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The profession of the agronomist, in the hundred years of its history, is marked by the evolution of the notion of agriculture. Thus, initially holder of skills inherent to the land relevance of production structures, he finds himself later exercising more articulated tasks congenial to the profound transformation of production activities, once the biological cycle is removed from soil conditioning and the valorisation of the land becomes a qualifying parameter of a multifunctional vocation capable of involving management formulas integrated with the environment. A profession that requires a specialised cultural background but which rejects the fragmentation of knowledge, in a renewed commitment to compose from his point of view, how the agronomist can continue to be an interpreter of the productive leap characterising the sustainable dimension of development, improving the quality of life in the countryside with solutions placed at the service of common goods.

Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers.

Yellow rust in winter wheat is a widespread and serious fungal disease, resulting in significant yield losses globally. Effective monitoring and accurate detection of yellow rust are crucial to ensure stable and reliable wheat production and food security. The existing standard methods often rely on manual inspection of disease symptoms in a small crop area by agronomists or trained surveyors. This is costly, time consuming and prone to error due to the subjectivity of surveyors. Recent advances in unmanned aerial vehicles (UAVs) mounted with hyperspectral image sensors have the potential to address these issues with low cost and high efficiency. This work proposed a new deep convolutional neural network (DCNN) based approach for automated crop disease detection using very high spatial resolution hyperspectral images captured with UAVs. The proposed model introduced multiple Inception-Resnet layers for feature extraction and was optimized to establish the most suitable depth and width of the network. Benefiting from the ability of convolution layers to handle three-dimensional data, the model used both spatial and spectral information for yellow rust detection. The model was calibrated with hyperspectral imagery collected by UAVs in five different dates across a whole crop cycle over a well-controlled field experiment with healthy and rust infected wheat plots. Its performance was compared across sampling dates and with random forest, a representative of traditional classification methods in which only spectral information was used. It was found that the method has high performance across all the growing cycle, particularly at late stages of the disease spread. The overall accuracy of the proposed model (0.85) was higher than that of the random forest classifier (0.77). These results showed that combining both spectral and spatial information is a suitable approach to improving the accuracy of crop disease detection with high resolution UAV hyperspectral images.

Excessive use of nitrogen fertilizer and inappropriate fertilization designs have negative results in agricultural ecosystems, such as considerable nitrogen losses through nitrogen dioxide (NO2) soil leaching and ammonia NH3 volatilization. In addition, climate change, with rising summer temperatures and reduced precipitation, leads to production declines and water shortages in the soil. This review aims to highlight the characteristics of natural zeolite and focus on their multiple uses in agriculture. These minerals are tectosilicates showing an open three-dimensional structure involving the cations required to balance the framework electrostatic charge of aluminum and silicon tetrahedral units. Different research groups reported more than fifty natural zeolites; chabazite, clinoptilolite, phillipsite, erionite, stilbite, heulandite, and mordenite are the most well-known. Zeolites are great tools to help the farmer and agronomist cope with several issues, such as soil or water pollution, contamination by heavy metals, loss of nutrients, and loss of water-use efficiency (WUE) of drylands. These natural crystalline aluminosilicates are considered soil conditioners to improve soil chemical and physical properties, such as saturated hydraulic conductivity (Ks), infiltration rate, cation exchange capacity (CEC), and water-holding capacity (WHC). Owing to their properties, these materials are able to reduce nitrate leaching and ammonia volatilization. Zeolites are also known for their carrying capacity of slow-release macronutrients, micronutrients, and fertilizers. However, the potential of these materials in agricultural areas is apparent, and zeolites show the promise of contributing directly to improve agricultural ecosystems as a sustainable product.

Stomatal regulation is a key determinant of plant photosynthesis and water relations, influencing plant survival, adaptation, and growth. Stomata sense the surrounding environment and respond rapidly to abiotic and biotic stresses. Stomatal conductance to water vapour (g s) and/or transpiration (E) are therefore valuable physiological parameters to be monitored in plant and agricultural sciences. However, leaf gas exchange measurements involve contact with leaves and often interfere with leaf functioning. Besides, they are time consuming and are limited by the sampling characteristics (e.g. sample size and/or the high number of samples required). Remote and rapid means to assess g s or E are thus particularly valuable for physiologists, agronomists, and ecologists. Transpiration influences the leaf energy balance and, consequently, leaf temperature (T leaf). As a result, thermal imaging makes it possible to estimate or quantify g s and E. Thermal imaging has been successfully used in a wide range of conditions and with diverse plant species. The technique can be applied at different scales (e.g. from single seedlings/leaves through whole trees or field crops to regions), providing great potential to study plant–environment interactions and specific phenomena such as abnormal stomatal closure, genotypic variation in stress tolerance, and the impact of different management strategies on crop water status. Nevertheless, environmental variability (e.g. in light intensity, temperature, relative humidity, wind speed) affects the accuracy of thermal imaging measurements. This review presents and discusses the advantages of thermal imaging applications to plant science, agriculture, and ecology, as well as its limitations and possible approaches to minimize them, by highlighting examples from previous and ongoing research.

