V. Alchanatis

6.6k total citations
126 papers, 5.0k citations indexed

About

V. Alchanatis is a scholar working on Plant Science, Ecology and Analytical Chemistry. According to data from OpenAlex, V. Alchanatis has authored 126 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Plant Science, 42 papers in Ecology and 36 papers in Analytical Chemistry. Recurrent topics in V. Alchanatis's work include Remote Sensing in Agriculture (39 papers), Spectroscopy and Chemometric Analyses (36 papers) and Smart Agriculture and AI (25 papers). V. Alchanatis is often cited by papers focused on Remote Sensing in Agriculture (39 papers), Spectroscopy and Chemometric Analyses (36 papers) and Smart Agriculture and AI (25 papers). V. Alchanatis collaborates with scholars based in Israel, United States and Greece. V. Alchanatis's co-authors include Yafit Cohen, M. Meron, Thomas F. Burks, J. Tsipris, Duke M. Bulanon, V. Ostrovsky, Won Suk Lee, Yehoshua Saranga, David J. Bonfil and Arnon Karnieli and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and PLANT PHYSIOLOGY.

In The Last Decade

V. Alchanatis

125 papers receiving 4.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
V. Alchanatis Israel 39 3.1k 1.9k 1.2k 921 750 126 5.0k
Yanbo Huang United States 37 3.0k 1.0× 2.7k 1.4× 989 0.8× 803 0.9× 1.1k 1.5× 166 5.7k
Nicolas Tremblay Canada 38 4.1k 1.3× 3.0k 1.6× 1.0k 0.8× 670 0.7× 1.2k 1.6× 149 6.6k
V. González-Dugo Spain 35 2.6k 0.8× 2.5k 1.3× 1.7k 1.4× 400 0.4× 1.0k 1.4× 65 4.3k
Chunjiang Zhao China 45 3.8k 1.2× 3.2k 1.7× 1.0k 0.8× 1.3k 1.4× 1.8k 2.4× 418 7.7k
Raffaele Casa Italy 32 1.6k 0.5× 1.7k 0.9× 696 0.6× 366 0.4× 1.2k 1.6× 108 3.4k
Paulo Eduardo Teodoro Brazil 30 2.6k 0.8× 1.3k 0.7× 1.0k 0.8× 452 0.5× 450 0.6× 471 4.6k
Felix Fritschi United States 37 4.5k 1.4× 1.8k 0.9× 655 0.5× 356 0.4× 897 1.2× 167 6.5k
José A. Jiménez-Berni Spain 29 2.8k 0.9× 3.2k 1.7× 1.5k 1.3× 373 0.4× 1.9k 2.5× 49 5.2k
Yubin Lan China 47 5.2k 1.7× 2.1k 1.1× 453 0.4× 740 0.8× 1.2k 1.6× 394 7.7k
Zhenhai Li China 45 3.1k 1.0× 4.3k 2.3× 1.3k 1.1× 839 0.9× 2.1k 2.8× 207 6.9k

Countries citing papers authored by V. Alchanatis

Since Specialization
Citations

This map shows the geographic impact of V. Alchanatis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by V. Alchanatis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. Alchanatis more than expected).

Fields of papers citing papers by V. Alchanatis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by V. Alchanatis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by V. Alchanatis. The network helps show where V. Alchanatis may publish in the future.

