• International Journal of Technology (IJTech)
  • Vol 11, No 8 (2020)

Effectiveness Assessment of Investments in Robotic Biological Plant Protection

Effectiveness Assessment of Investments in Robotic Biological Plant Protection

Title: Effectiveness Assessment of Investments in Robotic Biological Plant Protection
Tatiana Kudryavtseva, Angi Skhvediani

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Cite this article as:
Kudryavtseva, T., Skhvediani, A. 2020. Effectiveness Assessment of Investments in Robotic Biological Plant Protection. International Journal of Technology. Volume 11(8), pp. 1589-1597

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Tatiana Kudryavtseva Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg 195251, Russia
Angi Skhvediani Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, Saint Petersburg 195251, Russia
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Abstract
Effectiveness Assessment of Investments in Robotic Biological Plant Protection

Evaluation of the effectiveness of digital technologies adoption is relevant in all areas of activity, including agriculture. The goal of this study is to evaluate the effectiveness of investments in robotic technologies for biological plant protection in greenhouse enterprises. This article proposes a decision-making algorithm for evaluating the effectiveness of investments in robotic technology projects for biological plant protection based on a financial model, which is supplemented by the technical and economic parameters of digital technologies. Testing of the model on the example of a Russian enterprise showed that the project pays off in two years, while the profitability of the enterprise grows by increasing the yield and boosting the sales of environmentally friendly products in the context of replacing chemical plant protection with biological methods. The main assessed risk factors for the project are a decrease in revenue, an increase in overall costs of the greenhouse, and an increase in the cost of digital technology development and implementation. Sensitivity of the project to personnel recruitment and requalification issues appeared to be very low. The study contributes to the development of methods for economic assessment of the effectiveness of digital technologies in agriculture. In addition, it shows in a specific case that for transitional and low-income countries (in this case Russia), implementation of the high technologies may result in higher relative operational expenses.

Entomophagy; Fertilizer; Insectivore; Internet of things; Risks; Sensitivity analysis

Introduction

The digital economy is a system of economic relations in which data is a key factor in production in all fields (Rodionov and Rudskaia, 2018; Schepinin and Bataev, 2019). The transition to digital agriculture is closely linked to the processes that are transforming this area (Tang et al., 2002; Zaytsev, 2020). These processes imply the interaction of all components (agronomic, economic, financial, environmental, etc.), each of which is responsible for its own sphere (Ansari et al., 2016; Kovács and Husti, 2018; Zaborovskaya et al., 2019; Ciruela-Lorenzo et al., 2020). The transition to the digital economy of agriculture implies the formation and introduction of new structures and technologies that will ensure the development of the agricultural complex of the Russian Federation (Kurbatova et al., 2019; Panetto et al., 2020). Thus, in order to develop digital agricultural technologies, it is necessary to determine what data needs to be collected and processed to create  a  decision-making  support  system  for agrarians.  Based on  this information, it is possible to determine the technical task for the formation of a digital solution and assess the economic efficiency of its realization.

To date, there are two main reasons for the digitization of the agricultural sector:

·         Improving productivity of agro-industrial complex (AIC) sector enterprises;

·         Reducing losses in agricultural production.

Losses in agriculture arise from natural conditions that the producer cannot affect, biological threats, and unskilled workers who fail to accept or use high-tech solutions (Trisasongko et al., 2016; Zinchenko, 2017; Wegren et al., 2019; Borisov and Danilova, 2020). Therefore, one of the potential economic effects of the digitization of the AIC in Russia can be an increase in the market supply of agricultural products. 

Table 1 Possibilities, limitations and risks of digital technologies application in agriculture in Russia

Activity type

 

Parame-
ters analyzed

Crop farming

Livestock farming

Systems and technologies that can be used in the development of digital solutions for the AIC

Precision farming systems;

GLONASS;

Satellite technologies;

Landscape maps;

Determining the actual acreage;

Predicting harvest yield and loss of harvest;

Computer vision for planting analysis;

Crop health monitoring;

Automatic watering systems.

Machine vision for livestock accounting;

Facial recognition systems for livestock;

Forming animal diet;

Veterinary care;

Optimization of the agricultural equipment park;

Limitations and risks of the implementation and use of digital solutions for the AIC

The need to make capital investments in the modernization and renewal of equipment, capital buildings, due to their high physical wear and tear.

The need to carry out a large amount of research and development to refine the technologies used in the final product, including the development of the user interface and solutions for the integration of various technical and information systems.

