![](\"http:\/\/www.agrolink.com.br\/upload\/imagens-resizes\/f03a44328bb549a7b8f3f49c6bd0f73c_858x483.jpg\")
<\/p>\n<\/p>\n
The use of Drones<\/a> Equipped with multispectral and thermal sensors, they are transforming crop phenotyping and increasing the precision of genetic improvement programs. According to data released by the Argentine government, researchers at INTA Pergamino have already obtained significant results in... soy<\/a>, sunflower<\/a>, wheat<\/a> and corn<\/a>, with particular emphasis on models capable of exceeding 92% precision in commercial corn hybrids.\n<\/p>\n The technology was incorporated by the INTA Pergamino Agricultural Experimental Station (EEA) as part of the National Ecophysiology and Agroecosystems Program. The aim is to reduce the time spent on field assessments and establish objective and repeatable protocols for remote data processing.<\/p>\n According to data released by the Argentine government, the initiative brings together the areas of Geographic Information Systems (GIS), Crop Ecophysiology, Sunflower Breeding, and Corn Breeding from the experimental station. The work also involves interaction with the Experimental Stations in the region through the INTA National Drone Network.<\/p>\n Traditionally, genetic improvement trials are evaluated manually. According to data released by the Argentine government, this method is time-consuming and can introduce subjectivity into the observations made by the operators.<\/p>\n In this scenario, remote sensors allow for the objective and repeatable estimation of plant characteristics, considering the interaction between genotype and environment.<\/p>\n \u201cThis development was consolidated through an associative scheme that internally links the areas of Geographic Information Systems (GIS), Crop Ecophysiology, Sunflower Breeding, and Corn Breeding at the experimental station,\u201d explained Javier Portillo, a researcher at the INTA Pergamino Experimental Station.<\/p>\n "In turn, the synergy of work extends to the federal level through interaction with the Experimental Stations in the region, via the INTA National Drone Network," he added.<\/p>\n According to data released by the Argentine government, scheduled flights were conducted throughout the soybean growth cycle to monitor the evolution of leaf cover. The methodology also allowed for estimating plant height with a margin of error of less than 8% compared to manual measurements. "In soybeans, through scheduled flights throughout the growth cycle, it was possible to estimate the evolution of leaf cover, making it possible to measure plant height with a margin of error of less than 8% compared to manual measurements," explained Portillo.\n<\/p>\n In the sunflower field, images obtained by drones were combined with artificial intelligence algorithms, including machine learning techniques. The goal was to automate the detection of hybrids resistant to commercial herbicides and expand the number of plots evaluated simultaneously.<\/p>\n In wheat, researchers have initiated a line of investigation focused on using specific vegetation indices to monitor the drying rate of grains before harvest, a characteristic related to cereal quality.<\/p>\n Technology is also advancing in corn.<\/p>\n The latest results related to corn will be presented at the XIII National Corn Congress. According to data released by the Argentine government, two studies led by Jos\u00e9 Menes, from the SIG group, focus exclusively on the crop. The first study evaluated the estimation of plant height from digital surface models (DSMs) produced with drone images. The methodology achieved agreement between 81% and 86% in relation to traditional manual measurements.<\/p>\n Estimating plant height can contribute to evaluating crop structure and anticipating problems such as stem breakage and lodging, factors associated with losses during harvest. The second research project developed mathematical models to estimate the fraction of solar radiation intercepted by plants, a variable related to biomass production and yield.<\/p>\n According to data released by the Argentine government, researchers analyzed more than 60 indicators. The percentage of green cover estimated from the atmosphere outperformed traditional digital agriculture indices as a predictor of the fraction of radiation intercepted by the crop. The NDVI, an index widely used in digital agriculture, also showed the ability to adequately explain the variable, but it was not among the indicators with the highest predictive capacity.\n<\/p>\n Artificial intelligence expands the scale of trials.<\/p>\n The results obtained reinforce the potential of drones to accelerate evaluations in genetic improvement programs. In the case of corn, according to data released by the Argentine government, the models achieved accuracy greater than 92% in commercial hybrids and 86% in lines. \u201cIn contrast, remote sensors are emerging as a strategic alternative. The use of these sensors allows for a completely objective and repeatable estimation over time of plant characteristics that arise from the interaction between genotype and environment,\u201d stated Portillo.<\/p>\n The researcher also highlighted that technological advancements allow for an increase in the number of plots evaluated and a reduction in reliance on manual observations. \u201cAlthough the United States is not a member of Fontagro, thanks to Eugenia, we can participate,\u201d stated Carlos Messina, director of the UF\/IFAS Center for Crop Transformation at the University of Florida, regarding the institution's participation in another initiative related to agricultural research.<\/p>\n Overall, the results presented by INTA Pergamino indicate that the use of drones, remote sensors, and artificial intelligence expands the capacity for collecting and processing information in the field, with applications focused on genetic selection and monitoring crop performance.<\/p>\n<\/p><\/div>\n\n<\/div>\n\n<\/div>\n\n<\/div>\n\n<\/div>\n\n<\/div>\nTHE MM Cereais<\/strong> works with the best grains on the market and also keeps you up to date with the latest news and analyses on agribusiness.
\nDon't forget to follow our social networks.<\/em><\/h6>\n