b'PARTNER CONTENTThere IS a Better Way: Drone Advances Drive Crop Breeding InnovationBy: Lee WestT heres got to be a better way! This is a phrase uttered in many languages ev-ery day across the globe by crop researchers walking through fields assessing plots by eye and by hand. Ive uttered this phrase myself many times when doing assessments or reviewing data sets that I was trying to merge between different trials. In a previous role as global agronomy manager for Novo-zymes, I was responsible for coordinating thousands of biologi-cal product trials across the globe. One of our major hurdles to mining the data from the trials to its full potential was the fact that qualitative assessments are not principled enough to be interoperable.Basically, each person doing the assessments had different enough rating scales that there was too much noise in the data to confidently identify treatment/germplasm differences and attribute entry, environmental or soil impacts as we required.In the 20-teens, the drone era began to emerge, giving crop researchers a new technology that hinted at solving some of fieldpick up many insights into varietal differences, we lack adequate data collections most challenging problems. Early drones wereability to measure the reflectance of different wavelengths of expensive and difficult to operate (likely to crash). The tools tolight to give insights into varietal differences in a principled and stitch imagery and to georeference and extract traits were veryrepeatable way. Thats where drone-based imagery excels. And, immature and difficult to find and operate. Luckily, that haswith proper flight mission protocols, researchers can also extract changed as drone technologies have advanced.architectural data like crop height and volume. Theres more: advances in deep learning have allowed advanced counting and Todays drones allow high-throughput phenotypingclassification of plant features from corn stand counts to tomato Drone operational efficiency has now advanced to the pointfruit maturity ratings. And, on the horizon are classification tools where any researcher can afford and operate their own drone.to infer stress types like disease, pest, drought and heat.This means the ability to collect ever increasing quantities of phe-notypic data is now accessible to any researcher pursuing highYield estimationthe phenome frontierthroughput phenotyping. The age-old breeders dilemma has been interpreting how pheno-However, the tools to extract data from the imagery havetypic assessments can contribute and even drive variety advance-developed more slowly for agriculture researchers because of thement decisions. Phenotyping is labor intensive and training specificity of need and agricultures relatively small market com- intensive, so historically there have not been many assessments pared to public utilities, mining and public safety applications.acquired per season.With drones many pieces of information can be collected quickly and repeatably through the season. Extracting data Already, the application and utility of drone-based imagery is Even today, it is challenging for individual researchers to developenormous. That will only grow as ever-improving technologies and maintain their own pipelines to extract novel insights into thesupport even more advanced data collection and data extraction.crops they are developing. It was this very need that convinced remote sensing expert Alexis Comar to create Hiphenthe leadingLee West is Business Development Director for Hiphen Agricultural global agricultural imaging solutions organizationin 2014.Imaging Solutions. He is committed to developing tools that help Coming out of my PhD work on phenotyping leaf/light inter- researchers contribute to the agricultural challenges of the 21st actions with remote sensing, I recognized the value of develop- century. ing tools that were scalable so that I could help other researchers extract traits from imaging systems in a high throughput way, heThis article is the first in a four-part series on how drones have be-says.come a critical tool in the toolchests of crop breeders. The next three will focus on: 1. Image acquisition with drones, 2. Data extraction Drones dont replace researchers; they support themfrom drone imagery and 3. Putting that data to work informing Though the human eye and interpretation engine (the brain)advancement decisions.DECEMBER 2023SEEDWORLD.COM /41'