The need to train new highly qualified personnel and retrain existing ones, including in the skills of organization, processing, and analyzing digitally generated information

The need to develop new standards for agricultural activities, taking into account the use of digital solutions

Low level of development of telecommunications infrastructure in rural areas

Restrictions on aerial photography data

Need to import modern technological means of keeping, feeding, and taking care of animals

 

       Table 1 organizes the main areas of digital use in agriculture, as well as the main limitations and risks of their application in Russia. These limitations and risks are based on a literature review of the results of the theory and practice of the introduction of digital solutions in agriculture of other countries, including developing countries such as Russia. Among the main constraints, we should point out the significant need for investments related to production facilities and infrastructure upgrades (Lele and Goswami, 2017; Pivoto et al., 2018; Iovlev et al., 2019; Zaytsev, 2020), the requalification and training of staff capable of working with new technologies (Salemink et al., 2017; Pivoto et al., 2018; Rotz et al., 2019; Kudryavtseva et al., 2019), the difficulties in purchasing technologies and equipment abroad, and the inaccessibility of information (Yong et al., 2018). These limitations create significant risks for the successful implementation of projects applying digital solutions in agriculture and their increase in price.

        Within the current study, the object of research is the use of robotic technologies to carry out the protection of plants using biological methods. Table 2 presents some of the latest developments used in plant protection. The equipment described in Table 2 is usually designed either for spraying (chemical protection of plants) or for pruning and thinning. In addition, we present robots engaged in biological plant protection in one way or another and mention the use of drones for scanning the territory and producing a detailed map of the state of the fields. With additional software, such drones can identify the contamination zones in the greenhouse area. The authors found the only robot on the market that can conduct both pest treatment and pruning, LettuceBot2. However, this robot cannot be used in greenhouse farms for biological plant protection. Thus, the authors were not able to find robotic solutions capable of scanning the territory of greenhouses for infestation with insect pests and placing biological agents of protection (entomophages) automatically.

 

Table 2 Robots used for biological plant protection

Machine

Functions

LettuceBot2 (2nd generation)

thinning and spraying; pruning

Agribotix Hornet Drone

producing high-resolution images and maps using a variety of sensors and their processing; map processing to reveal which locations are most in need of fertilizer and protection

Wall-Ye 1000 mobile

pruning

Grizzly RUV

detecting stems and their trimming inside the soil using a laser scanner; tillage

Forge Robotic Platform

pruning and spraying

Development of Wageningen UR and Agritronics, Sint Annaparochie

spraying (point and hinged)

Precision Hawk development

providing data on the status of the territory to agronomists

SenseFly development

territory analysis and compilation of a detailed map

FLYSEEAGRO

multi-spectrum field photography

 

Because of increasing interest in and attention to ecology and health, agricultural enterprises need to address the challenge of improving the environmental safety of production. Despite the simplicity of using chemical methods to protect plants inside greenhouses, enterprises are faced with a number of negative consequences, which are difficult to measure: harm to human health (both workers and consumers) and harm to treated soil. Separately, we should note the increasing costs of creating or acquiring new chemicals due to the adaptation of pests to the chemicals used, as well as the growth of the exchange rates of major currencies against the ruble.

Many countries in Europe are currently switching or have already switched to biological methods of plant protection, although this method also has a number of drawbacks. Among the drawbacks is its slow action, so there is a need for constant monitoring of the condition of the greenhouse, which requires having specialized workers on staff.

The goal of this research is to assess the cost-effectiveness of robotic technology for biological plant protection. To achieve this goal, feasibility studies of the project will be considered, a comparative analysis of costs will be carried out, and the effectiveness of investments in robotic technology of biological protection of greenhouse plants located in the Moscow region of Russia, as well as the risks of the project will be assessed.


Conclusion

The study proposed and tested a decision-making algorithm for investments in robotic technologies of biological plant protection. The proposed decision-making algorithm will allow agricultural enterprises to make decisions on the effectiveness of investments in robotic plant protection technology projects. At the heart of the algorithm lies the financial model, which is supplemented by the technical and economic parameters of digital technology.

As a result of the study, it has been proven that the introduction of robotic biological plant protection technology improves the profitability of the agricultural enterprise; this investment pays off in two years. The project is most sensitive to such factors as a decrease in revenue for eco-products and an increase in the cost of robotic technology considering scientific and technical uncertainty in the use and creation of new technology and an increase in overall costs.

An important limitation of this study is that it was modeled on one greenhouse farm located in Russia. As part of the following detailed research, the algorithm is being tested at agricultural enterprises in other regions.

Acknowledgement

This research was supported by the Academic Excellence Project 5-100, proposed by Peter the Great St. Petersburg Polytechnic University.

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