Skip to main content

Mike Gore, Ph.D. '09, plant geneticist in the College of Agriculture and Life Sciences, explains corn breeding at Musgrave Research Farm in Aurora, New York, in August.

小喵直播app破解版污

Mike Gore, Ph.D. ’09, hears the clock ticking. And while it’s not an alarm clock, it’s part of what gets him going every day.

Gore, associate professor of molecular breeding and genetics for nutritional quality, Liberty Hyde Bailey professor and international professor of plant breeding and genetics, conducts research at the intersection of several disciplines. His lab uses quantitative genetics, genomics, analytical chemistry and remote sensing to explore the genetic basis of trait variation in crops such as corn, oat and cassava.

A TerraSentia robot, which is being trained to perform remote diagnostics on individual corn plants, moves between rows of corn at Musgrave Research Farm in Aurora, New York.

Plant breeding has been going on for 10,000 years, he said, but technology – unmanned aerial vehicles (UAVs), robots, artificial intelligence (AI) and machine learning – is revolutionizing the practice.

“One role that we plant breeders can play is to learn how to integrate these cutting-edge technologies into research programs,” he said, “so that we can more efficiently and effectively select [plant variations] for the high-yielding, or highly nutritious, cultivar that can help feed the world’s population.”

黄瓜app下载新版本

Feeding the world’s population: It’s a huge challenge for plant breeders, he said, as well as researchers in other disciplines. Cornell is addressing it with the Cornell Initiative for Digital Agriculture (CIDA), which is leveraging digital innovations in agriculture to improve the sustainability, profitability, resiliency and efficiency of the world’s food systems. Gore is in the CIDA leadership group.

Currently at around 7.6 billion people, Earth’s population is expected to reach around 10 billion by 2050. How will we feed all those people in an efficient and sustainable way?

Gore admits that, although there’s still time to come up with viable solutions, he’s feeling the urgency.

“I think all plant scientists do,” Gore said. “We all share that passion, but we definitely hear that clock ticking. Let’s hope it’s not a timebomb.”

Gore’s lab uses “rapid phenotyping” – the ability to non-destructively measure a plant’s morphological, physiological, and biochemical properties in real time repeatedly over the course of a growing season, as opposed to waiting until harvest. That could help reduce the time it takes to develop crop varieties that are optimal for a particular region or climate.

“With these new technologies, we’re able to do phenotyping every day, every week, every month, to know how the plant is responding to the environment over whole growing seasons,” Gore said.

Among other crops, Gore’s lab focuses on corn – including corn grown in upstate New York – and the development of variations that are best suited to the short growing season and weather conditions. His lab employs camera-wielding UAVs – drones – and four-wheeled robots to perform real-time diagnostics of scores of corn varieties at the Musgrave Research Farm in Aurora, New York, about 24 miles north of campus.

This past summer, his shared 3-acre cornfield contained approximately 800 highly diverse hybrids, each in two-row mini-plots, from which his team will try to identify the best varieties for growing in the upstate region.

Gore’s team – in collaboration with the lab of Ed Buckler, adjunct professor of plant breeding and genetics – is developing AI for the autonomous vehicles that can count individual plants, measure plant height and check individual leaves for disease, among other tasks. And he can perform diagnostics on the plant at any point in its growth process.

“It’s like knowing a baseball player’s batting average in July, as opposed to just at the end of the season,” he said. “We’re trying to identify the key plant developmental stage that you can do the phenotyping on, so that it could be predictive of yield at the end of the season.

“If you had that capability,” he said, “then you’d know what plants to cross-breed before the pollen’s even been shed.”

By using technology to detect key traits in midseason, Gore said, he can perhaps develop more precise breeding methods – and shorten the breeding timeline “from six to eight years, to maybe four or five” as the technologies are developed.

He envisions a day when a robot or drone can not only facilitate rapid phenotyping, but also detect fungal diseases or weeds and immediately dispense a fungicide or herbicide in a precise dose, at just the right coordinate in the field. And while there will always be humans on a farm, Gore thinks a role-reversal could be in the offing.

“If we can train the robots, perhaps someday the robots will be training us to do very precise plant breeding,” he said. “We have more than 800 highly diverse hybrids in this field [at Musgrave]. Which one is the best for growing here, and why? Those are the questions we’re trying to answer. … We’re trying to closely model the biological reality of a plant. I would argue that, over time, robots can probably do it even better than human beings. That’s what we’re kind of on the cusp of right now.”

Developing a corn variety that’s best suited for upstate New York is one of many challenges Gore and researchers like him are tackling as the specter of feeding 10 billion people looms.

“All of these tools are going to be important for food and nutrition security,” he said. “How do we figure out how to use these technologies for crops such as cassava, rice, maize, wheat that all of these developing nations are relying on for nourishment?

