Plant Pest Modeling
Follow
Find
1.8K views | +6 today
Plant Pest Modeling
About computer systems using forecasting models, databases and decision support schemes in managing plant pest interactions with crop/canopy and weather/climatic data
Curated by Knapco
Your new post is loading...
Your new post is loading...
Scooped by Knapco
Scoop.it!

Forecasting agricultural output using space, agrometeorology and land based observations

Forecasting agricultural output using space, agrometeorology and land based observations | Plant Pest Modeling | Scoop.it

This document presents the proceedings of the annual review meeting by India Meteorological Department (IMD) on “Forecasting Agricultural Output Using Space, Agrometeorology and Land Based Observations” (FASAL) organized at YASHADA, Pune during 1-2 August 2011.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Warm Winters May Affect Crop Management Decisions in Kansas

Salina Journal: Warm Winters May Affect Crop Management Decisions in Kansas 

The U.S. Department of Agriculture recently revised its Plant Hardiness Zone Map northward, meaning that the extreme low temperatures during the winter in Kansas and most of the rest of the country aren't quite as cold now as they were about 20 to 30 years ago, said Mary Knapp, K-State Research and Extension climatologist.

Agricultural producers in the state may see some benefits from this trend of less extreme cold in the winter, but it may also result in the need for a few management changes in their cropping practices, according to K-State Research and Extension scientists. It may influence plant disease and pest overwintering survival. 

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Agro-Meteorology in India

Agro-Meteorology in India | Plant Pest Modeling | Scoop.it
Agro-Meteorology. WOTR is partnered by the India Meteorological Department (IMD) in its Agro-Meterology efforts. The IMD guides WOTR in weather station installations, weather predictions as well as in providing agro advisories.

Automated Weather Stations were installed in villages. Localized Met-advisories and Agri-met advisories are in demand and they can be very much useful in giving timely information to farmers so that they can plan their agricultural activities accordingly.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

USPEST.ORG, Integrated Plant Protection Center of Oregon State University

USPEST.ORG, Integrated Plant Protection Center of Oregon State University | Plant Pest Modeling | Scoop.it

Integrated Plant Protection Center of Oregon State University hosts several web sites/resources dealing with IPM, forecasting models and pest management.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Plant pest and disease forecasting for early warning in crop protection

Plant pest and disease forecasting for early warning in crop protection | Plant Pest Modeling | Scoop.it

News and Events - Bioforsk:

Climate factors play a major role in determining the impact of several pests and diseases on rice crop yields. Based on this rationale, the ClimaRice II project has identified a potential for further use of existing weather data as input to a computerised system for plant pest and disease.

A network of 224 Automatic Weather Stations (AWS) throughout Tamil Nadu state will collect the data which will be used as input to a weather forecasting model. Initially, the focus will be on paddy blast disease, caused by the fungal pathogen Magnaporthe grisea, and insect pest paddy leaf mite Oligonychus oryzae. The assumption is that farmers access to pest and disease warnings, either directly by mobile internet/SMS, or through advisory service officers, enables improved targeting of crop protection measures which both can give increased crop yield and quality, as well as reduced pesticide use/or timely use and less production costs to farmers.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Interactive Effects of Temperature and Leaf Wetness Duration - Cucurbit Downy Mildew

Interactive Effects of Temperature and Leaf Wetness Duration - Cucurbit Downy Mildew | Plant Pest Modeling | Scoop.it

Outbreaks of cucurbit downy mildew caused by Pseudoperonospora cubensis are dependent on the weather but effects of temperature and leaf wetness duration on infection have not been studied for different cucurbits. To determine the effects of these two weather variables on sporangia germination and infection of cucurbit host types by P. cubensis, three host types; cucumber, cantaloupe, and acorn squash, were inoculated and exposed to leaf wetness durations of 2 to 24 h at six constant temperatures ranging from 5 to 30°C in growth-chamber experiments


Interactive effects of temperature and leaf wetness duration on sporangia germination and infection of cucurbit hosts by P. cubensis were used on risk charts based on prevailing or forecasted temperature and leaf wetness duration. These results will improve the timing and application of the initial fungicide spray for the control of cucurbit downy mildew.



Neufeld KN & Ojiambo PS (2012) Interactive Effects of Temperature and Leaf Wetness Duration on Sporangia Germination and Infection of Cucurbit Hosts by Pseudoperonospora cubensis. Plant Disease - 96(3):345-353. 

http://dx.doi.org/10.1094/PDIS-07-11-0560 

more...
No comment yet.
Scooped by Knapco
Scoop.it!

European Federation for Information Technology in Agriculture

European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) has been sending EFITA Newsletters weekly already since 1999. 

