Sajad Kiani

910 total citations
28 papers, 699 citations indexed

About

Sajad Kiani is a scholar working on Analytical Chemistry, Biomedical Engineering and Plant Science. According to data from OpenAlex, Sajad Kiani has authored 28 papers receiving a total of 699 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Analytical Chemistry, 11 papers in Biomedical Engineering and 8 papers in Plant Science. Recurrent topics in Sajad Kiani's work include Spectroscopy and Chemometric Analyses (19 papers), Advanced Chemical Sensor Technologies (11 papers) and Smart Agriculture and AI (6 papers). Sajad Kiani is often cited by papers focused on Spectroscopy and Chemometric Analyses (19 papers), Advanced Chemical Sensor Technologies (11 papers) and Smart Agriculture and AI (6 papers). Sajad Kiani collaborates with scholars based in Iran, Netherlands and Italy. Sajad Kiani's co-authors include Saeid Minaei, Mahdi Ghasemi‐Varnamkhasti, Saskia M. van Ruth, Abdolabbas Jafari, L.W.D. van Raamsdonk, Hassan Yazdanpanah, Mahdi Ayyari, S. Kamgar, Javad Feizy and Soleiman Abbasi and has published in prestigious journals such as Scientific Reports, Food Chemistry and Journal of Food Engineering.

In The Last Decade

Sajad Kiani

27 papers receiving 679 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sajad Kiani Iran 15 324 321 141 141 119 28 699
Khalid Tahri Morocco 13 371 1.1× 146 0.5× 193 1.4× 28 0.2× 213 1.8× 15 706
Martina Foschi Italy 13 85 0.3× 175 0.5× 93 0.7× 79 0.6× 108 0.9× 47 445
Magdalena Śliwińska Poland 13 323 1.0× 92 0.3× 170 1.2× 56 0.4× 132 1.1× 17 569
Liwen Jiang China 19 244 0.8× 171 0.5× 473 3.4× 227 1.6× 242 2.0× 67 1.1k
Xuezhen Hong China 12 366 1.1× 214 0.7× 98 0.7× 147 1.0× 103 0.9× 16 611
Laura Aceña Spain 16 465 1.4× 700 2.2× 517 3.7× 170 1.2× 297 2.5× 32 1.3k
Luqing Li China 26 789 2.4× 1.0k 3.2× 344 2.4× 214 1.5× 253 2.1× 56 1.7k
Xinzhe Gu China 17 156 0.5× 245 0.8× 369 2.6× 244 1.7× 189 1.6× 25 898
Nicoletta Sinelli Italy 15 451 1.4× 810 2.5× 335 2.4× 203 1.4× 228 1.9× 17 1.2k
Zhenjiao Du United States 18 65 0.2× 138 0.4× 226 1.6× 167 1.2× 405 3.4× 28 892

Countries citing papers authored by Sajad Kiani

Since Specialization
Citations

This map shows the geographic impact of Sajad Kiani'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 Sajad Kiani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sajad Kiani more than expected).

Fields of papers citing papers by Sajad Kiani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sajad Kiani. 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 Sajad Kiani. The network helps show where Sajad Kiani may publish in the future.

