برآورد میزان اکسید پتاسیم در کود پتاس با استفاده از روش‌های پردازش تصویر فراطیفی و یادگیری ماشین

Ahmad, Z., Anjum, S., Waraich, E.A., Ayub, M.A., & Ahmad, T. (2018). Growth, physiology, and biochemical activities of plant responses with foliar potassium application under drought stress–a review, Journal of Plant Nutrition 41, 1734–1743.

Patiluna, V., Owen, J., Jr., Maja, J.M., Neupane, J., Behmann, J., Bohnenkamp, D., Borra-Serrano, I., Peña, J.M., Robbins, J., & de Castro, A. (2025). Using Hyperspectral Imaging and Principal Component Analysis to Detect and Monitor Water Stress in Ornamental Plants. Remote Sens, 17, 285. https://doi.org/10.3390/rs17020285.

Arif Chaudhry, M.M., Bane, M., McAllister, T., Paliwal, J., & Narváez-Bravo, C. (2025). Identification and Classification of Multi-Species Biofilms on Polymeric Surfaces Using Hyperspectral Imaging. Journal of Food Safety. 45: e70008. https://doi.org/10.1111/jfs.70008.

Arjomandi, H.R., Kheiralipour, K., & Amarloei, A. (2022). Estimation of dust concentration by a novel machine vision system. Scientific Reports, 12(1), 1-8.

Azadnia, R., & Kheiralipour, K. (2022). Evaluation of hawthorns maturity level by developing an automated machine learning-based algorithm. Ecological Informatics, 71, 101804. https://doi.org/10.1016/j.ecoinf.2022.101804.

Barbosa, M.C., Fernandes, G.C., Lima, B.H., Rosa, L.G.P., Ito, W.C.N., Souza, L.F.R.d., Jalal, A., Nogueira, T.A.R., Oliveira, C.E.d.S., & Ghaley, B.B. (2025). The Effects of Potassium Dose, Timing, and Source in Soybean Crops in Brazilian Savannah Oxisol. Sustainability, 17, 934. https://doi.org/10.3390/su17030934.

Brunetto, G., Marques, A., Martins, A., Miotto, A., Tiecher, T., Tiecher, T., Pias, O., Ambrosini, V., Ferreira, P., & Souza da Silva, L. (2022). Fertilidade do solo e nutric.o para cultura da soja. In Tecnologias Aplicadas para o Manejo Rentavel e Eficiente da Cultura da Soja; GR: Santa Maria, CA, USA, pp. 11–46. ISBN 9786589469575.

Efraim, I., Holdengraber, C., & Lampert, S. (1996). U. S. Patent No. 5552126, Washington, D.C.: U.S. Patent and Trademark Office.

ElMasry, G., Kamruzzaman, M., Sun, D. W., & Allen, P. (2012). Principles and applications of hyperspectral imaging in quality evaluation of agro food products: a review. Crit. Rev. Food Sci. Nutr., 52(11), 999-1023.

Esa, N., Masarudin, M.F., Saad, M.M., & Misman, S.N. (2025). Determine the Balance of Nitrogen, Potassium, and Silicon Fertilization for the Control of Rice Tungro Disease Using Response Surface Methodology. Natural and Life Sciences Communications. 24(1): e2025002.

Farokhzad, S., Modares Motlagh, A., Ahmadi Moghadam, P., Jalali Honarmand, S., & Kheiralipour, K. (2020). Application of infrared thermal imaging technique and discriminant analysis methods for non-destructive identification of fungal infection of potato tubers. Journal of Food Measurement and Characterization. 14(1): 88-94.

Fernandez, L.C., Allende-Prieto, J., & Peon, E. (2019). Preliminary Assessment of Visible, Near-Infrared, and Short-Wavelength–Infrared Spectroscopy with a Portable Instrument for the Detection of Staphylococcus aureus Biofilms on Surfaces. Journal of Food Protection. 82, no. 8: 1314–1319. https://doi.org/10.4315/0362-028X. JFP-18-567.

Giambra, M.A. (2005). Application of ion chromatography to qualitative and quantitative determination of the main inorganic ionic components of samples from a production process of potassium sulphate, Analytica Chimica Acta, 530, 41–48, https://doi.org/10.1016/J.ACA.2004.08.047.

