National Investment Framework for Revitalizing the R&D Collaborative Ecosystem of Sustainable Smart Agriculture
Round 1
Reviewer 1 Report
This study focuses on the monitor the current status of R&D investment for Sustainable Smart Agriculture in South Korea and identifies tasks belonging to technical areas and regions that require sustainable cooperation in smart agriculture. This is an important topical issue with the potential to contribute to improving policies in this area.
The methodology is well described and uses its own approach to address the problem.
I just think of a question to explain the conditions for propounding project topics. These can impact the amount and focus of supported projects. The question is whether research priorities are directly determined by policymakers (government bodies) or whether the topics of submitted projects are free and based on the needs of practice in collaboration with research organizations.
The results and conclusions are well formulated and have the potential to allow for determining strategic decisions for the further development of rural areas. The developed recommendations can contribute to improving the quality of planning and forecasting activities of policymakers.
Author Response
Point-by-point responses to reviewers’ comments (details of the revisions)
Thank you for reviewing our manuscript (Sustainability—1707890) entitled “National Investment in Research and Development and Collaboration Ecosystem Framework for Sustainable Smart Agriculture in South Korea.”
We are grateful for the opportunity to submit a revised version of our manuscript and sincerely thank the reviewers for their constructive criticism and helpful comments. We believe our manuscript has improved as a result. We look forward to hearing from you and would be happy to make further changes if required.
Kindly find the responses to reviewer comments below. We sincerely appreciate the reviewers’ expert review and constructive assessment of our manuscripts and hope the responses prove to be satisfactory.
Reviewer #1 and Author's Response to the Review Report (Reviewer 1):
Comments and Suggestions for Authors:
This study focuses on the monitor the current status of R&D investment for Sustainable Smart Agriculture in South Korea and identifies tasks belonging to technical areas and regions that require sustainable cooperation in smart agriculture. This is an important topical issue with the potential to contribute to improving policies in this area.
The methodology is well described and uses its own approach to address the problem.
The results and conclusions are well formulated and have the potential to allow for determining strategic decisions for the further development of rural areas. The developed recommendations can contribute to improving the quality of planning and forecasting activities of policymakers.
Point 1: I just think of a question to explain the conditions for propounding project topics. These can impact the amount and focus of supported projects. The question is whether research priorities are directly determined by policymakers (government bodies) or whether the topics of submitted projects are free and based on the needs of practice in collaboration with research organizations.
Response 1:
We sincerely appreciate the reviewer’s comments and their expert review and the positive assessment of our manuscript. The reviewer raises an important question that can greatly enrich readers’ understanding of the conditions for suggesting research topics and the background that influences the scale and focus of the research.
Accordingly, decision-making on research priorities in Korea's R&D investment policy employs an interactive two-way approach. That is, it employs the top-down approach determined directly by the decision-making of the policymakers (governmental bodies) and an interactive approach that reflects the topic of the proposed bottom-up project based on the practical need through the collaboration of research organizations.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The work appears full of innovative insights and approaches. Therefore I loved reading this paper because it covers an interest sector nowadays more and more appreciated by academia and business. The paper investigated the current status of smart agricultural R&D investment from different perspectives. It is absolutely important to publish it for future research and for drawing new paths of study. There are mistakes and non clear points that need a re-arranging of the paper and of the structure.
The title is too long and not much appealing as it could be.
The abstract is good but from 17 to 23 lines could be necessary to consider an improvment. For example it is not clear why strawsberry sector is selected (even if the explanation is along the paper it is necessary to give some words to help the understanding.
Literature review is good but some recent works are missin (i.e.: Adamashvili, N. et al., 2021 and 2020).
57-58 lines: This will promote precision agriculture, thereby improving productivity and profitability for small farmers....The future of the verb and the sense of the sentence is not clear.
When authors want redefine the 180 concept of smart agriculture in Korea (180 line) are a bit confusing....What are you redefining? Point 1 is ok. I don't understand point 2 and 3. Point 4 and 5 are ok but all the points do not have sources of starting for redefining the SA concept in Corea.