Co-authorship network of co-authors of V. Alchanatis

This figure shows the co-authorship network connecting the top 25 collaborators of V. Alchanatis. A scholar is included among the top collaborators of V. Alchanatis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with V. Alchanatis. V. Alchanatis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Alchanatis, V., et al.. (2025). UAV-borne hyperspectral and thermal imagery integration empowers genetic dissection of wheat stomatal conductance. Computers and Electronics in Agriculture. 235. 110411–110411. 2 indexed citations
2.
Peeters, Aviva, Yafit Cohen, Noa Ohana‐Levi, et al.. (2024). A spatial machine-learning model for predicting crop water stress index for precision irrigation of vineyards. Computers and Electronics in Agriculture. 227. 109578–109578. 5 indexed citations
3.
Netzer, Yishai, José M. Grünzweig, A. Naor, et al.. (2024). How do spatial scale and seasonal factors affect thermal-based water status estimation and precision irrigation decisions in vineyards?. Precision Agriculture. 25(3). 1477–1501. 6 indexed citations
4.
Sperling, Or, Tal Rapaport, V. Alchanatis, Ze’ev Schmilovitch, & Uri Yermiyahu. (2023). Measuring foliar mineral concentrations by X-ray fluorescence requires crop-specific partial regression models. Journal of Analytical Atomic Spectrometry. 38(8). 1691–1703. 1 indexed citations
5.
Ben‐Gal, Alon, M. Iggy Litaor, A. Naor, et al.. (2023). How Sensitive Is Thermal Image-Based Orchard Water Status Estimation to Canopy Extraction Quality?. Remote Sensing. 15(5). 1448–1448. 5 indexed citations
6.
Alchanatis, V., et al.. (2022). Canopy-cooling systems applied on avocado trees to mitigate heatwaves damages. Scientific Reports. 12(1). 12563–12563. 5 indexed citations
7.
Bar-Hillel, Aharon, et al.. (2019). Detection and counting of flowers on apple trees for better chemical thinning decisions. Precision Agriculture. 21(3). 503–521. 88 indexed citations
8.
Alchanatis, V., Tímea Ignát, H. Egozi, et al.. (2015). Machinery for Fresh Cut Watermelon and Melon. SHILAP Revista de lepidopterología. 1 indexed citations
9.
Ignát, Tímea, et al.. (2015). Sensor Fusion for Maturity Prediction of Pepper. SHILAP Revista de lepidopterología. 1 indexed citations
10.
Kelly, Gilor, Nir Sade, Ziv Attia, et al.. (2014). Relationship between Hexokinase and the Aquaporin PIP1 in the Regulation of Photosynthesis and Plant Growth. PLoS ONE. 9(2). e87888–e87888. 38 indexed citations
11.
Edan, Yael, V. Alchanatis, U. Moallem, et al.. (2013). Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors. Journal of Dairy Science. 96(12). 8047–8059. 61 indexed citations
12.
Moulin, A., Y. Cohen, V. Alchanatis, Nicolas Tremblay, & K. M. Volkmar. (2012). Yield response of potatoes to variable nitrogen management by landform element and in relation to petiole nitrogen - A case study. Canadian Journal of Plant Science. 92(4). 771–781. 7 indexed citations
13.
Alchanatis, V., et al.. (2011). Multimodal remote sensing for enhancing detection of spatial variability in agricultural fields. Aisberg (University of Bergamo). 1–4. 2 indexed citations
14.
Ben‐Gal, Alon, Dilia Kool, Nurit Agam, et al.. (2010). Whole-tree water balance and indicators for short-term drought stress in non-bearing ‘Barnea’ olives. Agricultural Water Management. 98(1). 124–133. 64 indexed citations
15.
Gal, Shira, et al.. (2010). Determining an economic injury level for the persea mite, Oligonychus perseae, a new pest of avocado in Israel. Entomologia Experimentalis et Applicata. 138(2). 110–116. 20 indexed citations
16.
Weintraub, Phyllis G., et al.. (2007). Factors affecting the distribution of a predatory mite on greenhouse sweet pepper. Experimental and Applied Acarology. 42(1). 23–35. 28 indexed citations
17.
Möller, Matthias, V. Alchanatis, Yuval Cohen, et al.. (2006). Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. Journal of Experimental Botany. 58(4). 827–838. 346 indexed citations
18.
Cohen, Yafit, V. Alchanatis, M. Meron, Yehoshua Saranga, & J. Tsipris. (2005). Estimation of leaf water potential by thermal imagery and spatial analysis*. Journal of Experimental Botany. 56(417). 1843–1852. 281 indexed citations
19.
Cohen, Y., V. Alchanatis, M. Meron, Yehoshua Saranga, & D. J. Mulla. (2004). Mapping of leaf water potential using thermal images for site-specific irrigation.. 1090–1102. 1 indexed citations
20.
Alchanatis, V., et al.. (2002). A Machine Vision System for Evaluation of Planter Seed Spatial Distribution. eCommons (Cornell University). 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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