Gili, M., Ashourloo, D., Aghighi, H., Motakan, A., & Shakiba, A. (2021). Classification of agricultural products with deep convolutional network based on product index. Quarterly Journal of Environmental Sciences, Volume 20, Issue 4, 37-52. http://dx.doi.org/10.48308/envs.2022.1126.

Gomez-Sanchis, J., Gomez-Chova, L., Aleixos, N., Camps-Valls, G., Montesinos-Herrero, C., Molto, E., & Blasco, J. (2008). Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins. Journal of Food Engineering, 89, 80-86.

Hasan, M. M., Chaudhry, M. M. A., Erkinbaev, C., Paliwal, J., Suman, S. P., & Rodas- Gonzalez, A. (2022). Application of Vis-NIR and SWIR Spectroscopy for the Segregation of Bison Muscles Based on Their Color Stability. Meat Science, 188: 108774. https://doi.org/10.1016/j.meatsci. 2022.108774.

Hosainpour, A., Kheiralipour, K., Nadimi, M., & Paliwal, J. (2022). Quality assessment of dried white mulberry (Morus alba L.) using machine vision. Horticulturae, 8(11), 1011.

Ismail, A., Yim, D.-G., Kim, G., & Jo, C. (2023). Hyperspectral imaging coupled with multivariate analyses for efficient prediction of chemical, biological and physical properties of seafood products. Food Eng. Rev. 15, 41–55. https://doi.org/10.1007/s12393-022-09327-x.

Khazaee, Y., Kheiralipour, K., Hosainpour, A. Javadikia, H., & Paliwal, J. (2022). Development of a novel image analysis and classification algorithms to separate tubers from clods and stones. Potato Res., 65, 1-22.

Kheiralipour, K. (2024). The Future of Imaging Technology. Nova Science Publishers, Hauppauge, New York, USA. ISBN 979-8-89530-078-7.

Kheiralipour, K. (2022). Sustainable Production: Definitions, Aspects, Nova Science Publishers, Hauppauge, New York, USA. ISBN 979-8-88697-208-5.

Kheiralipour, K. (2012). Implementation and construction of a system for detecting fungal infection in pistachio kernel based on thermal imaging (TI) and image processing technology. Ph.D. Dissertation, University of Tehran, Karaj, Iran.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., & Rafiee, S. (2018). Thermal Imaging, Principles, Methods and Applications. 1^st Ed. Ilam University Publication, Ilam, Iran.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., Rafiee, S., & Javan-Nikkhah. M. (2015a). Classifying healthy and fungal infected-pistachio kernel by thermal imaging technology. International Journal of Food Properties, 18 (1), 93-99.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., Rafiee, S., Javan-Nikkhah, M., & Jayas, D.S. (2013). Development of a new threshold-based classification model for analyzing thermal imaging data to detect fungal infection of pistachio kernel. Agricultural Research, 2, 127-131.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., Rafiee, S., Javan-Nikkhah, M., & Jayas, D.S. (2015b). Detection of healthy and fungal-infected pistachios based on hyperspectral image processing. 8^th Iranian National Congress of Agricultural Machinery Engineering (Biosystems) and Mechanization. 28-30 January, Mashahd, Iran.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., Rafiee, S., Javan-Nikkhah, M., Jayas, D. S. and & Siliveru K. (2015). Detection of fungal infection in pistachio kernel by long-wave near infrared hyperspectral imaging technique. Quality Assurance and Safety of Crops & Foods, 8(1): 129-135.

Kheiralipour, K., Ahmadi, H., Rajabipour, A., Rafiee, S., Javan-Nikkhah, M., Jayas, D. S., Siliveru, K., & Mlihipour, A. (2015). Processing the hyperspectral images for detecting infection of pistachio kernel by R5 and KK11 isolates of Aspergillus flavus fungus. Iran. J. Biosyst. Eng., 52(1), 13-25.

Kheiralipour, K., Chelladurai, V., & Jayas, D.S. (2023a). Imaging Systems and Image Processing Techniques. In Image Processing: Advances in Applications and Research. Edited by Jayas, D.S. New York, USA: Nova Science Publishers.

Kheiralipour, K., & Jayas, D.S. (2023a). Advances in image processing applications for assessing leafy materials. International Journal of Tropical Agriculture. 41(1-2), 31-47.

