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Archive for the ‘Monitoring’ Category

From the Aliens’ list/PestNet

From: Arne Witt <a.witt@cabi.org>
Date: 9 November 2017 at 20:25
Subject: [Aliens-L] FAW

New report reveals cost of Fall Armyworm and provides recommendations for control

 

fall-armyworm-frontal-MER-563x744

The report, commissioned by the UK’s Department for International Development (DFID), reviews the current evidence of the potential impact of the pest and quantifies the likely economic effect on agricultural sectors in affected countries and regions if left unmanaged.

In the absence of any control methods, we estimate that the pest has the potential to cause huge maize yield losses in Africa and we expect it to spread throughout suitable habitats in mainland sub-Saharan Africa within the next few cropping seasons. Northern Africa and Madagascar are also at risk. This would clearly have a huge impact on food security and the achievement of SDG 2 (Zero Hunger).

Control of Fall Armyworm requires an integrated pest management (IPM) approach and immediate recommendations we make in the report include raising awareness on Fall Armyworm symptoms, early detection and control, and the creation and communication of a list of recommended, regulated pesticides and biopesticides to control the pest. Work must also start to assess which crop varieties can resist or tolerate Fall Armyworm. In the longer run national policies should promote lower risk control options through short term subsidies and rapid assessment and registration of biopesticides and biological control products.

To see the reports:

Download the 10 page summary of the evidence note

Download the full evidence note

 

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science daily -logo

These  can dive, swim, and jump like dolphins

Puffins, flying fish, and dolphins are naturals in both the air and sea, moving from one to the other with ease. Now, for the first time, a tiny robot is joining their routine. The bee-sized bot, which can fly by flapping its tiny wings, has been re-engineered to dive into water, swim, take off again, and land safely. Once it dries off, the “robo-bee” can repeat the whole routine—or go back to flying. But engineering for water wasn’t easy. The researchers realized early on that their 175-milligram bot needed help staying upright underwater. So they added stabilizing cross beams and slowed down how quickly it beat its wing: In air, the wings flap about 250 times per second; in water, they average about nine beats per second. Any faster than that, and the bot starts to tilt and twist and can even fall apart. The bot also needed help breaking through the water’s surface tension, so the researchers figured out how to give it a push with an electrical device that converts water into oxygen and hydrogen, plus a “sparker” that can ignite these gases. After 2 minutes, the gases build and make the bot buoyant enough to get its wings out of the water. Then the spark blows up the gases, and the bot shoots up about 35 centimeters at a speed of more than 2 meters per second, the researchers report today in Science Robotics. The bot can’t fly again until it dries out, but its design helps it glide to a safe landing. And though it’s unlikely to perform at Sea World, this versatile bot may one day help with ocean search and rescue, fish surveys, and environmental monitoring.

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Daily Nation

Technology will help farmers identify crop diseases and the nearest support system

AP

By BRIAN OKINDA

More by this Author
1 day ago

A team of scientists has developed a mobile phone application which uses artificial intelligence (AI) to accurately identify crop diseases in the field.

The app also delivers the latest advice to manage all major diseases and pests that affect root, tuber and banana crops, and helps farmers identify the nearest agricultural extension support for the farmers.

The project which is being implemented by a global network of scientists is part of the Consultative Group for International Agricultural Research’s (CGIAR) research programme on Roots, Tubers and Bananas (RTB).

“As smartphones become more common in rural Africa, they also become handy in agricultural productivity.

“Smallholder farmers or extension officials having basic smartphones with a camera can download the application free of charge, run it up and point the camera at a leaf that has disease indications. They will then get an immediate diagnosis of the disease affecting the plant.” said Dr James Legg, a researcher at the (IITA), in Tanzania, who heads the project alongside Dr David Hughes of Penn State University.

Cassava brown streak and cassava mosaic diseases have for a long time been a threat to food security and income generation of over 30 million farmers in East and Central Africa.

Similarly, the region’s banana production is vulnerable to fungal and bacterial diseases such as the devastating banana bunchy top virus and while late blight which beleaguer potato farmers.

