Technological Advancements and Economics in Plant Production Systems: How to Retrofit?

Daniel Dooyum Uyeh; Rammohan Mallipeddi; Tusan Park; Seungmin Woo; Yushin Ha

doi:10.3389/fpls.2022.929672

Technological Advancements and Economics in Plant Production Systems: How to Retrofit?

Front Plant Sci. 2022 Jul 1:13:929672. doi: 10.3389/fpls.2022.929672. eCollection 2022.

Authors

Daniel Dooyum Uyeh^{1

2

3}, Rammohan Mallipeddi⁴, Tusan Park^{1

3}, Seungmin Woo^{1

2

3}, Yushin Ha^{1

2

3}

Affiliations

¹ Department of Bio-Industrial Machinery Engineering, Kyungpook National University, Daegu, South Korea.
² Upland-Field Machinery Research Centre, Kyungpook National University, Daegu, South Korea.
³ Smart Agriculture Innovation Center, Kyungpook National University, Daegu, South Korea.
⁴ Department of Artificial Intelligence, School of Electronics Engineering, Kyungpook National University, Daegu, South Korea.

Abstract

Plant production systems such as plant factories and greenhouses can help promote resilience in food production. These systems could be used for plant protection and aid in controlling the micro- and macro- environments needed for optimal plant growth irrespective of natural disasters and changing climate conditions. However, to ensure optimal environmental controls and efficient production, several technologies such as sensors and robots have been developed and are at different stages of implementation. New and improved systems are continuously being investigated and developed with technological advances such as robotics, sensing, and artificial intelligence to mitigate hazards to humans working in these systems from poor ventilation and harsh weather while improving productivity. These technological advances necessitate frequent retrofits considering local contexts such as present and projected labor costs. The type of agricultural products also affects measures to be implemented to maximize returns on investment. Consequently, we formulated the retrofitting problem for plant production systems considering two objectives; minimizing the total cost for retrofitting and maximizing the yearly net profit. Additionally, we considered the following: (a) cost of new technologies; (b) present and projected cost for human labor and robotics; (c) size and service life of the plant production system; (d) productivity before and after retrofit, (e) interest on loans for retrofitting, (f) energy consumption before and after retrofit and, (g) replacement and maintenance cost of systems. We solved this problem using a multi-objective evolutionary algorithm that results in a set of compromised solutions and performed several simulations to demonstrate the applicability and robustness of the method. Results showed up to a 250% increase in annual net profits in an investigated case, indicating that the availability of all the possible retrofitting combinations would improve decision making. A user-friendly system was developed to provide all the feasible retrofitting combinations and total costs with the yearly return on investment in agricultural production systems in a single run.

Keywords: decision making; greenhouse; non-dominated sorting genetic algorithm; plant factory; resilient food systems; return on investment.