by Fruit picking robots are machines that use computer vision systems with advanced image processing techniques to identify and pick fruits from orchards and farms. These robots incorporate mechanical arms, cameras, sensors, and software algorithms to efficiently handle harvesting operations with minimal human intervention. The increasing use of robotics in agriculture has helped optimize crop production and enhanced farm productivity. Fruit picking robots can identify ripe fruits based on parameters like color, shape, size, and texture. They pluck the fruits carefully without causing any damage, thus minimizing crop wastage. Adopting fruit picking robots allows farms to harvest around the clock and eliminates dependency on seasonal laborers.
The global fruit picking robots market is estimated to be valued at US$ 728.07 Mn in 2023 and is expected to exhibit a CAGR of 40% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market key trends:
Integration of advanced technologies: Key players are increasingly focusing on integrating innovative technologies like computer vision, artificial intelligence, machine learning, and predictive analytics in fruit picking robots. For instance, Harvest CROO Robotics developed “CROO” – an AI and computer vision-enabled robotic system for fruit harvesting. CROO uses deep learning algorithms trained on huge image datasets to recognize and grasp produce with precision. Such technological advancements are enhancing harvesting efficiency and making operations more profitable for farmers.
Preference for rental models: Leading manufacturers are offering fruit picking robots on a rental basis to make them more affordable for small and medium farm owners. Rental models help reduce upfront costs for clients and provide pay-per-use payment options. This flexible pricing approach is fueling the adoption of robotic harvesters, especially in developing countries. It is estimated that over 55% of new fruit picking robot installations in 2030 will be through the rental model.
Growing contractual farming: Large food companies and agribusinesses are increasingly engaging in contract farming with smallholder farmers globally. This trend is prompting more investment in farm mechanization, including fruit picking robots. Contract terms often require the use of advanced harvest technologies to ensure quantity, quality, and food safety compliance for exports and retail markets. This growing contractual farming landscape is catalyzing robotics usage significantly.
Porter’s Analysis
Threat of new entrants: Low. High capital requirement for development, testing and production limits new entrants.
Bargaining power of buyers: Moderate. Customers have relatively few options but high quality produce is a priority.
Bargaining power of suppliers: Low. Suppliers of components have moderate differentiation but fruit growers prefer automated solutions to reduce labour costs.
Threat of new substitutes: Moderate. Manual harvesting remains viable but wages are rising. Drones may emerge as an alternative but require regulatory approval.
Competitive rivalry: High. Major players compete on technology, quality, connectivity and pricing to gain long-term contracts from growers.
Key Takeaways
The Global Fruit Picking Robots Market Share is expected to witness high growth.
Regional analysis: North America is the largest due to advanced agriculture industry and large growers. Europe follows due to supportive government initiatives for automation. Asia Pacific is set to grow at the fastest pace led by Japan, China and India as growers invest in robotics to address labor shortage.
Key players operating in the fruit picking robots market are Abbott Laboratories (US), Medtronic PLC (Ireland), DexCom, Inc. (US), iRhythm Technologies, Inc. (US), and Texas Instruments Inc. (US). Major players compete on technology, quality, connectivity and pricing to gain long-term contracts from growers. Fruit picking robots allow agricultural operations to reduce costs, increase yields and ensure consistent quality throughout the harvest season. Advancements include machine learning, computer vision and collaborative robots that can operate alongside human workers.
