{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T04:44:16Z","timestamp":1769575456435,"version":"3.49.0"},"reference-count":61,"publisher":"Emerald","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,18]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aims to improve the Standard Colour Analysis (SCAN) values and overall production quality of paprika powder, a spice of substantial market importance. Moreover, the investigation is intended to identify the key factors that significantly influence the SCAN colour of paprika.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>The article adopted a case study methodology to attain the research objectives. In addition, it utilized Six Sigma DMAIC phases to unearth the potential causes that influence the variation in the quality of the product. Advanced statistical methodologies such as DoE and multiple regressions are incorporated to validate the potential causes and draw robust inferences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>It is determined that water content or moisture levels before and after blending significantly affect the SCAN colour. Additionally, it is uncovered that dryer parameters \u2013 specifically temperature and conveyor belt speed \u2013 impact moisture and colour attributes across different pepper characteristic clusters. By applying Six Sigma methodologies, the research provides actionable insights and process adjustments that led to a 10-percentage point increase in compliant batches, rising from 5 to 15% within four\u00a0months.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Research limitations\/implications<\/jats:title>\n                    <jats:p>The study\u2019s outcomes have practical implications for the spice processing industry. By identifying factors that affect colour and moisture in paprika powder, the study provides a valuable reference for optimising production processes and enhancing overall product quality. Nevertheless, the study considered only control parameters during the study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>This study contributes to the existing literature by demonstrating the applicability of the Six Sigma DMAIC model in complex agricultural and food processing environments, where natural variability, quality consistency and customer-driven specifications converge. By focusing on colour attributes and moisture \u2013 two critical yet underexplored quality parameters in industrial paprika production \u2013 the research offers a replicable methodology for process optimization and adds practical value to the continuous improvement literature. Furthermore, the study supports the United Nations Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation and Infrastructure) and SDG 12 (Responsible Consumption and Production), by enhancing process efficiency and minimizing production waste.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/ijppm-12-2024-0850","type":"journal-article","created":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T09:42:41Z","timestamp":1757756561000},"page":"3621-3648","source":"Crossref","is-referenced-by-count":2,"title":["Spice quality: a Six Sigma approach to increasing SCAN colour in a paprika production process"],"prefix":"10.1108","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6426-3187","authenticated-orcid":true,"given":"F\u00e1tima","family":"Carneiro","sequence":"first","affiliation":[{"name":"FEUP Department of Industrial Engineering and Management, , ,","place":["Porto, Portugal"]},{"name":"Kaizen Institute Western Europe , 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