Pisco, an Appellation of Origin from Peru: A review

JC Palma, JF Campos, JJD Morales, ADA Durand… - Heliyon, 2025 - cell.com
Pisco is an Appellation of Origin from Peru, its name comes from the town and the port of
Pisco. It is a spirit obtained exclusively by the distillation of base wine, produced along the …

Inter-species comparative analysis of components of soluble sugar concentration in fleshy fruits

Z Dai, H Wu, V Baldazzi, C Van Leeuwen… - Frontiers in plant …, 2016 - frontiersin.org
The soluble sugar concentration of fleshy fruit is a key determinant of fleshy fruit quality. It
affects directly the sweetness of fresh fruits and indirectly the properties of processed …

Modeling grape quality by multivariate analysis of viticulture practices, soil and climate

S Beauchet, V Cariou, C Renaud-Gentié, M Meunier… - Oeno One, 2020 - hal.science
Aims: The present study aims to model grape quality criteria by combining a large number of
viticultural practices and soil and climatic variables related to the main determinants …

Decision support tool for the agri-food sector using data annotated by ontology and Bayesian network: A proof of concept applied to milk microfiltration

C Baudrit, P Buche, N Leconte… - International Journal of …, 2022 - igi-global.com
The scientific literature is a valuable source of information for develo** predictive models
to design decision support systems. However, scientific data are heterogeneously structured …

A decision-support system to predict grape berry quality and wine potential for a Chenin vineyard

NM Perrot, A Tonda, I Brunetti, H Guillemin… - … and Electronics in …, 2022 - Elsevier
Grape berry ripening is a complex process, and predicting the quality of wine starting from
the ripening kinetics of grape berries is a challenging task. To tackle this problem, we …

Integrating collective know-how for multicriteria decision support in agrifood chains—application to cheesemaking

P Buche, J Couteaux, J Cufi, S Destercke… - Frontiers in Artificial …, 2023 - frontiersin.org
Agrifood chain processes are based on a multitude of knowledge, know-how and
experiences forged over time. This collective expertise must be shared to improve food …

Maturation of shoots, leaves and fruits of Ecolly grape in response to alternative new pruning system and harvesting times in China

L Nan, Y Li, C Cui, J Huang, Y Liu, C Xu, S Fan… - Scientia …, 2018 - Elsevier
This study investigated effect of two trellises, single crawled cordon training (SCCT) and
independent long-stem pruning (ILSP) on change of total organic carbons (TOCs) in the …

Метод оценки зрелости ягод без их разрушения

АФ Алейников, ВВ Минеев - … вестник сельскохозяйственной науки, 2018 - elibrary.ru
При промышленном производстве продукции садоводства необходимы
инструментальные средства контроля физических свойств растений и элементов …

Interactive machine learning for applications in food Science

A Tonda, N Boukhelifa, T Chabin, M Barnabé… - Human and Machine …, 2018 - Springer
The apparent simplicity of food processes often hides complex systems, where physical,
chemical and living organisms' processes co-exist and interact to create the final product …

Machine learning for agri-food processes: learning from data, human knowledge, and interactions

NM Perrot, A Tonda, N Boukhelifa, I Brunetti… - … in Biotechnology and …, 2022 - Elsevier
This chapter presents three examples of data-based machine learning (ML) on time series.
The common denominator of these case studies is the sparseness of data, making ML …