Fundamentals in agriculture and food

Development and challenges of fruit harvesting robots 
Robotic fruit harvesters have been created to collect a range of crops, 
such as tomatoes, cucumbers, eggplants, strawberries, and cherry tomatoes. As 
mentioned by (Kawamura et al.,1984), the history of agricultural robots began 
with the development of a tomato harvesting robot, first studied at Kyoto 
College in 1982. 
Over the years, various types of tomato harvesting robots have been 
developed, the main components of which are an end effector, an image 
processing system, a manipulator, and a driving device, as shown in Figure 2 
(Kondo et al.,1993; Subrata et al.,1997). The robot is designed to automatically 
move between ridges and breaks in front of a plant and determine its position 
in the greenhouse using reflective plates and photosensors on the ridges. 
After the moving device comes to a halt, the image recognition system 
analyses the color and position of the fruit, following which the manipulator 
advances towards the cluster and the end effector plucks a fruit. Upon 
completion of the task at hand, the robot moves on to the next site on the 

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FUNDAMENTALS IN AGRICULTURE AND FOOD | 162 
reflective plate (Kondo et al.,1994; Subrata et al.,1997). Despite the slow 
operating speeds, fluctuating crop features, and seasonal expenses posing 
limitations on the commercialization of harvesting robots, it is highly probable 
that they will be put to practical use in the future (Kondo et al.,1998). 
Figure 2:
A tomato Harvesting robot (Liu et al, 2021) 
Automation in greenhouses
Greenhouse automation is a relatively simple process due to the 
structured nature of the environment. The variability of agricultural products is 
the main reason for automation. Climate regulation, spraying, seedling 
cultivation, and harvesting are all aspects addressed by the advancement of 
automated systems for greenhouse operations (Simonton, 1990). 
One of the most important areas of automation in greenhouses is climate 
control, which involves retaining solar radiation energy and protecting plants 
from harmful natural influences and insects. Microcomputers and sensors have 
led to the latest greenhouse operations that include irrigation, plant nutrient 
management, and climate control to provide the best growing conditions for 
plants throughout the year. Climate control in greenhouses involves monitoring 
various parameters, including CO2 concentration, airflow, light, temperature, 
and humidity (Monta,1997a, b). 
Control models for greenhouse climate control should consider weather 
forecast models, greenhouse models, and plant growth models, due to the need 

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to account for multiple non-linear and interconnected factors, regulating the 
climate in a greenhouse necessitates careful attention. Control methods include 
soft computing methods with artificial intelligence, classical methods, and 
advanced control methods. Control is achieved with microcomputers or 
programmable logic controllers (PLCs) (Albright, 2001; Bailey, 2004). 
In the future, climate controls will be developed that use on-line 
measurements of plant temperature, fruit growth, and fruit quality to 
approximate photosynthesis and actual transpiration. This will enable the 
development of closed-loop systems that use plant response as feedback to the 
control system, leading to more efficient greenhouse climate regulation. 
Effective greenhouse climate regulation must also include long-term 
management strategies to improve quality and profitability (Daskalov et al, 
2006; Serodio et al.,2001). 
In addition, the Arduino platform can also be used to control greenhouses 
for experimental purposes (Kraiem, et al.,2022). The Arduino platform 
provides an open-source and flexible environment that enables the development 
of customized and low-cost greenhouse control systems.