Rural farmers are often incapable of properly identifying these diseases, while researchers, plant health experts and extension officials lack the data to support them, hence the significance of this development.

The current app was developed to help identify cassava diseases, but the team of developers/researchers  was awarded Sh10 million in grants as part of CGIAR’s platform for Big Data in Agriculture Inspire Challenge in September, to help them expand the application to other root, tuber and banana crops that are key food sources.

This will in turn boost nutrition and income security for many farmers.

In the application’s initial development, careful fieldwork involving cameras, spectrophotometers and drones at cassava field sites in coastal Tanzania and on farms in western Kenya generated more than 200,000 images of diseased crops to train the system’s AI algorithms.

Using these images, the scientists advanced an AI process that is able to automatically classify five cassava diseases, and by involving tech company, Google, the team was able to develop the smartphone application using TensorFlow, an open-source software library for machine learning across a range of tasks.

The system is currently under field-test in Tanzania.

Penn State University has also developed a mobile spectrophotometer through a small firm called Croptix, whose initial results indicate it can accurately diagnose different viral diseases in the field, even when the plant looks healthy.

“The application similarly uses AI in real time so the farmer can be an active contributor in disease diagnosis and plant health management, hence more yields for smallholder farmers.

“It is similarly groundbreaking because our AI is based on research from scientists at CGIAR and RTB, who are among the world’s best human intelligence on African crops,” said Dr Hughes.

The team has established a working association with Vodafone’s agriculture SMS platform, DigiFarm, which will allow them to link digital diagnostics to largescale text messaging services used by rural farmers.

It will in turn deliver farmer-tailored SMS alerts on crop diseases and pests to 350,000 Kenyan farmers by July 2018.

 

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Machine Learning Helps Small Farmers Identify Plant Pests And Diseases

A new app aims to help smallholder farmers fight pests and diseases that are killing their crops.

Machine Learning Helps Small Farmers Identify Plant Pests And Diseases
[Photo: Waldo Swiegers/Bloomberg/Getty Images]

The world’s 500 million smallholder farmers have a new weapon in their never-ending fight against pests and plant diseases: an app called Plantix. By uploading pictures of affected crops to the mobile service, they can quickly diagnose unwanted funguses and insects and get ideas about how to deal with infestations before they get out of control. Three years after launch, the app is being used more than 1 million times a month, particularly in India, Brazil, and North Africa.

[Photo: courtesy Plantix]

In Africa, the current number-one enemy pest is the fall armyworm–so-called because it marches like an advanced military unit, eating everything in its path. The colorful caterpillars are munching through maize, sorghum, rice, and legume fields in 24 countries. If farmers don’t react in time–for example by spraying with the appropriate pesticides–economic losses could reach more than $5 billion this year, estimates show.The UN Food & Agricultural Organization says 20% to 40% of all global crops are lost each year because of plant pests and diseases that aren’t managed properly. Developed by a small team in Germany, Plantix offers guidance to farmers who don’t have the privilege of human consultants.

https://www.fastcompany.com/embed/uATcLOJZ?playerID=G2hQKLvX

“There’s a huge gap between agricultural consultancy and people’s needs on the ground in emerging countries,” says Korbinian Hartberger, one of four cofounders of PEAT, the startup that develops the free-to-use app. “There’s a lot more demand than what’s on offer. They can’t wait for someone to come along two months [after the infestation] and say, ‘yes, I think you should have sprayed this.’”

The Android interface is simple but makes use of sophisticated machine learning technology working in the background. PEAT has trained its algorithms using thousands of pictures of affected plants, allowing the app to recognize telltale patterns as farmers upload new pictures. They’re currently sending in about 5,000 pictures a day and the app is able to recognize up to 400 diseases or pests. The most common include soya bean and wheat rust, powdery and downy mildews, and aphids, Hartberger says.

As well as automated image recognition, the app also features community forums, where users help each other diagnose problems from uploaded photos. About 200,000 users are actively using the service, according to the startup.

