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.


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.”


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.”




合欢视频下载app 草榴视频app下载 趣播app下载 彩云直播app下载 恋夜秀场下载app 蓝精灵直播app下载 黄鱼视频下载app视频免费最新 蓝颜app下载 污软件下载app视频免费最新 享爱app下载 iAVBOBOapp下载 趣播app下载 梦露直播下载app 套路直播下载app 依恋直播app下载 木瓜视频下载app 笔芯直播下载app 夜夜直播下载app 木瓜视频app下载 A头条下载app 可乐视频下载app视频免费最新 小奶狗app下载 硬汉视频app下载 遇见直播下载app 硬汉视频下载app 69视频下载app 花仙子直播下载app 美岁直播app下载 小奶狗app下载 佳丽直播app下载 年轻人片app下载 繁花直播下载app 花心社区app下载 91香蕉下载app 蚪音下载app 花姿直播下载app 梦露直播app下载 米老鼠直播下载app 冈本app下载 金鱼直播app下载 妖妖直播app下载 成版人短视频下载app视频免费最新 午夜直播间app下载 9uu下载app 梦幻直播下载app BB直播app下载 迷雾直播下载app 七秒鱼下载app 云雨直播下载app 牛牛视频下载app 幸福宝下载app 内裤直播app下载 含羞草app下载 香蕉app下载 花心视频app下载 秀色小抖音app下载 彩云直播下载app 麻豆传媒映画app下载 蝶恋花下载app 久草下载app 梦幻直播app下载 麻豆传媒映画app下载 大小姐直播下载app 橙子直播app下载 圣女直播下载app视频免费最新 杏吧直播下载app 富二代f2抖音下载app 橘子视频app下载 探探直播下载app 富二代短视频下载app 红楼直播app下载 蜜桃直播下载app 久草app下载 豌豆直播下载app 盘她直播下载app avgoapp下载 卡哇伊下载app 斗艳直播下载app 豆奶视频app下载 香草成视频人下载app 猫咪软件app下载 污软件下载app 香草视频下载app 花狐狸直播下载app 心上人直播app下载 草莓视频下载app 丝瓜下载app 花仙子直播下载app 朵朵直播app下载 黄页荔枝下载app视频免费最新 小草莓app下载 黄鱼视频app下载 荔枝下载app 享受直播下载app 斗艳直播app下载 秀色直播app下载 黄瓜直播下载app 成版人茄子视频下载app 微啪下载app 台湾swagapp下载 卡哇伊app下载 梦鹿直播下载app 猛虎直播下载app 小花螺直播app下载 大番号下载app 小宝贝直播下载app视频免费最新 压寨直播app下载 繁花直播下载app 千层浪app下载 蚪音下载app 91视频下载app 午夜直播下载app 音色短视频下载app 金鱼直播下载app 小仙女app下载 美岁直播app下载 比心下载app 蜜橙视频app下载 BB直播下载app 探花直播app下载 暗夜直播下载app 压寨直播app下载 久草视频下载app视频免费最新 蜜橙视频下载app 麻豆视频下载app 灭火卫视下载app视频免费最新 丝瓜草莓视频下载app视频免费最新 富二代f2下载app 菠萝菠萝蜜视频下载app 快狐app下载 可乐视频app下载 佳丽直播下载app 鸭脖视频下载app 泡芙短视频app下载 金屋藏娇直播间app下载 香草成视频人下载app视频免费最新 泡芙短视频下载app 夜夜直播下载app 富二代短视频下载app 红高粱直播下载app 小怪兽app下载 麻豆传媒直播app下载 心上人直播下载app 后宫下载app视频免费最新 黄页荔枝下载app视频免费最新 豆奶短视频app下载 小米粒直播app下载 柚子直播下载app 黄色直播软件下载app 合欢视频app下载 比心直播下载app 水晶直播app下载 梦露直播下载app 麻豆传媒直播下载app 遇见直播app下载 茶馆视频下载app 水仙直播下载app 依恋直播app下载 69视频下载app ML聚合下载app 彩色直播下载app 小宝贝直播下载app视频免费最新 食色短视频下载app 火爆社区下载app视频免费最新 尤蜜视频app下载 爱爱视频app下载 茶馆视频app下载 初恋直播下载app 花秀神器下载app 直播盒子下载app 圣女直播下载app视频免费最新 番茄社区app下载 富二代f2抖音下载app 杏吧直播下载app 红娘直播下载app 水仙直播app下载 豌豆直播下载app 一对一直播下载app 茄子直播下载app 主播福利app下载 iAVBOBO下载app 泡芙视频app下载 木瓜app下载 皮卡丘直播下载app BB直播下载app 9uuapp下载 