Kheiralipour, K., & Jayas D.S. (2023b). Applications of near infrared hyperspectral imaging in agriculture, natural resources, and food in Iran. 15^th National and 1^st International Congress of Mechanics of Biosystems Engineering and Agricultural Mechanization. Karaj, Iran.

Kheiralipour, K., & Jayas, D.S. (2023c). Image Processing for the Quality Assessment of Flour and Flour-Based Baked Products. In Image Processing: Advances in Applications and Research. Edited by Jayas, D.S. New York, USA: Nova Science Publishers.

Kheiralipour, K., & Jayas, D.S. (2024). Current and future applications of hyperspectral imaging in agriculture, nature and food. Trends in Technical & Scientific Research 7 (2), 1-9.

Kheiralipour, K., Kazemi, A. (2020) A new method to determine morphological properties of fruits and vegetables by image processing technique and nonlinear multivariate modeling. International Journal of Food Properties 23(1), 368-374.

Kheiralipour, K., & Marzbani. F. (2016). Pomegranate quality sorting by image processing and artificial neural network. 10^th Iranian National Congress on AGR Machi Eng (Biosystems) and Mechanizasion, 29-31 August, Mashhad, Iran.

Kheiralipour, K., & Nargesi, M.H. (2024). Classification of wheat flour levels in powdered spices using visual imaging. Journal of Agriculture and Food Research. 18, Pages, 101408. https://doi.org/10.1016/j.jafr.2024.101408.

Kheiralipour, K., Nadimi, M., & Paliwal, J. (2022). Development of an Intelligent Imaging System for Ripeness Determination of Wild Pistachios. Sensors. 22(19), 7134.

Kheiralipour, K., Sajadipour, F., Nadimi, M. (2025a). A review of nut quality assessment using hyperspectral imaging technique. Journal of Food Composition and Analysis, 108184.Kheiralipour, K., Sajadipour, F., Nargesi, M. H. (2025b). Applications of spectral imaging in Biosystems engineering in Iran, A review. Recent Progress in Sciences, 2(1), 007.

Kheiralipour, K., Singh, C. B., & Jayas, D. S. (2023b). Applications of Visible, Thermal, and Hyperspectral Imaging Techniques in the Assessment of Fruits and Vegetables. In Image Processing: Advances in Applications and Research. Edited by Jayas, D.S.  New York, USA: Nova Science Publishers.

Kumar, A., Bharti, V., Kumar, V., Kumar, U., & Meena, P.D. (2016). Hyperspectral imaging: A potential tool for monitoring crop infestation, crop yield and macronutrient analysis, with special emphasis to Oilseed Brassica. Journal of Oilseed Brassica, 7(2), 113-12.

Li, Ch., Xu, F., Cao, Ch., Shang, M.Y., Zhang, C.Y., Yu, J., Liu, G.X., Wang, X. & Cai, SH.C. (2013). Comparative analysis of two species of Asari Radix et Rhizoma by electronic nose, headspace GC–MS and chemometrics, Journal of Pharmaceutical and Biomedical Analysis, 85, 231-238.

Li, Norman & Bailey, J. & Kenrick, Douglas & Linsenmeier, Joan. (2002). The Necessities and Luxuries of Mate Preferences: Testing the Tradeoffs. Journal of personality and social psychology. 82. 947-55. 10.1037//0022-3514.82.6.947.

Malavi, D., Nikkhah, A., Alighaleh, P., Einafshar, S., Raes, K., & Haute, S. V. (2024). Detection of saffron adulteration with Crocus sativus style using NIR-hyperspectral imaging and chemometrics. Food Control, 157 (2024) 110189.

Manzoor, N., Akbar, N., Ahmad Anjum, S., Ali, I., Shahid, M., Shakoor, A., Waseem Abbas, M., Hayat, K., Hamid, W., & Rashid, M. A. (2017). Interactive effect of different nitrogen and potash levels on the incidence of bacterial leaf blight of rice (Oryza sativa L.). Agricultural Sciences. 8: 56–63.

Mientka, A., Grzmil, B., & Tomaszewska, M. (2007). Production of potassium sulfate from potassium hydrosulfate solutions using alcohols. Institute of Chemical and Environment Engineering, Szczecin University of Technology, ul. Pulaskiego 10, 70-322 Szczecin, Poland. 62 (1) 123–126.

