Harnessing Multisensory Perception for the Tomato Agrifood Chain

Area of Science:

• Agricultural Science
• Sensory Science
• Food Technology

Background:

• Global tomato agrifood chains face economic threats from structural inefficiencies and labor shortages.
• Current vision-dominated systems for intelligent management have limitations in environmental robustness and computational efficiency.
• Dimensional incompleteness in current systems hinders the accurate decoding of internal tomato states.

Purpose of the Study:

• To critically review multisensory perception technologies for characterizing tomato physiological states.
• To outline progress, challenges, and prospects in multisensory perception for the agrifood sector.
• To propose a pathway for constructing digital fingerprints and multimodal fusion for practical applications.

Main Methods:

• Integration of physical (tactile, auditory) and chemical (olfactory, gustatory) sensory modalities.
• Quantitative characterization of tomato physiological states using multisensory data.
• Development of digital fingerprints by coupling instrumental sensing signals with human sensory experiences.

Main Results:

• Multisensory perception enables a more comprehensive quantitative characterization of tomato physiological states compared to vision-only systems.
• Significant progress has been made in multisensory perception, addressing limitations of visual perception.
• A pathway for constructing digital fingerprints and multimodal fusion has been delineated.

Conclusions:

• Multisensory perception presents a promising avenue for advancing intelligent management in the tomato agrifood chain.
• Digital fingerprints and multimodal fusion are key to addressing practical challenges and ensuring sensorially transparent evaluation.
• This perspective provides a roadmap for future research and development in agrifood sensory evaluation systems.