{"id":12153,"date":"2021-08-30T11:51:01","date_gmt":"2021-08-30T15:51:01","guid":{"rendered":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences-new\/?p=12153"},"modified":"2021-08-30T11:51:01","modified_gmt":"2021-08-30T15:51:01","slug":"winter-wheat-scouting-takes-flight","status":"publish","type":"post","link":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/news\/winter-wheat-scouting-takes-flight\/","title":{"rendered":"Winter Wheat Scouting Takes Flight"},"content":{"rendered":"

Winter wheat is an economically (and gastronomically) important grain crop in North Carolina, producing legions of cookies and crackers and almost $100 million in revenue for NC farmers. But Italian ryegrass is an herbicide-resistant weed that plagues winter wheat yields, especially in NC’s Piedmont region. In many fields, once the weed appears, it can\u2019t be chemically controlled. NC State researchers have successfully drone-identified early-stage Italian ryegrass in winter wheat allowing for wholistic weed management options.<\/span><\/p>\n

\u201cIt\u2019s easy to identify a broadleaf weed in a grass crop or a grass in a broadleaf crop. But there were a lot of questions about whether or not we could differentiate within a grass species,\u201d said Wes Everman, NC State associate professor of weed science. \u201cOur aerial imagery was very clear. My team and I quickly realized that we could identify and map Italian ryegrass with up to 96% accuracy <\/span>and<\/span><\/i> early enough to have some management options.\u201d<\/span><\/p>\n

\"Italian
Italian ryegrass is an herbicide-resistant weed that can limit winter wheat yields.<\/figcaption><\/figure>\n

Studies have shown that Italian ryegrass reduces wheat tillering causing four percent yield declines for every ten Italian ryegrass plants per square meter. Up to 80 percent yield loss can occur where high densities of Italian ryegrass exist. If a significant Italian ryegrass population forms, farmers often settle to cut the crop for hay, usually at a lower price.\u00a0<\/span><\/p>\n

Additionally, most growers wait until crop prices solidify mid-season before actively managing winter wheat fields, making management with post-emergence herbicides problematic.\u00a0<\/span><\/p>\n

Early Italian ryegrass identification opens the door to early-season management techniques beyond herbicides. Cultivation, seed cleaning, and even hand-pulling in small patches would improve wheat crop quality. Even late-stage weed identification could impact management practices for next season like preemergence applications and crop rotation. Knowing where weed populations exist empowers growers to make informed decisions.<\/span><\/p>\n

Detection At The Speed of Light<\/span><\/h2>\n
\"drone
Drone imagery highlights Italian ryegrass weeds in winter wheat.<\/figcaption><\/figure>\n

Everman\u2019s research used multispectral sensing to classify ryegrass based on reflected energy from the leaf surface instead of <\/span>leaf size or pattern shape<\/span><\/a>. With clear skies and midday timing, the team could discern Italian ryegrass in wheat using a drone at altitudes ranging from 15-45 meters. The higher flight altitude had no significant bearing on the classification accuracy, allowing a drone pilot to cover larger fields faster, maximizing drone battery life and enabling application in real-world situations.<\/span><\/p>\n

\u201cWhile our analyst-guided image classification was almost universally correct, even our computer-assigned image classification was 60-70% accurate. That\u2019s low-hanging fruit showing just how easy it is to train an artificial intelligence classifier for this weed.\u201d Everman said.<\/span><\/p>\n

And the entire identification process is becoming more efficient. What used to take one to two weeks from field collection to conclusion has now slimmed to a few hours because of improved processing power. And the technology keeps improving.<\/span><\/p>\n

Refining Weed Imagery Id<\/span><\/h2>\n

The next evolution in Everman\u2019s research is to classify additional weed species in wheat and eventually tell different weed species apart in any crop.\u00a0<\/span><\/p>\n

\u201cMost of the work in remote sensing has been to differentiate between crop and weed. Very little has been done to discern within grass weed species and broadleaf species.\u201d Everman said. \u201cSoftware companies are refining their algorithms to identify crops and count plants. We could reverse engineer the weed population out of those maps for identification.\u201d<\/span><\/p>\n

Scouting On The Fly<\/span><\/h2>\n

Everman noted that weeds usually affect less than 40% of a field and occur in isolated patches, making entire-field treatment unnecessary and potentially counterproductive. Knowing exactly where and when specific weeds appear in a field would allow farmers to select the appropriate management strategy and proactively thwart troublesome weeds.\u00a0<\/span><\/p>\n

\"Wes
Wes Everman’s research specializes in weed science<\/figcaption><\/figure>\n

