A Data-Driven Approach to Improve Cocoa Crop Establishment in Colombia: Insights and Agricultural Practice Recommendations from an Ensemble Machine Learning Model DOI Creative Commons
Leonardo Hernán Talero Sarmiento, Sebastián Roa Prada,

Luz Caicedo-Chacon

et al.

AgriEngineering, Journal Year: 2024, Volume and Issue: 7(1), P. 6 - 6

Published: Dec. 28, 2024

This study addresses the critical challenge of limited understanding environmental factors influencing cocoa cultivation in Colombia, a region with significant production potential but diverse agroecological conditions. The fragmented nature existing agricultural data and lack targeted research hinder efforts to optimize productivity sustainability. To bridge this gap, employs data-driven approach, using advanced machine learning techniques such as supervised, unsupervised, ensemble models, analyze datasets provide actionable recommendations. By integrating from official Colombian sources, well NASA POWER database, geographical APIs, present proposes methodology systematically assess conditions classify regions for optimal cultivation. use an assembled model, combining clustering each cluster, offers more precise scalable establishment under Despite challenges dataset resolution localized climate variability, provides valuable insights comprehensive impacting plantation given location. key findings reveal that temperature, humidity, wind speed are crucial determinants growth, complex interactions affecting regional suitability. results offer guidance implementation adaptive practices resilience strategies, enabling sustainable systems. implementing better practices, countries Colombia can achieve higher market shares growing global demand

Language: Английский

Portable System for Cocoa Bean Quality Assessment Using Multi-Output Learning and Augmentation DOI
Kamini G. Panchbhai, Madhusudan G. Lanjewar

Food Control, Journal Year: 2025, Volume and Issue: unknown, P. 111234 - 111234

Published: Feb. 1, 2025

Language: Английский

Citations

2
The Health Impact of Cocoa from Cultivation to the Formation of Biogenic Amines: An Updated Review DOI Creative Commons
Antonello Paparella, Maria Schirone, Clemencia Chaves‐López

et al.

Foods, Journal Year: 2025, Volume and Issue: 14(2), P. 255 - 255

Published: Jan. 15, 2025

Cocoa and chocolate are known for their health benefits, which depend on factors like cocoa variety, post-harvest practices, manufacturing processes, including fermentation, drying, roasting, grinding, refining. These processing methods can influence the concentration bioavailability of bioactive compounds, such as polyphenols that linked to cardiovascular antioxidant effects. Recent scientific research has led development cocoa-based products marketed functional foods. However, despite growing interest in potential cocoa, literature lacks crucial information about properties different varieties possible implications human health. Moreover, climate change is affecting global production, potentially altering product composition health-related characteristics. In addition polyphenols, other compounds biogenic amines, due role toxic effects Based toxicological data recent complex relationship between amines setting limits or standards could help ensure safety. Finally, new trends suggest these might also be used quality markers, formulation process conditions content diversity amines.

Language: Английский

Citations

0
Assessing the Cocoa Farmer Empowerment Program through the Lens of Stufflebeam's Evaluation Framework: A Farmer-Centric Approach DOI Creative Commons

Regina Sapta Samudera,

Deddy T. Tikson

Deleted Journal, Journal Year: 2025, Volume and Issue: 2025(1), P. 524 - 528

Published: Jan. 14, 2025

This study evaluates the effectiveness of PT. Berau Coal's Corporate Social Responsibility (CSR) program for empowering cocoa farmers in Regency, Indonesia, using Stufflebeam's Context, Input, Process, and Product (CIPP) evaluation model. Through in-depth interviews, focus group discussions, observations involving 28 key informants, including representatives from Coal, local government, NGOs, farmers, assesses program's alignment with farmers' needs, provision resources training, implementation challenges, outcomes. The findings reveal that addresses aspirations economic improvement capacity building, Coal providing essential facilities, knowledge-sharing opportunities, a supportive environment. However, challenges persist, need enhanced collaboration expanded socialization efforts, comprehensive monitoring system. Despite these has yielded positive results, such as increased production sales, emergence skilled farmer champions. recommends strengthening partnerships within value chain continuously adapting to ensure its long-term sustainability scalability driving empowerment Regency.

Language: Английский

Citations

0
Automatic Switching System for Submersible Motor Pump: Case Study of a Cocoa Processing Company in Ghana DOI

Emmanuel Osei-Kwame,

Yaw Sam-Okyere,

Lambert Dwomoh

et al.