Please define acronyms from the starting.
What do you mean with 'epistemic uncertainty can stem from either lack of knowledge or information about a phenomenon, topic, or diverging frames about the information'. [223-224]
From 273 to 279 there is a too lon not clear sentence.
The main research questions (RQs) appear questions not research questions to be investigated. RQ is a statement of a long-term objective expected to be achieved by the study.
Please explain soon why you will select strawsberry sector in method section.
The research areas related to smart agriculture were divided into eight clusters....maybe they appear too much otherwise try to summarize in a better way. All in all the paper appears too long and in some point difficutl to read because it is necessary to sum up some parts and reduce the paper in a more readble way. In some parts, the paper does not appear replicable and easy to follow. Please try to structure it and systematize the steps (reducing the 'blabla') in a better way.
Affirmation as 'nationwide. Policymakers and stakeholders of central and local governments can view the investment concentration and regional distribution and set directions to consider the appropriate government investment to enhance regional competitiveness and capabilities' are preferible in the conclusion section.
I don't understand welll the sense of the follwoing sentence 'Future research can also demonstrate the procedural effects, including of the use of information, conflict management, and increased legitimacy.'
GOOD LUCK...try to follow a file rouge and to close the loop.
Author Response
Point-by-point responses to reviewers’ comments (details of the revisions)
Thank you for reviewing our manuscript (Sustainability—1707890) entitled “National Investment in Research and Development and Collaboration Ecosystem Framework for Sustainable Smart Agriculture in South Korea.”
We are grateful for the opportunity to submit a revised version of our manuscript and sincerely thank the reviewers for their constructive criticism and helpful comments. We believe our manuscript has improved as a result. We look forward to hearing from you and would be happy to make further changes if required.
Kindly find the responses to reviewer comments below. We sincerely appreciate the reviewers’ expert review and constructive assessment of our manuscripts and hope the responses prove to be satisfactory.
Reviewer #2 and Author's Response to the Review Report (Reviewer 2):
Comments and Suggestions for Authors
The work appears full of innovative insights and approaches. Therefore, I loved reading this paper because it covers an interest sector nowadays more and more appreciated by academia and business. The paper investigated the current status of smart agricultural R&D investment from different perspectives. It is absolutely important to publish it for future research and for drawing new paths of study. There are mistakes and non-clear points that need a re-arranging of the paper and of the structure.
Point 1: The title is too long and not much appealing as it could be.
Response 1:
We have revised the title of the manuscript accordingly, as noted in the box below, for your consideration.
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(Before) National Investment in Research and Development and Collaboration Ecosystem Framework for Sustainable Smart Agriculture in South Korea
(After) National Investment Framework for Revitalizing the R&D Collaborative Ecosystem of Sustainable Smart Agriculture
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Point 2: The abstract is good but from 17 to 23 lines could be necessary to consider an improvement. For example, it is not clear why strawberry sector is selected (even if the explanation is along the paper it is necessary to give some words to help the understanding.
Response 2: Following your insightful suggestion, we have revised the abstract, as presented in the box below (the revision is marked in purple font). It briefly presents the reason for selecting the strawberry sector [Page 1, lines 18–21].
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(Revised Abstract) Abstract: Demographic, economic, and environmental issues, including climate change events, an aging population, growing urban-rural area disparity, and the COVID-19 pandemic contribute to vulnerabilities in agricultural production and food systems. South Korea has designated smart agriculture as a national strategic investment, expanding investment in research and development (R&D) to develop and commercialize convergence technologies, thus extending sustainable smart agriculture and strengthening global competitiveness. Hence, this study probes the status of smart agricultural R&D investment from the perspectives of public funds, research areas, technologies, regions, organizations, and stakeholders. It examines 5,646 public R&D projects worth USD 1,408.5 million on smart agriculture in 17 regions and eight technology clusters from 2015 to 2021. Further, it proposes a pool of potential collaborative networks via a case study of strawberry, a representative veritable crop inspiring the smart agriculture, to demonstrate the study framework’s usefulness in promoting smart agriculture and establishing a sustainable R&D collaboration ecosystem. The proposed framework, accordingly, allows stakeholders to understand and monitor the status of R&D investment from various perspectives. Moreover, given the insight into the tasks belonging to technical areas and regions that require sustainable cooperation in smart agriculture, central and local governments develop policies to reinforce sustainable smart farming models. |
Point 3: Literature review is good but some recent works are missing (i.e.: Adamashvili, N. et al., 2021 and 2020).