Min, D., Zhao, J., Bodner, G., Ali, M., Li, F., Zhang, X., & Rewald, B. (2023). Early decay detection in fruit by hyperspectral imaging–Principles and application potential. Food Control 152, 109830. https://doi.org/10.1016/j.foodcont.2023.109830.

Moosavian, A. (2012). Fault Diagnosis and Classification of Journal Bearings by Using Support Vector Machine, M. Sc. dissertation, University of Tehran, Karaj.

Nargesi, M.H. (2024). Detection of fraud in black pepper, red pepper, and cinnamon powder using hyperspectral imaging and artificial neural network. Ph.D. Dissertation, University of Bu-Ali Sina. Pages 11-130.

Nargesi, M. H., Amiriparian, J., & Kheiralipour, K. (2024). Determination of the purity of black pepper powder using hyperspectral imaging and support vector machine methods., Innov. Food Technol, 11(4), 295-312., DOI: https://doi.org/10.22104/ift2024.6934.2174.

Nargesi, M. H., Amiriparian, J., Bagherpour, H., & Kheiralipour, K. (2024). Detection of different adulteration in cinnamon powder using hyperspectral imaging and artificial neural network method. Results in Chemistry. Volume 9, July 2024, 101644.

Nargesi, M. H., Amiriparian, J., Kheiralipour, K. (2025). Detection of wheat, chickpea, and sea foam in black pepper using hyperspectral imaging technique. Applied Food Research, 5(1), 101031.

Nargesi, M. H., Heidarbeigi, K., Moradi, Z., & Abdolahi, S. (2024). Detection of chlorine in potassium chloride and potassium sulfate using chemical imaging and artificial neural network. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. Volume 326, 125253. https://doi.org/10.1016/j.saa.2024.125253.

Nargesi, M. H., & Kheiralipour, K. (2024). Ability of visible imaging and machine learning in detection of chickpea flour adulterant in original cinnamon and pepper powders. Heliyon. Volume 10, ISSUE 16, e35944, August 30, 2024.

Nargesi, M. H., & Kheiralipour, K. (2024). Visible feature engineering to detect adulteration in black and red peppers. Scientific Reports. volume 14, Article number: 25417. https://doi.org/10.1038/s41598-024-76617-1.

Nargesi, M. H., & Kheiralipour, K. (2025). Non-destructive prediction of sucrose, proline, ash, and fructose/glucose ratio in date syrup using hyperspectral imaging and machine learning. LWT, 229, 118153.

Nargesi, M. H., Kheiralipour, K., & Jayas, D. S. (2024a). Classification of different wheat flour types using hyperspectral imaging and machine learning techniques. Infrared Physics & Technology. Volume 142, 105520.Nobari Moghaddam, H., Tamiji, Z., Akbari Lakeh, M., Khoshayand, M. R., & Haji & Mahmoodi, M. (2022). Multivariate analysis of food fraud: A review of NIR based instruments in tandem with chemometrics. Journal of Food Composition and Analysis, 107. https://doi.org/10.1016/j.jfca.2021.104343.

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Development and evaluation of chickpea classification system based on visible image processing technology and artificial neural network. Innovative Food Technologies. 9(2), 181-163.

Sajadipour, F., & Kheiralipour, K. (2025). Water Quality Assessment Using Spectral Imaging Techniques. In: Daniels, J.A. Advances in Environmental Research. Nova Science Publishers, Hauppauge, New York, USA. Salam, S., & Kheiralipour, K. (2022).

Salam, S., & Kheiralipour, K., & Jian, F. (2022). Detection of unripe kernels and foreign materials in chickpea mixtures using image processing. Agriculture, 12(7), 995.

Shabbir Dar, J., Akhtar Cheema, M., Ishaq Asif Rehmani, M., Khuhro, S., Rajput, S., Latif Virk, A., Hussain, S., Amjad Bashir, M., Suliman, M., Al-Zuaibr, M., Javed Ansari, M., & Hessini, K. (2021). Potassium fertilization improves growth, yield and seed quality of sunflower (Helianthus annuus L.) under drought stress at different growth stages. PLoS ONE 16(9): e0256075. https://doi.org/ 10.1371/journal. pone.0256075.

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