The HortiQD project aims to develop an affordable and easy-to-use machine vision system for precision farming. The objective is to build a hyperspectral Short-Wave Infra Red camera working in the wavelength range of 1 - 2 µm with integrated point detection at smaller wavelengths, specifically suitable for orchard monitoring. To reach this goal we propose a novel detector type based on QD technology, based on lead- and mercury-free QDs in compliance with EU regulations and reducing the component cost by approximately 99%. The optical filter will allow for high spectral and spatial resolution, tunable to specific application requirements by design. The hyperspectral images, recorded in-vivo, will be analyzed by deep-learning algorithms in order to identify diseases in an early state and assess the plant health, starting with apples. A data management and correlation system will be set up and present the derived diagnoses and measures directly to the farmer in real-time. The system will be mounted on an already existing autonomous tractor, customized for horticulture, in order to verify the feasibility and targeted TRLs under realistic conditions in several orchard types. HortiQD will help to reduce or avoid the usage of pesticides in European orchards, paving the way towards sustainable farming and increasing food quality. It will scale up the intensity of monitoring by automation, hence, ensure the reliability of European food production. It will help analyze and address the impacts of climate change. The project aims for a fully integrated solution, consisting of several innovative sub components. Each of the developments brings benefit to the industry it addresses and opens up new markets, beyond agriculture and food.