Journal of Power, Energy, and Control, Journal Year: 2025, Volume and Issue: 2(1), P. 27 - 42

Published: April 18, 2025

Cocoa processing companies are pivotal to Ghana's economy and the sustainability of its cocoa industry. transform raw beans into a paste-like form known as liquor, which serves foundation for various cocoa-based products. These operations require using pumps supply water different stages production. Most these particularly concerned about potential pump failures associated costs replacements. To mitigate this risk, they have developed technique protect from burnout. Currently, existing protection system is manually operated suffers inaccuracies in switching times. Additionally, fluctuations weather conditions pose further threats pumps' integrity. This research focuses on automating address issues effectively. In project, Programmable Logic Controller (PLC) was utilized design an automated system. The control program simulated RSLogix Micro Starter Lite verify functionality. Simulation results demonstrated that provides effective automatic pumps, thereby enhancing their operational efficiency equipment longevity.

Language: Английский

Citations

0
Theobroma cacao Virome: Exploring Public RNA-Seq Data for Viral Discovery and Surveillance DOI Creative Commons

Gabriel Victor Pina Rodrigues,

João Pedro Nunes Santos,

Lucas Yago Melo Ferreira

et al.

Viruses, Journal Year: 2025, Volume and Issue: 17(5), P. 624 - 624

Published: April 26, 2025

Cocoa (Theobroma cacao L.) is a major agricultural commodity, essential for the global chocolate industry and livelihoods of millions farmers. However, viral diseases pose significant threat to cocoa production, with Badnavirus species causing severe losses in Africa. Despite its economic importance, overall virome T. remains poorly characterized, limiting our understanding diversity potential disease interactions. This study aims assess cocoa-associated by analyzing 109 publicly available RNA-seq libraries from nine BioProjects, covering diverse conditions geographic regions. We implemented comprehensive bioinformatics pipeline integrating multiple sequence enrichment steps, hybrid assembly strategy using different assemblers, similarity searches against NCBI non-redundant databases. Our approach identified ten putative novel viruses associated microbiome species. These findings provide new insights into landscape cacao, characterizing cacao-associated their ecological roles. Expanding catalog plants not only enhances plant–virus–microbiome interactions but also contributes development more effective surveillance management strategies, ultimately supporting sustainable production.

Language: Английский

Citations

0
Disease Detection on Cocoa Crops Based on Computer-Vision Techniques: A Systematic Literature Review DOI Creative Commons
Joan Alvarado, Juan Felipe Restrepo-Arias, David Velásquez

et al.

Agriculture, Journal Year: 2025, Volume and Issue: 15(10), P. 1032 - 1032

Published: May 10, 2025

Computer vision in the agriculture field aims to find solutions guarantee and assure farmers quality of their products. Therefore, studies diagnose diseases detect anomalies crops, through computer vision, have been growing recent years. However, crops such as cocoa required further attention drive advances detection diseases. As a result, this paper explore methods used especially cocoa. purpose is provide answers following research questions: (Q1) What are affecting crop production? (Q2) main Machine Learning algorithms techniques classify cocoa? (Q3) types imaging technologies (e.g., RGB, hyperspectral, or multispectral cameras) commonly these applications? (Q4) mobile applications other platforms for disease detection? This carries out Systematic Literature Review approach. The Scopus Digital, Science Direct Springer Link, IEEE Explore databases were explored from January 2019 August 2024. These questions identified that affect production. From this, it was mostly based on employed In addition, sensors explored, RGB hyperspectral cameras, creation datasets tool Finally, allowed us algorithm deployed Internet Things detecting crops.

Language: Английский

Citations

0
A Data-Driven Approach to Improve Cocoa Crop Establishment in Colombia: Insights and Agricultural Practice Recommendations from an Ensemble Machine Learning Model DOI Creative Commons
Leonardo Hernán Talero Sarmiento, Sebastián Roa Prada,

Luz Caicedo-Chacon

et al.

AgriEngineering, Journal Year: 2024, Volume and Issue: 7(1), P. 6 - 6

Published: Dec. 28, 2024

This study addresses the critical challenge of limited understanding environmental factors influencing cocoa cultivation in Colombia, a region with significant production potential but diverse agroecological conditions. The fragmented nature existing agricultural data and lack targeted research hinder efforts to optimize productivity sustainability. To bridge this gap, employs data-driven approach, using advanced machine learning techniques such as supervised, unsupervised, ensemble models, analyze datasets provide actionable recommendations. By integrating from official Colombian sources, well NASA POWER database, geographical APIs, present proposes methodology systematically assess conditions classify regions for optimal cultivation. use an assembled model, combining clustering each cluster, offers more precise scalable establishment under Despite challenges dataset resolution localized climate variability, provides valuable insights comprehensive impacting plantation given location. key findings reveal that temperature, humidity, wind speed are crucial determinants growth, complex interactions affecting regional suitability. results offer guidance implementation adaptive practices resilience strategies, enabling sustainable systems. implementing better practices, countries Colombia can achieve higher market shares growing global demand

Language: Английский

Citations

2