Migliorare la sostenibilità della coltivazione di prodotti agricoli utilizzando un approccio basato sui dati

In questo approfondimento, a cura di Dzmitry Yablonski, CTO e co-fondatore di GeoPard Agriculture, potrai scoprire come AWS, e grazie alla collaborazione con Corteva, leader a livello mondiale nel settore agricolo, affrontano le sfide relative al cambiamento climatico, alla conservazione della biodiversità e al soddisfacimento della crescente domanda di cibo.

Autore: Redazione InnovationCity

A causa del cambiamento climatico e della crescita della popolazione mondiale, il settore agricolo è più che mai sotto pressione per produrre di più con meno input. Infatti, secondo le statistiche delle Nazioni Unite, nei prossimi 30 anni la popolazione mondiale dovrebbe aumentare di 2 miliardi e, allo stesso tempo, acqua, terra, manodopera e altre risorse per la produzione alimentare dovrebbero diventare più scarse. Per questo ridurre le emissioni gas serra (GHG) provenienti dall’agricoltura, che secondo l'Agenzia per la protezione ambientale degli Stati Uniti equivalgono al 24% del totale, è più che mai importante. Nel frattempo, il COVID-19 rimane una sfida. Per accelerare la consegna d tecnologie avanzate ai coltivatori, una soluzione che potrebbe arrivare da collaborazioni tra aziende Ag Tech è più che mai essenziale. Per esempio, Geopard, una piattaforma indipendente per l'agricoltura di precisione, sta collaborando con Corteva, leader a livello mondiale nel settore agricolo, per migliorare la loro app Granular Link.

Il caso aziendale

Per affrontare sfide come il cambiamento climatico, la conservazione della biodiversità e il soddisfacimento della crescente domanda di cibo, Corteva Agriscience ha deciso di investire nell'agricoltura sostenibile e nella biodiversità, elementi integranti della visione strategica dell’azienda. In Europa, stanno investendo in soluzioni digitali che possano migliorare l'efficienza delle decisioni agronomiche attraverso un uso più intelligente degli input agricoli.
Quest'anno, Corteva Agriscience Europe ha lanciato
Granular Link, una app con mappe VRA (Variable Rate Application ) personalizzate che permette di gestire in modo più intelligente le materie della filiera agroalimentare (dalla protezione delle sementi e alle colture) con raccomandazioni integrate. L’app comprende funzionalità di agricoltura digitale in grado di ridurre il rischio e massimizzare i rendimenti della coltura. Granular Link fornisce:

Sin dal primo giorno, il team di Flavio Cozzoli, Head of Digital Agronomy and Innovation di Corteva Agriscience Europe ha affrontato molteplici sfide per garantire un lancio commerciale di successo. Per gestire l’origine eterogenea e grande quantità di dati, che ha raggiunto un centinaio di terabyte, il team ha avuto bisogno di un sistema in grado di generare mappe VRA su scala per milioni di ettari, in pochi minuti. Il tutto tenendo conto della cronologia agricola, poiché saltare anche una singola stagione del raccolto causerebbe problemi di convalida delle tecnologie.

Per questo Corteva Agriscience si è affidata a GeoPard Agriculture, che ha fornito sistemi di analisi dei dati di alta qualità, potenti e scalabili. Il fondatore di GeoPard è stato uno dei primi ingegneri software/direttori tecnici di Xarvio e ha partecipato allo sviluppo di software per l'agricoltura di precisione acquisito da Bayer Crop Science nel 2015. La soluzione Granular Link combina le capacità di geoanalisi di GeoPard Agriculture, la conoscenza unica dei propri prodotti e delle pratiche agronomiche più adatte, e l'infrastruttura sicura e scalabile di AWS per fornire una tecnologia all'avanguardia ai coltivatori dell'UE.

L’approccio di GeoPard Agriculture

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