{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T02:48:24Z","timestamp":1772851704658,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T00:00:00Z","timestamp":1678665600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T00:00:00Z","timestamp":1678665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s00521-023-08444-w","type":"journal-article","created":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T14:03:39Z","timestamp":1678716219000},"page":"7609-7618","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A non-invasive approach for calcium deficiency detection in pears using machine learning"],"prefix":"10.1007","volume":"37","author":[{"family":"Yogesh","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0778-9262","authenticated-orcid":false,"given":"Ashwani Kumar","family":"Dubey","sequence":"additional","affiliation":[]},{"given":"Alvaro","family":"Rocha","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,13]]},"reference":[{"key":"8444_CR1","unstructured":"Agriculture and Food (2020) Department of primary industries and regional development. https:\/\/www.agric.wa.gov.au\/pome-fruit\/trace-element-treatments-apple-and-pear-trees. Accessed 13 Sept 2020"},{"key":"8444_CR2","unstructured":"Ware M, RDN LD (2020) Medical news today. https:\/\/www.medicalnewstoday.com\/articles\/285430, November 1, 2019. Accessed 13 Sept 2020"},{"issue":"5","key":"8444_CR3","first-page":"45","volume":"15","author":"T Milo\u0161evi\u0107","year":"2016","unstructured":"Milo\u0161evi\u0107 T, Milo\u0161evi\u0107 N (2016) Estimation of nutrient status in pear using leaf mineral composition and deviation from optimum percentage index. Acta sci Polonorum Hortorum cultus Ogrodnictwo 15(5):45\u201355","journal-title":"Acta sci Polonorum Hortorum cultus Ogrodnictwo"},{"key":"8444_CR4","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-020-05310-x","author":"Y Kumar","year":"2020","unstructured":"Kumar Y, Dubey AK, Arora RR, Rocha A (2020) Multiclass classification of nutrients deficiency of apple using deep neural network. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-020-05310-x","journal-title":"Neural Comput Appl"},{"key":"8444_CR5","doi-asserted-by":"publisher","first-page":"579","DOI":"10.17660\/actahortic.2011.909.69","volume":"909","author":"WJ Steyn","year":"2011","unstructured":"Steyn WJ, Manning N, Muller M, Human JP (2011) Physical, sensory and consumer analysis of eating quality and appearance of pear genotypes among south African consumers. Acta Hortic 909:579\u2013586. https:\/\/doi.org\/10.17660\/actahortic.2011.909.69","journal-title":"Acta Hortic"},{"key":"8444_CR6","doi-asserted-by":"publisher","first-page":"651","DOI":"10.17660\/actahortic.2011.909.79","volume":"909","author":"MD Raffo","year":"2011","unstructured":"Raffo MD, Candan AP, De Angelis V, Ma\u00f1ueco L, Miranda MJ, Barda N (2011) Sensory evaluation of pears: a useful tool to detect changes in eating quality during ripening. Acta hortic 909:651\u2013656. https:\/\/doi.org\/10.17660\/actahortic.2011.909.79","journal-title":"Acta hortic"},{"issue":"3","key":"8444_CR7","doi-asserted-by":"publisher","first-page":"382","DOI":"10.21273\/HORTTECH.2.3.382","volume":"2","author":"D Sugar","year":"1992","unstructured":"Sugar D, Righetti TL, Sanchez EE, Khemira H (1992) Management of nitrogen and calcium in pear trees for enhancement of fruit resistance to postharvest decay. HortTechnol horttech 2(3):382\u2013387","journal-title":"HortTechnol horttech"},{"issue":"2","key":"8444_CR8","doi-asserted-by":"publisher","first-page":"102","DOI":"10.5338\/KJEA.2013.32.2.102","volume":"32","author":"BW Moon","year":"2013","unstructured":"Moon BW, Jung HW, Lee HJ, Yu DJ (2013) Calcium deficiency causes pithiness in Japanese pear (Pyrus pyrifolia cv. Niitaka) fruit. Korean J Environ Agric 32(2):102\u2013107. https:\/\/doi.org\/10.5338\/KJEA.2013.32.2.102","journal-title":"Korean J Environ Agric"},{"key":"8444_CR9","doi-asserted-by":"publisher","first-page":"442","DOI":"10.3389\/fpls.2016.00442","volume":"7","author":"LA Kalcsits","year":"2016","unstructured":"Kalcsits LA (2016) Non-destructive measurement of calcium and potassium in apple and pear using handheld X-ray fluorescence. Front Plant Sci 7:442. https:\/\/doi.org\/10.3389\/fpls.2016.00442","journal-title":"Front Plant Sci"},{"key":"8444_CR10","first-page":"234","volume":"26","author":"J Shotton","year":"2013","unstructured":"Shotton J, Sharp T, Kohli P (2013) Decision jungles: compact and rich models for classification. Adv Neural Inf Process Syst 26:234\u2013242","journal-title":"Adv Neural Inf Process Syst"},{"key":"8444_CR11","doi-asserted-by":"publisher","first-page":"1817","DOI":"10.1007\/s10586-019-03029-6","volume":"23","author":"AK Yogesh","year":"2020","unstructured":"Yogesh AK, Dubey RA, Rocha A (2020) Computer vision based analysis and detection of defects in fruits causes due to nutrients deficiency. clust Comput 23:1817\u20131826. https:\/\/doi.org\/10.1007\/s10586-019-03029-6","journal-title":"clust Comput"},{"key":"8444_CR12","doi-asserted-by":"publisher","unstructured":"Chatterjee C, Dube BK (2004) Nutrient deficiency disorders in fruit trees and their management. In: Mukerji Kg (ed) Fruit and vegetable diseases. Disease management of fruits