“How do we turn the engine of evolution faster in plant breeding?” he asked. “We have to totally change the paradigm that we’ve been in for the past 10,000 years.”

枣庄佳巨浩有限公司

广州荣和国科技有限公司

青岛瑞永永贸易有限公司

酷咪直播app破解版污 黄鱼视频app破解版污 盘他app破解版污 含羞草实验研究所app下载新版本 月夜直播app下载新版本 奶茶视频app破解版污 陌秀直播app下载新版本 春水堂视频app最新版下载 Avnightapp最新版下载 小奶狗视频app最新版下载 名优馆app下载新版本 番茄视频app破解版污 MM直播app下载新版本 冈本视频app最新版下载 大西瓜视频app下载新版本 小猪视频app最新版下载 Kitty直播app最新版下载 久草app破解版污 成版人抖音app破解版污 豆奶视频app下载新版本 恋人直播app最新版下载 好嗨哟直播app破解版污 爱爱视频app下载新版本 恋人直播app最新版下载 秋葵视频app破解版污 丝瓜视频污app下载新版本 性福宝app破解版污 丝瓜视频污app下载新版本 97豆奶视频app下载新版本 主播福利app下载新版本 盘她s直播app最新版下载 麻豆视频app破解版污 野花视频app破解版污 向日葵app最新版下载 东京视频app最新版下载 初见直播app最新版下载 蝶恋花app最新版下载 花椒直播app下载新版本 雨燕直播app最新版下载 菠萝蜜app下载新版本 名优馆app破解版污 西瓜直播app下载新版本 成人快手app下载新版本 小公主直播app最新版下载 冈本视频app破解版污 嘿嘿连载app破解版污 梦鹿直播app最新版下载 大象视频app下载新版本 葡萄视频app破解版污 菠萝蜜app破解版污 s8视频app破解版污 粉色视频app破解版污 美岁直播app下载新版本 小草莓app破解版污 ML聚合app下载新版本 暗夜直播app最新版下载 快狐短视频app破解版污 avgoapp最新版下载 美岁直播app下载新版本 直播盒子app下载新版本 硬汉视频app下载新版本 免费黃色直播app最新版下载 兔子直播app破解版污 芭乐app最新版下载 茄子直播app下载新版本 么么直播app破解版污 梦幻直播app下载新版本 小米粒直播app下载新版本 繁花直播app最新版下载 7秒鱼app下载新版本 BB直播app下载新版本 斗艳直播app下载新版本 樱花视频app破解版污 鸭脖视频app破解版污 兔子直播app破解版污 梦鹿直播app破解版污 蜜柚直播app最新版下载 小优app破解版污 蜜蜂视频app最新版下载 小姐姐直播app破解版污 草榴直播app破解版污 花秀神器app最新版下载 9uuapp破解版污 趣播app破解版污 d2天堂app下载新版本 香蕉app破解版污 Huluwaapp下载新版本 压寨直播app下载新版本 丝瓜视频污app破解版污 比心app破解版污 黄瓜app下载新版本 压寨直播app最新版下载 樱花直播app下载新版本 小奶狗app下载新版本 鸭脖视频app破解版污 大番号app下载新版本 swag视频app破解版污 久草视频app最新版下载 污直播app破解版污 快喵app下载新版本 盘她app最新版下载 圣女直播app破解版污 杏趣直播app下载新版本 成版人茄子视频app最新版下载 冈本app下载新版本 秀色直播app破解版污 成版人音色短视频app破解版污 BB直播app破解版污 bobo直播app下载新版本 葡萄视频app下载新版本 花仙子直播app最新版下载 向日葵app破解版污 灭火卫视app破解版污 丝瓜视频app下载新版本 老王视频app最新版下载 内裤直播app破解版污 番茄视频app破解版污 快喵app破解版污 蓝精灵直播app破解版污 后宫视频app最新版下载 比心app最新版下载 夜遇直播号app破解版污 9uuapp下载新版本 木瓜视频app最新版下载 望月app最新版下载 69热app最新版下载 蝶恋花app破解版污 初恋直播app最新版下载 9uuapp下载新版本 Kitty直播app破解版污 千层浪app破解版污 9uuapp破解版污 金鱼直播app最新版下载 污软件app下载新版本 小奶猫app最新版下载 小蝌蚪视频app下载新版本 盘她app下载新版本 小花螺直播app下载新版本 小狐仙app最新版下载 萝卜视频app破解版污 浪浪视频app下载新版本 富二代f2抖音app下载新版本 iAVBOBOapp下载新版本 迷雾直播app下载新版本 黄瓜视频人app破解版污 桃花直播app下载新版本 铁牛app最新版下载 云雨直播app下载新版本 梦幻直播app最新版下载 秀色小抖音app最新版下载