Modern Seed Technology

Satisfying the increasing number of consumer demands for high-quality seeds with enhanced performance is one of the most imperative challenges of modern agriculture. In this view, it is essential to remember that the seed quality of crops does not improve

Climate Change Impacts on Agriculture in Europe

COST Action 734 was launched thanks to the coordinated activity of 29 EU countries. The main objective of the Action was the evaluation of impacts from climate change and variability on agriculture for various European areas. Secondary objectives were: collection and review of existing agroclimatic indices and simulation models, to assess hazard impacts on European agricultural areas; to apply climate scenarios for the next few decades; the definition of harmonised criteria to evaluate the impacts of climate change and variability on agriculture; the definition of warning systems guidelines. Based on the result, possible actions (specific recommendations, suggestions, warning systems) were elaborated and proposed to the end-users, depending on their needs

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

On the Use of Unmanned Aerial Systems for Environmental Monitoring

[EN] Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.The present work has been funded by the COST Action CA16219 "HARMONIOUS-Harmonization of UAS techniques for agricultural and natural ecosystems monitoring". B. Toth acknowledges financial support by the Hungarian National Research, Development and Innovation Office (NRDI) under grant KH124765. J. Millerovd was supported by projects GA17-13998S and RVO67985939. Isabel and Jodo de Lima were supported by project HIRT (PTDC/ECM-HID/4259/2014-POCI-0145-FEDER016668).Manfreda, S.; Mccabe, MF.; Miller, PE.; Lucas, R.; Pajuelo Madrigal, V.; Mallinis, G.; Ben Dor, E.... (2018). On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sensing. 10(4):1-28. https://doi.org/10.3390/rs10040641S12810

Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario

Unmanned Aerial Vehicle (UAV) has the capability of acquiring high spatial and temporal resolution images. This new technology fills the data gap between satellite and ground survey in agriculture. In addition, UAV-based crop monitoring and methods are new challenge of remote sensing application in agriculture. First, in my thesis the potential of UAV-based imagery was investigated to monitor spatial and temporal variation of crop status in comparison with RapidEye. The correlation between red-edge indices and LAI and biomass are higher for UAV-based imagery than that of RapidEye. Secondly, the nitrogen weight and yield in wheat was predicted using the UAV-based imagery. The intra-field nitrogen prediction model performs well at wheat early growth stage. Additionally, the best data collection time for yield prediction is at the end of booting stage. The results demonstrate the UAV-based data could be an alternative effective and affordable approach for farmers on intra-field management

Using crop-pathogen modeling to identify plant traits to control Zymoseptoria tritici epidemics on wheat

Diversification in pathogen control methods to reduce the severity of economically important foliar diseases such as Zymoseptoria tritici on wheat is needed. One way is to identify plant physiological and architectural traits that influence disease development and that can be selected in the process of crop breeding. Such traits may be used for improving tolerance or disease escape. Traits favoring disease escape, the focus of our work, may significantly decrease crop epidemics (Robert et al., 2018). However, understanding the role of such traits in crop-pathogen interactions is a daunting task because the interactions are multiple and dynamic in time. To characterize and quantify crop-pathogen interactions, an innovative trait-based and resource-based modeling framework was developed (Precigout et al., 2017). In this framework, the pathosystem is assumed to respond dynamically to both architecture and physiological status of the host canopy. A canopy consists of plenty of small patches, i.e. small functional and infectable units of leaf tissue. Production of new patches, for canopy growth and renewal of photosynthetically active plant tissues, is a function of the available resources produced by the other patches. Pathogen spores can contaminate nearby healthy patches. The definition of patch proximity depends on dispersal abilities of the pathogen and canopy architecture. We used and adapted this modeling framework to quantify the effects of several plant traits on Zymoseptoria tritici epidemics for varied climate scenarios. The complex infection cycle of Z. tritici characterized by a long symptomless incubation period was implemented in the model. We studied plant architectural traits such as leaf size or stem height, and plant physiological traits such as leaf lifespan or leaf metabolite contents. In our simulations, these traits impacted the epidemics dynamics though their effects on pathogen dispersal and on the amount of resources available for the pathogen. Sensitivity analyses showed how disease severity depended on plant traits and pathogen virulence. The importance of several plant and pathogen traits could be linked to the pathogen’s ability to manage the race for the colonization of the canopy in the face of canopy growth. Playing on host traits also made it possible to simulate different wheat varieties - with contrasted heights, pathogen resistance or precocity - to characterize the behavior of the pathosystem of interest for different host ideotypes. We argue that this kind of trait-based modeling approach is a valuable tool to identify plant traits promoting more resilient agroecosystems in particular for crop breeding in a context of innovative and sustainable crop protection