and vegetables, vol 1. Springer, Dordrecht, https:\/\/doi.org\/10.1007\/0-306-48575-3_1","DOI":"10.1007\/0-306-48575-3_1"},{"key":"8444_CR13","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.jfca.2016.11.012","volume":"56","author":"RJ Marles","year":"2017","unstructured":"Marles RJ (2017) Mineral nutrient composition of vegetables, fruits and grains: the context of reports of apparent historical declines. J Food Compos Anal 56:93\u2013103","journal-title":"J Food Compos Anal"},{"key":"8444_CR14","doi-asserted-by":"crossref","unstructured":"Kawasaki R, Uga H, Kagiwada S, Iyatomi H (2015) Basic study of automated diagnosis of viral plant diseases using convolutional neural networks. Proceedings of the international symposium on visual computing (ISVC), Las Vegas, pp 638\u2013645","DOI":"10.1007\/978-3-319-27863-6_59"},{"key":"8444_CR15","first-page":"378","volume":"267","author":"Y Lu","year":"2017","unstructured":"Lu Y, Yi S, Zeng N, Liu Y, Zhang Y (2017) Identification of rice diseases using deep convolutional neural networks. Neuro Comput 267:378\u2013384","journal-title":"Neuro Comput"},{"issue":"2","key":"8444_CR16","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1109\/TASE.2010.2087325","volume":"8","author":"D-J Lee","year":"2011","unstructured":"Lee D-J, Archibald JK, Xiong G (2011) Rapid color grading for fruit quality evaluation using direct color mapping. IEEE Trans Autom Sci Eng 8(2):292\u2013302. https:\/\/doi.org\/10.1109\/TASE.2010.2087325","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"8444_CR17","doi-asserted-by":"publisher","first-page":"27389","DOI":"10.1109\/ACCESS.2019.2898223","volume":"7","author":"W Castro","year":"2019","unstructured":"Castro W, Oblitas J, De-La-Torre M, Cotrina C, Baz\u00e1n K, Avila-George H (2019) Classification of cape gooseberry fruit according to its level of ripeness using machine learning techniques and different color spaces. IEEE Access 7:27389\u201327400. https:\/\/doi.org\/10.1109\/ACCESS.2019.2898223","journal-title":"IEEE Access"},{"key":"8444_CR18","unstructured":"Olson DL, Delen D. Advanced data mining techniques. Springer Science and Business Media, Berlin, ISBN 3\u2013540\u201376916\u20131 2008"},{"key":"8444_CR19","unstructured":"BV. (2020) Lenntech mineral content of fruit and vegetables. https:\/\/www.lenntech.com\/fruit-vegetable-mineral-content.htm, Accessed 13 Sept 2020"},{"issue":"9","key":"8444_CR20","doi-asserted-by":"publisher","first-page":"12489","DOI":"10.3390\/s120912489","volume":"12","author":"Y Zhang","year":"2012","unstructured":"Zhang Y, Wu L (2012) Classification of fruits using computer vision and a multiclass support vector machine. Sensors 12(9):12489\u201312505","journal-title":"Sensors"},{"key":"8444_CR21","doi-asserted-by":"publisher","unstructured":"Feng G, Qixin C (2004) Study on color image processing based intelligent fruit sorting system. Fifth world congress on intelligent control and automation (IEEE Cat. No.04EX788), vol 6, pp 4802\u20134805. https:\/\/doi.org\/10.1109\/WCICA.2004.1343622","DOI":"10.1109\/WCICA.2004.1343622"},{"key":"8444_CR22","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1016\/j.compag.2018.12.019","volume":"156","author":"DP Cavallo","year":"2018","unstructured":"Cavallo DP, Cefola M, Pace B, Logrieco AF, Attolico G (2018) Non-destructive and contactless quality evaluation of table grapes by a computer vision system. Comput Electron Agric 156:558\u2013564","journal-title":"Comput Electron Agric"},{"key":"8444_CR23","doi-asserted-by":"crossref","unstructured":"Abdelsalam AM, Sayed MS (2016) Real-time defects detection system for orange citrus fruits using multispectral imaging. IEEE 59th intl. Midwest symposium on circuits and systems (MWSCAS), Abu Dhabi, pp 1\u20134","DOI":"10.1109\/MWSCAS.2016.7869956"},{"issue":"23","key":"8444_CR24","first-page":"515","volume":"116","author":"L Agilandeeswari","year":"2017","unstructured":"Agilandeeswari L, Prabukumar M, Goel S (2017) Automatic grading system for mangoes using multiclass SVM classifier. Int J Pure Appl Math 116(23):515\u2013523","journal-title":"Int J Pure Appl Math"},{"issue":"8","key":"8444_CR25","doi-asserted-by":"publisher","first-page":"2674","DOI":"10.3390\/s18082674","volume":"18","author":"K Liakos","year":"2018","unstructured":"Liakos K, Busato P, Moshou D, Pearson S, Bochtis D (2018) Machine learning in agriculture: a review. Sensors 18(8):2674","journal-title":"Sensors"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08444-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-08444-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-08444-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,22]],"date-time":"2025-03-22T17:48:19Z","timestamp":1742665699000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-08444-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,13]]},"references-count":25,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["8444"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-08444-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,13]]},"assertion":[{"value":"25 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}},{"value":"This article does not contain any studies with human participants performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}