蜜柚直播下载app 红杏视频app下载 柚子直播下载app 七秒鱼直播下载app 红杏视频下载app视频免费最新 快猫短视频app下载 左手视频下载app 久草视频下载app 草莓视频下载app 嘿嘿连载app下载 health2下载app 荔枝下载app 趣播app下载 d2天堂下载app Kitty直播下载app 快狐app下载 迷雾直播下载app 恋人直播app下载 菠萝蜜app下载 成版人抖音下载app swag台湾app下载 含羞草实验研究所app下载 梦鹿直播下载app 成版人短视频下载app视频免费最新 西瓜直播下载app fi11含羞草下载app视频免费最新 泡芙视频app下载 黄瓜下载app 麻豆传媒直播下载app 花秀神器下载app 花椒直播下载app 黄鱼视频下载app 佳丽直播下载app 鲍鱼视频下载app 夜猫视频app下载 丝瓜视频下载app视频免费最新 比心下载app 初见直播app下载 火爆社区下载app视频免费最新 东京视频app下载 硬汉视频下载app 杏花直播app下载 红杏视频下载app视频免费最新 光棍影院下载app 香草成视频人下载app 木瓜视频app下载 光棍影院下载app 小可爱app下载 嘿嘿连载下载app视频免费最新 性福宝下载app 笔芯直播app下载 色秀直播下载app 9uu下载app 麻豆视频下载app 彩色直播app下载 后宫下载app视频免费最新 内裤直播下载app视频免费最新 成版人茄子视频下载app 小狐仙视频app下载 迷雾直播下载app 桃花app下载 午夜直播app下载 黄瓜视频app下载 合欢视频app下载 遇见直播app下载 七仙女直播下载app 菠萝蜜视频下载app 水仙直播app下载 内裤直播下载app视频免费最新 花姬直播下载app 鲍鱼视频下载app 皮卡丘直播下载app 铁牛app下载 千层浪下载app MM直播下载app 樱花雨直播下载app Kitty直播下载app 蜜桃直播app下载 烟花直播app下载 酷咪直播下载app 樱桃视频下载app 青青草app下载 夜猫视频下载app 合欢视频app下载 花心下载app 名优馆app下载 红玫瑰直播下载app 九尾狐视频app下载 火爆社区app下载 s8视频下载app视频免费最新 蝶恋花app下载 秀色小抖音app下载 秀儿直播app下载 花心下载app 荔枝下载app avgo下载app 抖阴直播下载app 夜遇直播号app下载 梦露直播下载app 小v视频下载app视频免费最新 快播破解app下载 小小影视app下载 Avbobo下载app 九尾狐视频下载app 麻豆传媒app下载 草榴视频下载app视频免费最新 樱花直播下载app 成人快手下载app 咪哒app下载 夜夜直播app下载 彩云直播下载app 6房间视频直播app下载 享爱直播下载app AVnight下载app 花心视频下载app 麻豆传媒app下载 主播福利app下载 黄页荔枝下载app视频免费最新 蓝精灵直播下载app 花姿下载app视频免费最新 Kitty直播app下载 七仙女直播app下载 97豆奶视频app下载 抖阴下载app 成人快手下载app 小奶猫下载app 硬汉视频app下载 A头条app下载 斗艳直播app下载 铁牛视频app下载 套路直播app下载 猫咪软件下载app 黄瓜下载app 卡哇伊直播app下载 麻豆传媒直播app下载 皮卡丘直播app下载 千层浪视频下载app 最污直播下载app 7秒鱼app下载 秋葵视频下载app 盘他直播app下载 月亮视频下载app Huluwa下载app 青青草app下载 橘子直播app下载 蜜桃app下载 小天仙直播app下载 本色视频下载app 成人直播app下载 樱花app下载 性福宝下载app Huluwaapp下载 草鱼app下载 抖阴下载app JAV名优馆app下载 彩色直播下载app 猫咪视频下载app 柠檬直播下载app 萝卜视频下载app 本色视频下载app 蝴蝶直播app下载 云雨直播app下载 小猪视频下载app d2天堂下载app 小花螺直播app下载 成版人快手下载app 成版人音色短视频app下载 压寨直播下载app视频免费最新 樱花下载app 香蕉app下载 水晶直播app下载 火爆社区下载app视频免费最新 小草视频下载app 压寨直播下载app视频免费最新 黄瓜视频app下载 玉米视频app下载 年轻人片app下载 花心视频app下载 尤蜜视频app下载 黄瓜直播下载app 蝴蝶直播app下载 烟花直播app下载 富二代f2抖音app下载 享爱app下载 妖妖直播app下载 小草视频下载app 比心下载app 好嗨哟直播app下载 卖肉直播下载app 最污直播app下载 swag台湾app下载 恋夜秀场app下载 咪哒直播下载app 福利直播下载app视频免费最新 铁牛视频下载app 宅男之家下载app 荔枝app下载 望月app下载 冈本下载app视频免费最新 柠檬直播app下载 小公主直播app下载