Affiliation:
1. INMA Bucharest/ Romania
Abstract
The management of inter-row space of vineyards and fruit trees has emerged as an essential approach in sustainable agriculture, optimizing resource use and improving ecosystem services. This paper reviews a range of innovative technologies and solutions aimed at revolutionizing line management practices. Modern sensing and monitoring systems provide real-time data on soil moisture, nutrient levels, and plant health, facilitating precision row-to-row management. Furthermore, techniques for grassing the space between rows of vines and fruit trees are important for space management, ensuring good air circulation and facilitating agricultural activities such as maintenance and harvesting. In addition, the advent of inter-row seeding machines simplified the implementation of cover crops. These machines use advanced seed delivery mechanisms, precisely distributing the cover seed into the spaces between the rows. This not only encourages soil health and erosion prevention but also mitigates weed competition, increasing the overall resilience of the agroecosystem. The purpose of this review is to discuss the combination of state-of-the-art technologies such as 3D LIDAR technology, intelligent systems used for inter-row management of vines and fruit trees, and inter-row solar panel systems, all these examples have revolutionized inter-row management in vineyards and orchards. This holistic approach optimizes resource allocation, improves soil health, and encourages sustainable agricultural practices, paving the way for greener and more resilient inter-row spaces in modern agroecosystems.
Reference43 articles.
1. Aduov M.D., Nukusheva S.A., Kaspakov E. Zh, Isenov K.G., Volodya K.M. and Tulegenov T.K., (2019). Substantiation of constructive parameters of the seeding machine for sowing of non-flowing grass seeds. Mechanization in agriculture & Conserving of the resources, 65(2), pp.50-52. ISSN 2603-3712
2. Andújar D., Moreno H., Bengochea-Guevara J.M., De Castro A. and Ribeiro A., (2019). Aerial imagery or on-ground detection? An economic analysis for vineyard crops. Computers and electronics in agriculture, 157, pp.351-358. https://doi.org/10.1016/j.compag.2019.01.007
3. Biglia A., Zaman S., Gay P., Ricauda A., Comba L. (2022). 3D point cloud density-based segmentation for vine rows detection and localisation, Computers and Electronics in Agriculture, 199, p.107166, https://doi.org/10.1016/j.compag.2022.107166
4. Biglia A., Grella M., Bloise N., Comba L., Mozzanini E., Sopegno A., Pittarello M., Dicembrini E., Alcatrão E., Guglieri G., Balsari P., Ricauda A., Gay P. (2022). UAV-spray application in vineyards: Flight modes and spray system adjustment effects on canopy deposit, coverage, and off-target losses, Science of the Total Environment, 845, p.157292. https://doi.org/10.1016/j.scitotenv.2022.157292
5. Bobillet W., Da Costa J.P., Germain C., Lavialle O., Grenier G., (2003). Row detection in high resolution remote sensing images of vine fields, Precision agriculture Wageningen Academic pp. 81-87 https://doi.org/10.3920/9789086865147_011