But field scouting, he noted, is a dying art.<\/span><\/p>\n

\u201cWe can serve our growers by helping them get above their field and see what weeds they have. UAVs are a great entry point for that,\u201d Everman said. \u201cThe flying is pretty easy. There are software programs that allow you to just plug into an app and click \u201cgo.\u201d The UAV flies the route and comes back to where it started, and it\u2019s done. But the data interpretation — that\u2019s more intense.\u201d<\/span><\/p>\n

Everman sees an opportunity for Extension to assist growers with the complexities of image collection, processing and interpretation. He proposed training county Extension agents to fly drones for farmers and then collaborate with geospatial expert <\/span>Rob Austin<\/span><\/a> and himself to analyze the field data for various biotic and abiotic stresses.<\/span><\/p>\n

Farmers or agronomists could then translate field results into prescription herbicide application files or drone sprayers for precise application.\u00a0<\/span><\/p>\n

\"A
Rob Austin teaches geospatial analytics in and out of the classroom.<\/figcaption><\/figure>\n

\u201cHaving this type of technology would have been helpful when Palmer amaranth was just starting to invade the Piedmont area. Going forward, we could identify weed species shifts and herbicide resistance creeping in — maybe even different management techniques or chemistries that would extend their longevity. There\u2019s a number of applications this technology could have for our farmers.\u201d Everman said.<\/span><\/p>\n

Want More Field-Based Technology?<\/span><\/h2>\n

Crop and Soil Sciences\u2019 research impacts farmers and students, from the air to the field. Follow how our practical innovations affect agriculture and environmental science by joining our <\/span>weekly newsfeed<\/span><\/a>.<\/span><\/p>\n

If you are a student interested in weed science or precision agriculture, investigate our undergraduate and graduate <\/span>degree programs<\/span><\/a>. Then join us for a <\/span>guided email tour<\/span><\/a> of our department and university. Enhancing NC agriculture through technology is just part of how we are growing the future.\u00a0<\/span><\/p>\n

\"tractor<\/p>\n

 <\/p>\n","protected":false,"raw":"Winter wheat is an economically (and gastronomically) important grain crop in North Carolina, producing legions of cookies and crackers and almost $100 million in revenue for NC farmers. But Italian ryegrass is an herbicide-resistant weed that plagues winter wheat yields, especially in NC's Piedmont region. In many fields, once the weed appears, it can\u2019t be chemically controlled. NC State researchers have successfully drone-identified early-stage Italian ryegrass in winter wheat allowing for wholistic weed management options.<\/span>\r\n\r\n\u201cIt\u2019s easy to identify a broadleaf weed in a grass crop or a grass in a broadleaf crop. But there were a lot of questions about whether or not we could differentiate within a grass species,\u201d said Wes Everman, NC State associate professor of weed science. \u201cOur aerial imagery was very clear. My team and I quickly realized that we could identify and map Italian ryegrass with up to 96% accuracy <\/span>and<\/span><\/i> early enough to have some management options.\u201d<\/span>\r\n\r\n[caption id=\"attachment_12156\" align=\"alignnone\" width=\"1500\"]\"Italian Italian ryegrass is an herbicide-resistant weed that can limit winter wheat yields.[\/caption]\r\n\r\nStudies have shown that Italian ryegrass reduces wheat tillering causing four percent yield declines for every ten Italian ryegrass plants per square meter. Up to 80 percent yield loss can occur where high densities of Italian ryegrass exist. If a significant Italian ryegrass population forms, farmers often settle to cut the crop for hay, usually at a lower price.\u00a0<\/span>\r\n\r\nAdditionally, most growers wait until crop prices solidify mid-season before actively managing winter wheat fields, making management with post-emergence herbicides problematic.\u00a0<\/span>\r\n\r\nEarly Italian ryegrass identification opens the door to early-season management techniques beyond herbicides. Cultivation, seed cleaning, and even hand-pulling in small patches would improve wheat crop quality. Even late-stage weed identification could impact management practices for next season like preemergence applications and crop rotation. Knowing where weed populations exist empowers growers to make informed decisions.<\/span>\r\n

Detection At The Speed of Light<\/span><\/h2>\r\n[caption id=\"attachment_12158\" align=\"alignright\" width=\"450\"]\"drone Drone imagery highlights Italian ryegrass weeds in winter wheat.[\/caption]\r\n\r\nEverman\u2019s research used multispectral sensing to classify ryegrass based on reflected energy from the leaf surface instead of <\/span>leaf size or pattern shape<\/span><\/a>. With clear skies and midday timing, the team could discern Italian ryegrass in wheat using a drone at altitudes ranging from 15-45 meters. The higher flight altitude had no significant bearing on the classification accuracy, allowing a drone pilot to cover larger fields faster, maximizing drone battery life and enabling application in real-world situations.<\/span>\r\n\r\n\u201cWhile our analyst-guided image classification was almost universally correct, even our computer-assigned image classification was 60-70% accurate. That\u2019s low-hanging fruit showing just how easy it is to train an artificial intelligence classifier for this weed.\u201d Everman said.<\/span>\r\n\r\nAnd the entire identification process is becoming more efficient. What used to take one to two weeks from field collection to conclusion has now slimmed to a few hours because of improved processing power. And the technology keeps improving.<\/span>\r\n