This study determined the population structure and genome-wide marker-trait association of agronomic traits of wheat for drought-tolerance breeding. Ninety-three diverse bread wheat genotypes were genotyped using the Diversity Arrays Technology sequencing (DArTseq) protocol. The number of days-to-heading (DTH), number of days-to-maturity (DTM), plant height (PHT), spike length (SPL), number of kernels per spike (KPS), thousand kernel weight (TKW) and grain yield (GYLD), assessed under drought-stressed and non-stressed conditions, were considered for the study. Population structure analysis and genome-wide association mapping were undertaken based on 16,383 silico DArTs loci with < 10% missing data. The population evaluated was grouped into nine distinct genetic structures. Inter-chromosomal linkage disequilibrium showed the existence of linkage decay as physical distance increased. A total of 62 significant (P < 0.001) marker-trait associations (MTAs) were detected explaining more than 20% of the phenotypic variation observed under both drought-stressed and non-stressed conditions. Significant (P < 0.001) MTA event(s) were observed for DTH, PHT, SPL, SPS, and KPS; under both stressed and non-stressed conditions, while additional significant (P < 0.05) associations were observed for TKW, DTM and GYLD under non-stressed condition. The MTAs reported in this population could be useful to initiate marker-assisted selection (MAS) and targeted trait introgression of wheat under drought-stressed and non-stressed conditions, and for fine mapping and cloning of the underlying genes and QTL.

Background Oxidation-reduction and acid-base reactions are essential for the maintenance of all living organisms. However, redox potential (Eh) has received little attention in agronomy, unlike pH, which is regarded as a master variable. Agronomists are probably depriving themselves of a key factor in crop and soil science which could be a useful integrative tool. Scope This paper reviews the existing literature on Eh in various disciplines connected to agronomy, whether associated or not with pH, and then integrates this knowledge within a composite framework. Conclusions This transdisciplinary review offers evidence that Eh and pH are respectively and jointly major drivers of soil/plant/microorganism systems. Information on the roles of Eh and pH in plant and microorganism physiology and in soil genesis converges to form an operational framework for further studies of soil/plant/microorganism functioning. This framework is based on the hypothesis that plants physiologically function within a specific internal Eh-pH range and that, along with microorganisms, they alter Eh and pH in the rhizosphere to ensure homeostasis at the cell level. This new perspective could help in bridging several disciplines related to agronomy, and across micro and macro-scales. It should help to improve cropping systems design and management, in conventional, organic, and conservation agriculture.

1. Agricultural intensification reduces ecological resilience of land-use systems, whereas paradoxically, environmental change and climate extremes require a higher response capacity than ever. Adaptation strategies to environmental change include maintenance of shade trees in tropical agroforestry, but conversion of shaded to unshaded systems is common practice to increase short-term yield. 2. In this paper, we review the short-term and long-term ecological benefits of shade trees in coffee Coffea arabica, C. canephora and cacao Theobroma cacao agroforestry and emphasize the poorly understood, multifunctional role of shade trees for farmers and conservation alike. 3. Both coffee and cacao are tropical understorey plants. Shade trees in agroforestry enhance functional biodiversity, carbon sequestration, soil fertility, drought resistance as well as weed and biological pest control. However, shade is needed for young cacao trees only and is less important in older cacao plantations. This changing response to shade regime with cacao plantation age often results in a transient role for shade and associated biodiversity in agroforestry. 4. Abandonment of old, unshaded cacao in favour of planting young cacao in new, thinned forest sites can be named 'short-term cacao boom-and-bust cycle', which counteracts tropical forest conservation. In a 'long-term cacao boom-and-bust cycle', cacao boom can be followed by cacao bust due to unmanageable pest and pathogen levels (e.g. in Brazil and Malaysia). Higher pest densities can result from physiological stress in unshaded cacao and from the larger cacao area planted. Risk-averse farmers avoid long-term vulnerability of their agroforestry systems by keeping shade as an insurance against insect pest outbreaks, whereas yield-maximizing farmers reduce shade and aim at short-term monetary benefits. 5. Synthesis and applications. Sustainable agroforestry management needs to conserve or create a diverse layer of multi-purpose shade trees that can be pruned rather than removed when crops mature. Incentives from payment-for-ecosystem services and certification schemes encourage farmers to keep high to medium shade tree cover. Reducing pesticide spraying protects functional agrobiodiversity such as antagonists of pests and diseases, pollinating midges determining cacao yields and pollinating bees enhancing coffee yield. In a landscape perspective, natural forest along-side agroforestry allows noncrop-crop spillover of a diversity of functionally important organisms. Knowledge transfer between farmers, agronomists and ecologists in a participatory approach helps to encourage a shade management regime that balances economic and ecological needs and provides a 'diversified food-and-cash crop' livelihood strategy.

Endophytic actinobacteria, which exist in the inner tissues of living plants, have attracted increasing attention among taxonomists, ecologists, agronomists, chemists and evolutionary biologists. Numerous studies have indicated that these prolific actinobacteria appear to have a capacity to produce an impressive array of secondary metabolites exhibiting a wide variety of biological activity, such as antibiotics, antitumor and anti-infection agents, plant growth promoters and enzymes, and may contribute to their host plants by promoting growth and enhancing their ability of withstanding the environmental stresses. These microorganisms may represent an underexplored reservoir of novel species of potential interest in the discovery of novel lead compounds and for exploitation in pharmaceutical, agriculture and industry. This review focuses on new findings in the isolation methods, bio- and chemical diversity of endophytic actinobacteria and reveals the potential biotechnological application. The facing problems and strategies for biodiversity research and bioactive natural products producing are also discussed.

Malnutrition—in the form of insufficient energy intakes—affects millions of people worldwide and the negative impact of this kind of hunger is well acknowledged, not least by agronomists trying to increase yields to ensure a sufficient supply of food. This review focuses on another, more particular and “hidden” form of malnutrition, namely mineral malnutrition. It illustrates the burden of disease that is caused by mineral deficiencies and the social and economic consequences they bring about. Mineral malnutrition has a considerable negative impact on individual well-being, social welfare and economic productivity. Agricultural scientists should keep the nutritional qualities of food in mind and—next to optimizing the agricultural properties of crops that are paramount for their adoption by farmers—in particular try to increase the micronutrient content in major staple crops as one way to address vitamin and mineral malnutrition in humans; especially plant breeding approaches promise to be very cost-effective.