PEAT was initially funded through a grant from the German government and it doesn’t generate revenue currently. Hartberger says that could change in the future. For instance, the system could be adapted for use in aerial drones or on-the-ground robots, or it could help connect farmers with sellers of agricultural products. Currently, it suggests generic pesticides, but not brand names.

“People may use more pesticides [after using the app], but they’re less likely to use the wrong pesticides. Our contribution is to smallholders with fast and reliable information, so they’re not just going to shop and asking the guy behind the counter for advice. It gives them something more specific they can work with,” Hartberger says.

About the author

Ben Schiller is a New York staff writer for Fast Company. Previously, he edited a European management magazine and was a reporter in San Francisco, Prague, and Brussels.

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USDA APHIS ITP’s web-based tool, Antkey

The team is pleased to announce the latest addition to our mobile app collection: Antkey Mobile. Developed in cooperation with the tool’s author, Eli Sarnat, and Australia’s Identic team, this app is based on ITP’s

Lucid Mobile apps offer you the identification keys you’ve come to rely on from the convenience of your smartphone or tablet. Antkey Mobile (free for Android or iOS) allows you to take your Lucid key with you into the field for surveys and screening, even if your field site lacks internet access.

This key allows both specialists and novices to easily identify invasive, introduced, and commonly intercepted ant species from across the globe. You can help confirm whether you have found the correct species by comparing your specimen with the images and descriptions on the fact sheets, which are included for each species.

Antkey Mobile is one of 13 apps ITP has developed for use in field identification of plant pests and diseases. Please visit http://idtools.org to see all of ITP’s apps or to learn more about ITP. For technical questions about Lucid Mobile, please contact Identic (enquiries@lucidcentral.org) or visit their website. For questions or comments about this or any of ITP’s other mobile apps, please contact Amanda Redford (itp@usda.gov).Antkey

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SW FarmPress

Drones
A panel of researchers discussed possible applications for UAS—unmanned aerial systems—at the recent American Peanut Research and Education Society (APRES) annual meeting in Albuquerque.

 

Ron Smith | Jul 19, 2017

The initial “gee whiz what a great idea” phase of unmanned aerial vehicle introduction has abated, somewhat, leaving the folks genuinely interested in using the technology for commercial endeavors now asking: “How will this amazing technology help me run my business?”

A panel of researchers discussed possible applications for UAS—unmanned aerial systems—at the recent American Peanut Research and Education Society (APRES) annual meeting in Albuquerque. Panelists Jamey Jacob, Oklahoma State University; Sarah Pelham, University of Georgia; Josh McGinty, Texas A&M AgriLife; and Maria Batola, Virginia Tech, agreed that unmanned aerial vehicles—drones—are capable of “taking pretty pictures,” but that extracting useful data from those images requires a bit of tedious work and ongoing study into how to collect and use data.

“Collecting data is a piece of cake,” Batola said. “We get beautiful pictures in 10 to 15 minutes, but it may take several hours to analyze the data from those images.”

And data, she said, is the reason to fly the drones. “Big data is a big deal. We want to develop phenotyping tools to aid plant breeders and to develop remote sensing tools to benefit agricultural producers.”

Batola says ag research has used ground unit remote sensing tools for years. “Now, we want to compare those with UAS.”

PRACTICAL APPLICATION

She said remote sensing studies at Virginia Tech have included efforts to estimate yields and to develop a nitrogen stability index. “We want to improve nitrogen management in wheat,” she said.

She’s looking at drought stress research in peanuts, evaluating various genotypes to observe wilting, yield and mature kernel potential, and crop values. “We want to find coefficients of correlation,” Batola said.

Pelham, a graduate student at the University of Georgia, is evaluating disease and phenotype relationships in peanuts “using unmanned aerial systems.” Tomato spotted wilt virus is a key disease target. She’s also looking at leaf spot and nematodes. “We want to use UAS to identify areas in the field with nematode infestations.”

She says different peanut genotypes show “different spectral signatures with different colors in the field.” Some varieties may be greener than others, for instance.

