating the performance of prediction models in other populations.

Roaming Dogs

2015 ◽  
pp. 112-134
Author(s):  
Arnold Arluke ◽  
Kate Atema
Keyword(s):  
Public Health ◽  
Quality Of Life ◽  
Disease Management ◽  
Social Ties ◽  
Population Management ◽  
Economic Losses ◽  
Community Impact ◽  
Disadvantaged Communities ◽  
Livestock Predation

This chapter describes an original and much-needed approach to understanding worldwide efforts among disadvantaged communities to deal with roaming and unhealthy dogs. Rather than focus on the ways these efforts impact dogs and public health, as is typical of such interventions, we explore how people, too, are socially, psychologically, and economically affected by the dogs. More specifically, we examine the community impact that roaming or unhealthy dog populations can have, including negative or indifferent human-canine interactions; decreased quality of life because of dog nuisances, lack of safety, and disturbing encounters with injured, dead, or suffering dogs; weakened or fractured social ties; and economic losses from reduced tourism, livestock predation, and disease management. Lastly, we review how dog population management can have residual communitywide impact.

USE OF STANDARD TEMPERATURE THRESHOLDS AND PHENOLOGICAL PREDICTION FOR THE EUROPEAN CORN BORER (OSTRINIA NUBILALIS HÜBNER) IN ALBERTA

1990 ◽  
Vol 122 (6) ◽  
pp. 1247-1258 ◽  
Author(s):  
Douglas H. Kelker ◽  
Dennis A. Lee ◽  
John R. Spence
Keyword(s):  
Ostrinia Nubilalis ◽  
European Corn Borer ◽  
Temporal Distribution ◽  
Sampling Effort ◽  
Degree Days ◽  
Corn Borer ◽  
Degree Day ◽  
Temperature Thresholds ◽  
Southern Alberta ◽  
The Standard Model

AbstractA degree-day model was developed for Alberta populations of Ostrinia nubilalis Hübner. Starting with overwintered fifth-instar larvae, the model calculates the temporal distribution of first- and second-instar larvae which are the stages most vulnerable to chemical suppression. Predictions from three alternative models were compared against field data from southern Alberta. Use of a standard 10°C growth threshold to calculate physiological time scales allowed predictions as accurate as those obtained using either a pooled threshold (11.4°C) calculated specifically from Alberta populations, or a model using two thresholds (12.3°C for fifth-instar larvae to adult and 10.2°C for eggs to second-instar larvae) that incorporated significant differences in growth characteristics observed among life stages. We conclude that standard thresholds are sufficient for degree-day models for northern populations of O. nubilalis. The standard model (t0 = 10°C) predicts that moth emergence will peak at ca. 145 degree-days after median pupation, and that numbers of eggs, and first- and second-instar larvae should peak at 200, 310, and 450 degree-days, respectively. Model predictions can be used to time sampling effort in support of management decisions.

Distribution and Potential Spread of Japanese Knotweed (Polygonum cuspidatum) in Canada Relative to Climatic Thresholds

2010 ◽  
Vol 3 (1) ◽  
pp. 32-39 ◽  
Author(s):  
Robert S. Bourchier ◽  
Brian H. Van Hezewijk
Keyword(s):  
British Columbia ◽  
Minimum Temperature ◽  
Annual Precipitation ◽  
Suitable Habitat ◽  
Base Temperature ◽  
Japanese Knotweed ◽  
Degree Days ◽  
Southern Ontario ◽  
Degree Day ◽  
Daily Weather Data

AbstractJapanese knotweed (JK) is one of the most aggressive invasive plants known in the U.K., where its biology has been well-studied. It was introduced into Canada around 1900, but only recently has it become a serious concern in the province of British Columbia (BC). Climatic conditions, including annual degree days and mean-annual minimum temperatures at knotweed sites in British Columbia were modeled in BioSIM, using weather normals and long-term daily weather data, and compared to published thresholds (degree day = 2,505 DD, minimum temperature = −30.2 C, base temperature 0 C). The degree-day threshold was more limiting to JK in British Columbia than mean-minimum temperature (12.3% of province habitat was suitable for JK based on degree days compared with 26% for mean-minimum temperature). A new annual-precipitation threshold of 735 mm/year based on 95% of known knotweed sites in BC was identified. The best-fit logistic regression model included degree days and annual precipitation and predicted knotweed presence/absence with over 97% efficiency. Existing knotweed sites occupy just over half of the suitable habitat in BC, indicating there are still significant areas to be invaded. The limiting threshold for knotweed was reversed in Southern Ontario with between 35 to 53% of the habitat suitable based on minimum temperatures, whereas degree-day accumulations and annual precipitation were not limiting. Warmer temperatures from 2000 to 2008 resulted in an increase to 53% of the habitat in Southern Ontario being suitable for knotweed, compared to 35% when 1971 to 2000 weather normals were used. Different climatic thresholds among provinces might result in selection for different invasive knotweed genotypes. This could influence the success of biological control agents because of differential host suitability of knotweed genotypes. Habitat suitability maps generated will enable better targeting of knotweed surveys based on the risk of knotweed establishment.

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