scholarly journals Control of powdery mildew (Sphaerotheca pannosa var rosae) on rose (Rosa L sp) using anhydrous milk fat and soybean oil emulsions

2011 ◽  
Vol 64 ◽  
pp. 195-200 ◽  
Author(s):  
A. Ah Chee ◽  
K.V. Wurms ◽  
M. George
Keyword(s):  
Powdery Mildew ◽  
Soybean Oil ◽  
Leaf Area ◽  
Milk Fat ◽  
Anhydrous Milk Fat ◽  
Horticultural Crops ◽  
Severity Rating ◽  
Wide Range ◽  
Oil Emulsions ◽  
Sphaerotheca Pannosa

Powdery mildew (PM) is a serious fungal disease of a wide range of horticultural crops and can adversely affect crop yield and quality Anhydrous milk fat (AMF) and soybean oil (SBO) emulsions were evaluated for control of PM (Sphaerotheca pannosa var rosae) on potted rose plants (Rosa L sp Splendid Surprise and Sahara) maintained in a controlled environment Foliage was sprayed weekly with AMF (07 w/v) SBO (2 w/v) fungicide (Supershield 1 v/v) water or left unsprayed PM infection increased to 100 leaf area in water and unsprayed control plants over 6 weeks The fungicide reduced infection to a severity rating of 5 (>40 leaf area infection) The AMF and SBO treatments gave significantly better disease control (P

scholarly journals Control of powdery mildew (Podosphaera leucotricha) on apple seedlings using anhydrous milk fat and soybean oil emulsions

2011 ◽  
Vol 64 ◽  
pp. 201-208 ◽  
Author(s):  
K.V. Wurms ◽  
A. Ah Chee
Keyword(s):  
Powdery Mildew ◽  
Soybean Oil ◽  
Milk Fat ◽  
Apple Cultivar ◽  
Podosphaera Leucotricha ◽  
Anhydrous Milk Fat ◽  
Oil Emulsions

Powdery mildew (PM) is one of the most serious global diseases of apples roses cucurbits grapes and cereals The potential of anhydrous milk fat (AMF) and soybean oil (SBO) formulations to control apple PM (caused by Podosphaera leucotricha) on the apple cultivar Royal Gala was investigated Potted seedlings in a glasshouse were left unsprayed or subjected to weekly sprays of AMF SBO fungicide (sulphur as Kumulus DF) or water During 67 weeks of treatment the AMF and SBO formulations significantly reduced PM to

scholarly journals Control of powdery mildew on glasshousegrown roses and tomatoes in the Netherlands using anhydrous milk fat and soybean oil emulsions

2015 ◽  
Vol 68 ◽  
pp. 380-388 ◽  
Author(s):  
K.V. Wurms ◽  
J.D. Hofland-Zijlstra
Keyword(s):  
Powdery Mildew ◽  
The Netherlands ◽  
Soybean Oil ◽  
Milk Fat ◽  
Anhydrous Milk Fat ◽  
Oil Emulsions ◽  
Serious Disease

Powdery mildew (PM) is a very serious disease affecting glasshousegrown roses and tomatoes in the Netherlands Control is limited because of resistance to existing fungicides Anhydrous milk fat (AMF) and soybean oil (SBO) emulsions were evaluated for control of PM in roses and tomatoes Both AMF (14 g/litre) and SBO (14 g/litre) provided powdery mildew control on rose leaves and blooms that was significantly better (P

scholarly journals Product formulation is crucial to the success of lipid-based bio-fungicides

2018 ◽  
Vol 71 ◽  
pp. 272-284 ◽  
Author(s):  
Kirstin Wurms ◽  
Annette Ah Chee
Keyword(s):  
Powdery Mildew ◽  
Disease Control ◽  
Milk Fat ◽  
Emulsion Stability ◽  
Control Efficacy ◽  
Anhydrous Milk Fat ◽  
Polyglycerol Ester ◽  
Product Formulation ◽  
Fat Globules ◽  
Best Disease

Powdery mildew is a major cause of damage to squash plants. Anhydrous milk fat (AMF) or soybean oil (SBO) may be effective at treating this disease but these active ingredients must be mixed with an emulsifier to enable even distribution and suspension of fat globules, and an antioxidant to prevent rancidity. The overall formulation may affect disease control efficacy, leaf health and product stability. The effect of different emulsifiers and antioxidants on emulsion stability, odour and shelf-life of AMF and SBO bio-fungicides was tested in laboratory assays, and on powdery mildew disease control efficacy and leaf health on glasshouse-grown squash plants. Both AMF and SBO formulations including a polyglycerol ester emulsifier (Grindsted® PGE 20 Veg) resulted in the best emulsion stability, disease control and leaf health. None of the antioxidants tested significantly affected on disease control efficacy in AMF formulations, but SBO formulations containing vitamin E as the antioxidant provided the best disease control efficacy and emulsion stability.