Guy Waksman, a curator with a good sense of humor, carries for both, EFITA nad its French member AFIA news (Association Francophone d'Informatique en Agriculture). The EFITA moderated mailing list has over 4700 subscribers.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Caribbean Agrometeorological Initiative

Caribbean Agrometeorological Initiative | Plant Pest Modeling | Scoop.it

Weather and climate affect agricultural production in the Caribbean significantly where rainfall variability results in droughts and floods. Climate change is likely to exacerbate the impacts of natural variability and its extremes by, for example, an increasing frequency and intensity of events like floods and droughts.


The project has been launched to promote an integrated approach to sustainable development in the Caribbean region through the co-ordination and networking of the limited meteorological services available and their supporting regional and international research institutions. 

Agrometeorological applications will be improved and will contribute to increased and sustainable agricultural productivity at farm level in the Caribbean region through improved dissemination and application of weather and climate information. 

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Wheat Gains as Freezing Weather in Europe May Curb Production - BusinessWeek

Will the cold in Europe and in Russia and Ukraine influence grain prices?

Temperatures reached minus 15 degrees Celsius (5 degrees Fahrenheit) in France’s Alsace and Lorraine regions yesterday, according to forecaster Meteo France. In northern Germany, where some areas lack snow cover, soil temperatures have dropped below minus 8 degrees Celsius, Deutscher Wetterdienst said. Cold weather in the so-called Black Sea region also has hurt crops.

Soil temperatures dropped to minus 20 degrees Celsius for more than two days in the Dnipropetrovsk region, where 44 percent of planted grain failed to emerge after an autumn drought, Adamenko said by telephone from Kiev.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Weather center predicts reseeding 50% of winter crops in Ukrain

Weather center predicts reseeding 50% of winter crops in Ukrain | Plant Pest Modeling | Scoop.it

NRCU - Ukrainian Radio: Weather center predicts reseeding 50% of winter crops. This is what Tetiana Adamenko, head of the agrometeorology department, reported.

More accurate assessment of the state of winter crops after hibernation will be made by the end of March. The expert reminded that this year record low temperatures were registered in some regions at a depth of the tillering node. About 20% of wheat have not risen and the cold will add at least 20-30%.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

California PestCast: Disease Model Database-UC IPM

Information about Disease Model Database, California PestCast, on the University of California IPM Web site...


Their database is a clearinghouse of information about models developed for economically important crop and turf diseases in California. A model is included in the database if it uses weather, host, and/or pathogen data to predict risk of disease outbreak. The database is a part of a project called "PestCast," a regional weather network to support the development, validation, and implementation of crop disease models.

Statewide Integrated Pest Management Program staff members work closely with area IPM advisors, farm advisors, specialists, and researchers to develop educational programs that reflect the newest advances in pest management. The online courses are offered free of charge. Additional training materials, including videos, DVDs, books, and leaflets, are available in the Publications section. 

Insects, diseases, and invasive weeds threaten California's natural environments as well as homes, gardens, and agriculture. Warnings about exotic and invasive pests are included. Useful links to articles, fact sheets, and other information prepared by UC scientists on topics related to pests could be found on this page.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Hierarchical Bayesian models for estimating the extent of plant pest invasions | QUT ePrints

Hierarchical Bayesian models for estimating the extent of plant pest invasions | QUT ePrints | Plant Pest Modeling | Scoop.it
Stanaway, Mark Andrew (2011) Hierarchical Bayesian models for estimating the extent of plant pest invasions. PhD thesis, Queensland University of Technology.


The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities.

Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis.

Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. 

more...
No comment yet.
Scooped by Knapco
Scoop.it!

WEATHER AND CLIMATE FORECASTS FOR AGRICULTURE

Weather plays an important role in agricultural production. It has a profound influence on crop growth, development and yields; on the incidence of pests and diseases; on water needs; and on fertilizer requirements.


For optimal productivity at a given location, crops and cropping practices must be such that while their cardinal phased weather requirements match the temporal march of the relevant weather element(s), endemic periods of pests, diseases and hazardous weather are avoided. In such strategic planning of crops and cropping practices, short-period climatic data, both routine and processed (such as initial and
conditional probabilities), have a vital role to play.

Read more in GUIDE TO AGRICULTURAL METEOROLOGICAL PRACTICES.

more...
No comment yet.
Scooped by Knapco
Scoop.it!

Scientia Agricola - Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study

A review of disease-warning systems used as decision support tools designed to help growers determine when to apply control measures to suppress crop diseases.


The authors stress that weather data are nearly ubiquitous inputs to warning systems. Grower-operated weather monitoring is contrasted with obtaining data from networks of weather stations, and the advantages and disadvantages of measuring vs. estimating weather data are discussed. Special emphasis is given to leaf wetness duration (LWD), not only because LWD data are inputs to many disease-warning systems but also because accurate data are uniquely challenging to obtain. 


Gleason et al. (2008) Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study.  Scientia Agricola (Piracicaba, Braz.) vol.65 Dec. 2008

http://dx.doi.org/10.1590/S0103-90162008000700013

more...
No comment yet.