Refining Weed Imagery Id<\/span><\/h2>\r\nThe next evolution in Everman\u2019s research is to classify additional weed species in wheat and eventually tell different weed species apart in any crop.\u00a0<\/span>\r\n\r\n\u201cMost of the work in remote sensing has been to differentiate between crop and weed. Very little has been done to discern within grass weed species and broadleaf species.\u201d Everman said. \u201cSoftware companies are refining their algorithms to identify crops and count plants. We could reverse engineer the weed population out of those maps for identification.\u201d<\/span>\r\n

Scouting On The Fly<\/span><\/h2>\r\nEverman noted that weeds usually affect less than 40% of a field and occur in isolated patches, making entire-field treatment unnecessary and potentially counterproductive. Knowing exactly where and when specific weeds appear in a field would allow farmers to select the appropriate management strategy and proactively thwart troublesome weeds.\u00a0<\/span>\r\n\r\n[caption id=\"attachment_12154\" align=\"alignright\" width=\"450\"]\"Wes Wes Everman's research specializes in weed science[\/caption]\r\n\r\nBut field scouting, he noted, is a dying art.<\/span>\r\n\r\n\u201cWe can serve our growers by helping them get above their field and see what weeds they have. UAVs are a great entry point for that,\u201d Everman said. \u201cThe flying is pretty easy. There are software programs that allow you to just plug into an app and click \u201cgo.\u201d The UAV flies the route and comes back to where it started, and it\u2019s done. But the data interpretation -- that\u2019s more intense.\u201d<\/span>\r\n\r\nEverman sees an opportunity for Extension to assist growers with the complexities of image collection, processing and interpretation. He proposed training county Extension agents to fly drones for farmers and then collaborate with geospatial expert <\/span>Rob Austin<\/span><\/a> and himself to analyze the field data for various biotic and abiotic stresses.<\/span>\r\n\r\nFarmers or agronomists could then translate field results into prescription herbicide application files or drone sprayers for precise application.\u00a0<\/span>\r\n\r\n[caption id=\"attachment_12164\" align=\"alignnone\" width=\"1500\"]\"A Rob Austin teaches geospatial analytics in and out of the classroom.[\/caption]\r\n\r\n\u201cHaving this type of technology would have been helpful when Palmer amaranth was just starting to invade the Piedmont area. Going forward, we could identify weed species shifts and herbicide resistance creeping in -- maybe even different management techniques or chemistries that would extend their longevity. There\u2019s a number of applications this technology could have for our farmers.\u201d Everman said.<\/span>\r\n

Want More Field-Based Technology?<\/span><\/h2>\r\nCrop and Soil Sciences\u2019 research impacts farmers and students, from the air to the field. Follow how our practical innovations affect agriculture and environmental science by joining our <\/span>weekly newsfeed<\/span><\/a>.<\/span>\r\n\r\nIf you are a student interested in weed science or precision agriculture, investigate our undergraduate and graduate <\/span>degree programs<\/span><\/a>. Then join us for a <\/span>guided email tour<\/span><\/a> of our department and university. Enhancing NC agriculture through technology is just part of how we are growing the future.\u00a0<\/span>\r\n\r\n\"tractor\r\n\r\n "},"excerpt":{"rendered":"

NC State researchers successfully drone-identify early-stage Italian ryegrass in winter wheat allowing for wholistic weed management options.<\/p>\n","protected":false},"author":2196,"featured_media":12155,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"source":"","ncst_custom_author":"","ncst_show_custom_author":false,"ncst_dynamicHeaderBlockName":"","ncst_dynamicHeaderData":"","ncst_content_audit_freq":"","ncst_content_audit_date":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[23],"tags":[443,492,463,146,491],"class_list":["post-12153","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research","tag-drones","tag-remote-sensing","tag-stewardship","tag-weed-science","tag-winter-wheat"],"displayCategory":null,"acf":[],"_links":{"self":[{"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/posts\/12153","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/users\/2196"}],"replies":[{"embeddable":true,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/comments?post=12153"}],"version-history":[{"count":5,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/posts\/12153\/revisions"}],"predecessor-version":[{"id":12170,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/posts\/12153\/revisions\/12170"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/media\/12155"}],"wp:attachment":[{"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/media?parent=12153"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/categories?post=12153"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cals.ncsu.edu\/crop-and-soil-sciences\/wp-json\/wp\/v2\/tags?post=12153"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}