Drones also help evaluate stand count. “We can evaluate stands and determine a threshold for replant,” she said, “and we can determine where stands are thin and replant only those areas.”

Evaluating and predicting yield, she said, is another potential objective for UAS.

SYSTEMS EVOLVING

Jacob says making UAV technology an integral part of commerce has “a long way to go. The period of hype that comes with introduction of new technology does fade as some lose interest and some disillusionment sets in.” The task now, he said, is to find how to use UAS in a productive way.

The adoption will come, he added. “The current (younger) generation will be the last to get a driver’s license.” Driverless vehicles will become normal, he said. “Millennials, instead of having texting distract them from driving will think driving distracts them from texting.”

Agriculture, he added, will offer a big market for UAV use. “In Japan, UAVs have proven useful on small farms for spraying and other tasks.” Widespread use for more than imaging could be more problematic for large-scale farms. Potential uses include crop monitoring, chemical applications, and airborne imagery. But cost could be a factor. Manned aerial vehicles could, in some cases, be a better choice. Imagery would be takes from as high as 10,000 feet with a manned aircraft, he said. “UAVs have higher resolution, but do you need it? A lot depends on the cost and the crop value and what you need from the imagery.”

Jacob said UAVs will improve and find more uses. With normalized differentiated visual imagery (NVID) producers can identify areas of vegetation that are healthier than other areas. “We can get biomass estimations with added sensors and perhaps estimate crop yields. Plant diagnostic capabilities may improve to being capable of collecting data associated with a single plant.”

 He said automated weed databases will be configured to send data to automated ground vehicles that will target sprays.

REGULATORY ISSUES

Jacob says regulations continue to limit some uses. For instance, users currently have altitude limits and must keep the UAV in sight, which requires someone on the ground to monitor the vehicle. That could change in the future to allow a user to  monitor and control a unit from an office, collect data, process with a computer and take action from the information collected—without leaving the desk.

Challenges with that system include increased risk, insurance options and safety precautions.

He said technology is getting cheaper, but cost will be driven by the application and the size needed to perform certain tasks. A vehicle capable of spraying, for instance, would be heavier, and more expensive than a small rotor drone that mostly takes photos.

McGinty says in the future, UAS will be used to collect field data and use it for decisions or to evaluate research efforts. “We will collect and process data and determine what information will be useful and how best to use it. That’s the goal, but we’re not there yet.”

He’s using mostly rotor units for crop research evaluations, and fixed-wing for some pasture and rangeland studies. Fixed wing, he said, covers more area.

In research plots, he’s using drones to check plant growth, including plant height and canopy cover. Assessing plant health with NDVI is also a possibility. “We want to be able to use UAS data to predict yield,” he said. Drones are evaluating plant height and boll and bloom counts in cotton. “Boll counts have proven to be of less value than we anticipated,” he said. “But we are looking at different ways to use that data.”

He said looking at bloom counts may help identify stressed plants.

He’s also looking at sorghum. “We can collect images of sorghum panicles, but we have to count by hand. We want to automate that. But even having to do counts manually in the office is better than counting in the field in the heat and humidity of Corpus Christi.”

He said research on sorghum is in early stages. “We have only one year of data.

PROCESSING PROBLEMS

“Our biggest struggle so far is in sharing data,” McGinty said. “After collecting data, we may spend from eight to 12 hours processing it.” Going through a UAS Hub located at College Station streamlines the process.

The initial hype, Jacob says, has diminished. Regulations remain in place with the FAA still in control of drone flights, but rules are under review as more units are put in use and as technology improves control.

The key to making a drone a useful tool for agricultural research and for on-farm applications, the four researchers said, is to find ways to put the collected data to use in decision making. Data is the crucial factor, and the technology is not available yet to collect, process and use the information efficiently.

“Big data is essential for crop use,” Jacob said. “We can take pretty pictures, but we’re not to big data yet.”

 

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To see video go to:

https://shop.bdspublishing.com/checkout/Store/bds/Detail/WorkGroup/3-190-9781786761965

Rice_pests_aRice_pests_b

 

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