Co-authorship network of co-authors of Sajad Kiani

This figure shows the co-authorship network connecting the top 25 collaborators of Sajad Kiani. A scholar is included among the top collaborators of Sajad Kiani 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 Sajad Kiani. Sajad Kiani 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.
Kiani, Sajad, et al.. (2025). AI-powered computer vision system for veal-mutton minced meat authenticity evaluation. Journal of Food Engineering. 410. 112920–112920.
2.
Kiani, Sajad, et al.. (2025). Integration of Hyperspectral Imaging System and Machine Learning to Predict Amylose Content in Rice. Cereal Chemistry. 102(3). 671–680. 1 indexed citations
3.
Izadi, Zahra & Sajad Kiani. (2024). Pomegranate molasses authentication using hyperspectral imaging system coupled with automatic clustering algorithm. Journal of Food Science. 89(7). 4216–4228. 1 indexed citations
4.
Kiani, Sajad, et al.. (2023). Aroma modeling and quality evaluation of spearmint (Mentha spicata subsp. spicata) using electronic nose technology coupled with artificial intelligence algorithms. Journal of Applied Research on Medicinal and Aromatic Plants. 35. 100473–100473. 10 indexed citations
5.
Kiani, Sajad, Hassan Yazdanpanah, & Javad Feizy. (2023). Geographical origin differentiation and quality determination of saffron using a portable Hyperspectral imaging system. Infrared Physics & Technology. 131. 104634–104634. 23 indexed citations
6.
Haute, Sam Van, et al.. (2023). Prediction of essential oil content in spearmint (Mentha spicata) via near-infrared hyperspectral imaging and chemometrics. Scientific Reports. 13(1). 4261–4261. 6 indexed citations
7.
Ghasemi‐Varnamkhasti, Mahdi, et al.. (2023). Identifying the authenticity and geographical origin of rice by analyzing hyperspectral images using unsupervised clustering algorithms. Journal of Food Composition and Analysis. 125. 105737–105737. 11 indexed citations
8.
Kiani, Sajad, et al.. (2019). PTR-QiToF-MS and HSI for the characterization of fermented cocoa beans from different origins. Food Chemistry. 289. 591–602. 22 indexed citations
9.
Kiani, Sajad, Saeid Minaei, & Mahdi Ghasemi‐Varnamkhasti. (2018). Real-time aroma monitoring of mint (Mentha spicata L.) leaves during the drying process using electronic nose system. Measurement. 124. 447–452. 50 indexed citations
10.
Kiani, Sajad, Saeid Minaei, Mahdi Ghasemi‐Varnamkhasti, & Mahdi Ayyari. (2017). An original approach for the quantitative characterization of saffron aroma strength using electronic nose. International Journal of Food Properties. 20(sup1). S673–S683. 17 indexed citations
11.
Kiani, Sajad & Saeid Minaei. (2016). Potential application of machine vision technology to saffron (Crocus sativus L.) quality characterization. Food Chemistry. 212. 392–394. 13 indexed citations
12.
Kiani, Sajad, et al.. (2015). Computer vision system coupled with an Artificial Neural Network to rainbow trout eggs quality evaluation.. 3(10). 235–242. 2 indexed citations
13.
Kiani, Sajad, Saeid Minaei, & Mahdi Ghasemi‐Varnamkhasti. (2015). Fusion of artificial senses as a robust approach to food quality assessment. Journal of Food Engineering. 171. 230–239. 72 indexed citations
14.
Kiani, Sajad. (2012). Discriminating The Corn Plants From The Weeds By Using Artificial Neural Networks. DergiPark (Istanbul University). 3 indexed citations
15.
Kiani, Sajad & Abdolabbas Jafari. (2012). Crop Detection and Positioning in the Field Using Discriminant Analysis and Neural Networks Based on Shape Features. Journal of Agricultural Science and Technology. 14(4). 755–765. 27 indexed citations
16.
Kiani, Sajad, et al.. (2012). Machine Vision and Soil Trace-based Guidance-Assistance System for Farm Tractors in Soil Preparation Operations. Journal of Agricultural Science. 4(7). 3 indexed citations
17.
Kiani, Sajad & S. Kamgar. (2011). Application of Co-occurrence Matrix on Wavelet Coefficients for Crop-weed Discrimination. DergiPark (Istanbul University). 3 indexed citations
18.
Kiani, Sajad, Zohreh Azimifar, & S. Kamgar. (2010). Wavelet-based crop detection and classification. 587–591. 2 indexed citations
19.
Kiani, Sajad, et al.. (2010). Automatic On-Line Depth Control of Seeding Units Using a Non-Contacting Ultrasonic Sensor. DergiPark (Istanbul University). 13 indexed citations
20.
Abbasi, Soleiman, et al.. (2009). Effect of Time and Temperature on Moisture Content, Shrinkage, and Rehydration of Dried Onion. 6(3). 57–70. 25 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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