Can Yield Prediction Be Fully Digitilized? A Systematic Review

Going beyond previous work, this paper presents a systematic literature review that explores the deployment of satellites, drones, and ground-based sensors for yield prediction in agriculture. It covers multiple aspects of the topic, including crop types, key sensor platforms, data analysis techniques, and performance in estimating yield. To this end, datasets from Scopus and Web of Science were analyzed, resulting in the full review of 269 out of 1429 retrieved publications. Our study revealed that China (93 articles, >1800 citations) and the USA (58 articles, >1600 citations) are prominent contributors in this field; while satellites were the primary remote sensing platform (62%), followed by airborne (30%) and proximal sensors (27%). Additionally, statistical methods were used in 157 articles, and model-based approaches were utilized in 60 articles, while machine learning and deep learning were employed in 142 articles and 62 articles, respectively. When comparing methods, machine learning and deep learning methods exhibited high accuracy in crop yield prediction, while other techniques also demonstrated success, contingent on the specific crop platform and method employed. The findings of this study serve as a comprehensive roadmap for researchers and farmers, enabling them to make data-driven decisions and optimize agricultural practices, paving the way towards a fully digitized yield prediction

X-Ray Crystallographic Analysis, EPR Studies, and Computational Calculations of a Cu(II) Tetramic Acid Complex

In this work we present a structural and spectroscopic analysis of a copper(II) N-acetyl-5-arylidene tetramic acid by using both experimental and computational techniques. The crystal structure of the Cu(II) complex was determined by single crystal X-ray diffraction and shows that the copper ion lies on a centre of symmetry, with each ligand ion coordinated to two copper ions, forming a 2D sheet. Moreover, the EPR spectroscopic properties of the Cu(II) tetramic acid complex were also explored and discussed. Finally, a computational approach was performed in order to obtain a detailed and precise insight of product structures and properties. It is hoped that this study can enrich the field of functional supramolecular systems, giving place to the formation of coordination-driven self-assembly architectures

Precision farming technologies for crop protection: A meta-analysis

Precision farming technologies (PFTs) can have a significant impact on reducing the dependency on plant protection products (PPP) for crop protection. PFTs for crop protection comprises an extensive suite of digital solutions that can be used to predict, detect, and control pests. In this paper, we report the results of a systematic literature meta-analysis to map PFTs in relation to crop protection and identify trends and gaps in the use of these technologies in order for them to be easily adopted by farmers. In total, 239 different research articles were assessed in terms of sensor, platform, crop, pest, pest management stage, and impact type. The majority of research articles focused on arable crops and on weed management. The identified PFTs can achieve up to 97 % savings in herbicides, reduce the area that needs insecticide application by up to 70 %, and reduce weed densities by 89 %. In the future, high resolutions images and proximal sensing with heterogeneous robotic systems is expected to make pest detection and control more efficient

Genetic Analysis and Status of Brown Bear Sub-Populations in Three National Parks of Greece Functioning as Strongholds for the Species’ Conservation

In order to optimize the appropriate conservation actions for the brown bear (Ursus arctos L.) population in Greece, we estimated the census (Nc) and effective (Ne) population size as well as the genetic status of brown bear sub-populations in three National Parks (NP): Prespa (MBPNP), Pindos (PINDNP), and Rhodopi (RMNP). The Prespa and Pindos sub-populations are located in western Greece and the Rhodopi population is located in eastern Greece. We extracted DNA from 472 hair samples and amplified through PCR 10 microsatellite loci. In total, 257 of 472 samples (54.5%) were genotyped for 6–10 microsatellite loci. Genetic analysis revealed that the Ne was 35, 118, and 61 individuals in MBPNP, PINDNP, and RMNP, respectively, while high levels of inbreeding were found in Prespa and Rhodopi but not in Pindos. Moreover, analysis of genetic structure showed that the Pindos population is genetically distinct, whereas Prespa and Rhodopi show mutual overlaps. Finally, we found a notable gene flow from Prespa to Rhodopi (10.19%) and from Rhodopi to Prespa (14.96%). Therefore, targeted actions for the conservation of the bears that live in the abovementioned areas must be undertaken, in order to ensure the species’ viability and to preserve the corridors that allow connectivity between the bear sub-populations in Greece