scholarly journals Physicochemical characteristics of anhydrous milk fat mixed with fully hydrogenated soybean oil

2020 ◽  
Vol 132 ◽  
pp. 109038
Author(s):  
Maria Isabel Landim Neves ◽  
Mayara de Souza Queirós ◽  
Rodolfo Lázaro Soares Viriato ◽  
Ana Paula Badan Ribeiro ◽  
Mirna Lúcia Gigante
Keyword(s):  
Soybean Oil ◽  
Milk Fat ◽  
Physicochemical Characteristics ◽  
Anhydrous Milk Fat ◽  
Hydrogenated Soybean Oil

Anhydrous milk fat blended with fully hydrogenated soybean oil as lipid microparticles: Characterization, stability, and trends for application

LWT ◽  
2021 ◽  
pp. 112276
Author(s):  
Maria Isabel Landim Neves ◽  
Mayara de Souza Queirós ◽  
Rodolfo Lázaro Soares Viriato ◽  
Ana Paula Badan Ribeiro ◽  
Mirna Lúcia Gigante
Keyword(s):  
Soybean Oil ◽  
Milk Fat ◽  
Anhydrous Milk Fat ◽  
Lipid Microparticles ◽  
Hydrogenated Soybean Oil

scholarly journals Lipid-based bio-fungicides for control of powdery mildew in cucurbits

2018 ◽  
Vol 71 ◽  
pp. 262-271 ◽  
Author(s):  
Annette Ah Chee ◽  
Maureen George ◽  
Maryam Alavi ◽  
Kirstin Wurms
Keyword(s):  
Powdery Mildew ◽  
Milk Fat ◽  
Plant Health ◽  
Milk Products ◽  
Animal Fats ◽  
Organic Systems ◽  
Wide Range ◽  
New Generation ◽  
Future Work ◽  
Demethylation Inhibitor

Powdery mildew (PM) infection of cucurbits is a major problem facing commercial New Zealand growers. Resistance to demethylation inhibitor fungicides is widespread so, there is a demand for new-generation bio-fungicides that can provide durable control alternatives in both conventional and organic systems. A wide range of milk products, plant and animal fats/oils, and natural plant elicitors were tested for their ability to control PM on squash and zucchini plants in a series of four glasshouse trials. The most promising product tested was anhydrous milk fat (AMF), in formulation with an emulsifier (Alanate 191™ or Panodan® AL10), an antioxidant (Grindox 122™) and/or other products (Synertrol Horti oil). These treatments were as effective as commercial fungicides in controlling PM, but there were significant issues with plant health. Future work will focus on reducing concentrations of the active ingredient to produce an effective formulation that is not detrimental to plant health. Soybean oil, coconut fat and olive oil formulations with Panodan® AL10 and Grindox 122™ also gave effective PM control with minimal effect on plant health.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

Accuracy and sensitivity of different Bayesian methods for genomic prediction using simulation and real data

2020 ◽  
Vol 19 (3) ◽  
Author(s):  
Saheb Foroutaifar
Keyword(s):  
Data Analysis ◽  
Bayesian Methods ◽  
Milk Fat ◽  
Prediction Accuracy ◽  
Real Data ◽  
Fat Percentage ◽  
Real Data Analysis ◽  
Wide Range ◽  
High Heritability ◽  
Qtl Effects

AbstractThe main objectives of this study were to compare the prediction accuracy of different Bayesian methods for traits with a wide range of genetic architecture using simulation and real data and to assess the sensitivity of these methods to the violation of their assumptions. For the simulation study, different scenarios were implemented based on two traits with low or high heritability and different numbers of QTL and the distribution of their effects. For real data analysis, a German Holstein dataset for milk fat percentage, milk yield, and somatic cell score was used. The simulation results showed that, with the exception of the Bayes R, the other methods were sensitive to changes in the number of QTLs and distribution of QTL effects. Having a distribution of QTL effects, similar to what different Bayesian methods assume for estimating marker effects, did not improve their prediction accuracy. The Bayes B method gave higher or equal accuracy rather than the rest. The real data analysis showed that similar to scenarios with a large number of QTLs in the simulation, there was no difference between the accuracies of the different methods for any of the traits.

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