Evaluating Knowledge Creation in Smart Container for Monitoring and Prediction of Fresh Fruit Quality: A Systematic Literature Review

Post-harvest fruit losses continue to exceed 30% in many emerging economic. While smart containers equipped with Internet-of-Things (IoT) sensors and artificial-intelligence (AI) models can mitigate spoilage, most systems treat data as an end in itself rather than as a raw material for knowledge creation (KC). Applying PRISMA-2020 and bibliometric mapping (VOSviewer & Bibliometrix), we screened 343 Scope records (2003-2025) and analysed 43 primary studies. The key finding is that more than 70% of the literature operationalises only the Combination phase of the SECI model (data aggregation and predictive modelling). Socialization (tacit knowledge sharing) and Internalization (experiential learning) are almost absent, thereby limiting adaptive decision-making and stakeholder engagement. We conclude with a research-practice roadmap that embeds the complete SECI cycle into smart- container design.

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Publication Details

Journal
BIO Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/bioconf/202518903002
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluating Knowledge Creation in Smart Container for Monitoring and Prediction of Fresh Fruit Quality: A Systematic Literature Review

Taufik Djatna, Sri Hartati Yuliani, Endang Warsiki, Encik Eko Rifkowaty
BIO Web of Conferences
Smart Agriculture and AI
article

Evaluating Knowledge Creation in Smart Container for Monitoring and Prediction of Fresh Fruit Quality: A Systematic Literature Review

Taufik Djatna, Sri Hartati Yuliani, Endang Warsiki, Encik Eko Rifkowaty
article en

Abstract

Post-harvest fruit losses continue to exceed 30% in many emerging economic. While smart containers equipped with Internet-of-Things (IoT) sensors and artificial-intelligence (AI) models can mitigate spoilage, most systems treat data as an end in itself rather than as a raw material for knowledge creation (KC). Applying PRISMA-2020 and bibliometric mapping (VOSviewer & Bibliometrix), we screened 343 Scope records (2003-2025) and analysed 43 primary studies. The key finding is that more than 70% of the literature operationalises only the Combination phase of the SECI model (data aggregation and predictive modelling). Socialization (tacit knowledge sharing) and Internalization (experiential learning) are almost absent, thereby limiting adaptive decision-making and stakeholder engagement. We conclude with a research-practice roadmap that embeds the complete SECI cycle into smart- container design.

BIO Web of ConferencesVol. 189
IPB University (ID), Universitas Muhammadiyah Kupang (ID), National Nuclear Energy Agency of Indonesia (ID), Politeknik Kesehatan Kemenkes Semarang (ID), National Research and Innovation Agency (ID)
Lembaga Pengelola Dana Pendidikan
Openalex Percentile: Top 79%
Smart Agriculture and AI
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Evaluating Knowledge Creation in Smart Container for Monitoring and Prediction of Fresh Fruit Quality: A Systematic Literature Review — Taufik Djatna, Sri Hartati Yuliani, et al. · BIO Web of Conferences (2025) | TGRS Research Map | TGRS