Phenobot - Intelligent photonics for molecular phenotyping in Precision Viticulture

¹ INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
² FCUP - Department of Geosciences, Environment and Spatial Planning, Faculty of Sciences of the University of Porto, Portugal
³ INIAV - National Institute of Agricultural and Veterinary Research, I.P., Portugal
⁴ ADVID - Associação para o Desenvolvimento da Viticultura Duriense (ADVID) - CoLAB Vines&Wines – National Collaborative Laboratory for the Portuguese Wine Sector. Vila Real, Portugal
⁵ COTHN - National Horticultural Operative and Technological Center, Alcobaça, Portugal
⁶ SPIN.WORKS - Av. da Igreja 42 6º, 1700-239 Lisboa, Portugal
⁷ Portugal Ramos - Adega Vila Santa, Estrada Nacional 4, 7100-149 Estremoz, Portugal
⁸ Francisco Rodrigues - Quinta do Monte Bravo, 5130-130 Ervedosa do Douro, Portugal
⁹ Poças - Sociedade Vinícola Terras de Valdigem, S.A, Peso da Régua, Portugal
¹⁰ Real Companhia Velha - Rua de Azevedo Magalhães, 314, 4430-022 Vila Nova de Gaia, Portugal
¹¹ Frutus - Estação Fruteira de Montejunto, CRL, Portugal
¹² Camoptec - Comercialização e Consultoria em Hortofrutícolas, Portugal
¹³ Quinta do Pinto Sociedade Agrícola e Comercial, S.A. – Aldeia Galega da Merceana, Portugal

^* Corresponding author: rui.c.martins@inesctec.pt

Abstract

The Phenobot platform is comprised by an autonomous robot, instrumentation, artificial intelligence, and digital twin diagnosis at the molecular level, marking the transition from pure data-driven to knowledge-driven agriculture 4.0, towards a physiology-based approach to precision viticulture. Such is achieved by measuring the plant metabolome ‘in vivo' and 'in situ', using spectroscopy and artificial intelligence for quantifying metabolites, e.g.: i. grapes: chlorophylls a and b, pheophytins a and b, anthocyanins, carotenoids, malic and tartaric acids, glucose and fructose; ii. foliage: chlorophylls a and b, pheophytins a and b, anthocyanins, carotenoids, nitrogen, phosphorous, potassium, sugars, and leaf water potential; and iii. soil nutrients (NPK). The geo-referenced metabolic information of each plant (organs and tissues) is the basis of multi-scaled analysis: i. geo-referenced metabolic maps of vineyards at the macroscopic field level, and ii. genome-scale 'in-silico' digital twin model for inferential physiology (phenotype state) and omics diagnosis at the molecular and cellular levels (transcription, enzyme efficiency, and metabolic fluxes). Genome-scale 'in-silico' Vitis vinifera numerical network relationships and fluxes comprise the scientific knowledge about the plant's physiological response to external stimuli, being the comparable mechanisms between laboratory and field experimentation - providing a causal and interpretable relationship to a complex system subjected to external spurious interactions (e.g., soil, climate, and ecosystem) scrambling pure data-driven approaches. This new approach identifies the molecular and cellular targets for managing plant physiology under different stress conditions, enabling new sustainable agricultural practices and bridging agriculture with plant biotechnology, towards faster innovations (e.g. biostimulants, anti-microbial compounds/mechanisms, nutrition, and water management). Phenobot is a project under the Portuguese emblematic initiative in Agriculture 4.0, part of the Recovery and Resilience Plan (Ref. PRR: 190 Ref. 09/C05-i03/2021 – PRR-C05-i03-I-000134).