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Agronomy
Special Issues
Agriculture 4.0 as a Sustainability Driver
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Agriculture 4.0 as a Sustainability Driver

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Agricultural Biosystem and Biological Engineering".

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 5128

Special Issue Editors

Prof. Dr. Hernâni Gerós

E-Mail Website1 Website2 Website3
Guest Editor
Department of Biology, Universidade do Minho, Braga, Portugal
Interests: plant molecular physiology; plant-environment interaction; grape and wine; food science
Special Issues, Collections and Topics in MDPI journals
Dr. Natacha Fontes

E-Mail Website
Guest Editor
Sogrape Vinhos S.A., Vila Nova de Gaia, Portugal
Interests: grape; cell biology; genetics; biochemistry; biotechnology; sustainability; agroecology; circular economy; precision and digital agriculture

Special Issue Information

Dear Colleagues,

In a global scenario of increasing environmental and economic pressure, agriculture is facing many challenges. In particular, climate change is likely to mean lower yields, increased pests and diseases and food insecurity. Henceforth, to achieve the food production requirements for the growing world population, which is predicted to reach 10 billion people by 2050, there is an urgent need to implement farming practices based on a new paradigm, integrating automation, artificial intelligence and digitalization for eco-friendly sustainable crop production, including weeding and pest control. In this way, traditional agriculture based on engine power will be assisted with precision by automated equipment and robotics (FAO). The challenge is to provide better knowledge to support the increase in crop system yield production, at high-quality standards, while seeking the maintenance of biodiversity with a long-term view and cost-efficient strategies.

The aim of this Special Issue is to assemble innovative research on sustainable approaches for agricultural management in the context of Agriculture 4.0 aiming at the profitability of conserved and restored ecosystems. Original research articles and concepts for review articles to address major issues are welcome.

Prof. Dr. Hernâni Gerós
Dr. Natacha Fontes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision agriculture
  • sensors
  • decision-making tools
  • digital transformation
  • productive efficiency
  • mechanization and robotics
  • crop yield
  • monitoring and modelling
  • resilience
  • sustainable ecosystems
  • biodiversity
  • early detection of plagues and diseases
  • functional biodiversity
  • integrated strategies to reduce the use and impact of pesticides

Published Papers (2 papers)

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Research

10 pages, 1318 KiB  
Communication
Light Traps to Study Insect Species Diversity in Soybean Crops
by Alexey Pachkin, Oksana Kremneva, Daniil Leptyagin, Artem Ponomarev and Roman Danilov
Agronomy 2022, 12(10), 2337; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12102337 - 28 Sep 2022
Cited by 2 | Viewed by 2608
Abstract
We aimed to monitor the species diversity and the dynamics of the number of soybean pests using light traps with an original design to develop protection systems against the main phytophages. Traps lured 44 species of insects from eight orders and 27 families. [...] Read more.
We aimed to monitor the species diversity and the dynamics of the number of soybean pests using light traps with an original design to develop protection systems against the main phytophages. Traps lured 44 species of insects from eight orders and 27 families. The capture of 15 species of economically important phytophages was recorded—representatives of various orders and families: order Lepidoptera—Noctuidae, Crambidae, Erebidae, and Geometridae; order Hemiptera—Flatidae; order Coleoptera—Elateridae, etc. Insect identification was carried out via morphological methods. Over the study period (93 days), 4955.41 insect specimens were caught on average per one trap. Most of the attracted insects belong to harmful entomofauna: namely the cotton bollworm (Helicoverpa armigera, Hübner)—58.9%, the beet webworm (Loxostege sticticalis, L.)—12.74%, the nutmeg moth (Anarta trifolii, Hufnagel)—6.5%, the European corn borer (Ostrinia nubilalis, Hübner)—2.68%, and some other species—19.2%. In addition to economically significant phytophages, we registered some indifferent and beneficial species. The summer dynamics of the cotton bollworm and the nutmeg moth were obtained for the entire research period. Then, we calculated the values of the indices of biodiversity and the dominance of insect species. An analysis of the index values allows us to conclude a balanced entomocomplex at the research site. Full article
(This article belongs to the Special Issue Agriculture 4.0 as a Sustainability Driver)
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20 pages, 4051 KiB  
Article
Comparing a New Non-Invasive Vineyard Yield Estimation Approach Based on Image Analysis with Manual Sample-Based Methods
by Gonçalo Victorino, Ricardo P. Braga, José Santos-Victor and Carlos M. Lopes
Agronomy 2022, 12(6), 1464; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12061464 - 18 Jun 2022
Cited by 4 | Viewed by 1890
Abstract
Manual vineyard yield estimation approaches are easy to use and can provide relevant information at early stages of plant development. However, such methods are subject to spatial and temporal variability as they are sample-based and dependent on historical data. The present work aims [...] Read more.
Manual vineyard yield estimation approaches are easy to use and can provide relevant information at early stages of plant development. However, such methods are subject to spatial and temporal variability as they are sample-based and dependent on historical data. The present work aims at comparing the accuracy of a new non-invasive and multicultivar, image-based yield estimation approach with a manual method. Non-disturbed grapevine images were collected from six cultivars, at three vineyard plots in Portugal, at the very beginning of veraison, in a total of 213 images. A stepwise regression model was used to select the most appropriate set of variables to predict the yield. A combination of derived variables was obtained that included visible bunch area, estimated total bunch area, perimeter, visible berry number and bunch compactness. The model achieved an R2 = 0.86 on the validation set. The image-based yield estimates outperformed manual ones on five out of six cultivar data sets, with most estimates achieving absolute errors below 10%. Higher errors were observed on vines with denser canopies. The studied approach has the potential to be fully automated and used across whole vineyards while being able to surpass most bunch occlusions by leaves. Full article
(This article belongs to the Special Issue Agriculture 4.0 as a Sustainability Driver)
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