Response 3: Following the reviewer’s comments, we have incorporated the literature into the revised text as follows [Page 6, lines 257–263]:
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(After) Accordingly, Adamashvili et al. [54] proposed a framework to establish a successful ecosystem in the agriculture sector, which may be accomplished by a scheme where governments encourage collaborative research among key stakeholders to adopt emerging technologies. Building a digital supply chain in the agriculture sector can, for instance, accelerate a successful evolution of the ecosystem via exchanging information and knowledge among suppliers, farmers, producers, retailers, and governments [55]. |
Point 4: 57-58 lines: This will promote precision agriculture, thereby improving productivity and profitability for small farmers....The future of the verb and the sense of the sentence is not clear.
Response 4: Following the reviewer’s comments, we have revised the sentence below [Page 2, lines 55–57].
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(Before) This policy emphasizes the importance of investment in infrastructure to expand broadband Internet access service to unserved agricultural land; this will promote precision agriculture, thereby improving productivity and profitability for small farmers [8].
(After) This policy focuses on the investment in infrastructure to expand broadband Internet access to rural areas; it facilitates precision agriculture technologies, thereby improving productivity and profitability for small farmers [8]. |
Point 5: When authors want redefine the 180 concept of smart agriculture in Korea (180 line) are a bit confusing....What are you redefining? Point 1 is ok. I don't understand point 2 and 3. Point 4 and 5 are ok but all the points do not have sources of starting for redefining the SA concept in Korea.
Please define acronyms from the starting.
Response 5: First, I apologize for the confusion despite the intention to offer an in-depth explanation. We have explained the concept in Figure 2; points 2 and 3 were not necessary because they were mere addendums to point 1. Following the reviewer’s comments, we have revised the manuscript to match the concept of Figure 2 by deleting points 2 and point 3, as highlighted below [Page 4–5, lines 175–200].
(After)
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1. Smart agriculture aims to prepare a sustainability strategy for agriculture in response to factors such as climate change crises, food crises caused by population growth, limited resource utilization, and carbon emission. It employs advanced ICT (AI and big data) to improve agricultural productivity and quality, remotely or automatically manage the cultivation environment of crops and livestock, and reduce the labor force via a national innovative growth strategy for sustainable future agriculture. 2. Data-based high efficiency can maximize the convenience, productivity, and quality of agriculture by combining it with cutting-edge technologies such as Internet of things (IoT), big data, AI, and robots. Thus, digital agricultural technology can evolve by using big data on crop and livestock growth and the environment. 3. Smart agriculture largely encompasses the concepts of precision agriculture, smart farming, and digital agriculture. It refers to agriculture that achieves efficient decision-making and automation. 2. Precision agriculture is the oldest agricultural concept and includes technology for detailed monitoring of farmland and water supply and nutrients in the right place. The core technology of precision agriculture is open-field farming, which involves the cultivation of food crops, vegetables, and fruit trees. 3. Smart farming is a core technology of facility farming, including plant gardening facilities, such as greenhouses and plastic houses, livestock facilities for mass breeding of livestock, and plant factories that are closed plant cultivation facilities using artificial light. Smart-farm technology includes technologies to monitor the growth and breeding environment of crops and livestock in facility farms using Internet of things (IoT), big data, and AI and make optimal farming decisions. 4. Digital agriculture includes technology that collects, analyzes, and shares data on the agriculture and livestock industry and traces the entire process of production, processing, logistics, distribution, and consumption. Digital agriculture can be largely divided into fields such as digital agriculture data platform; digital agriculture distribution, logistics, and consumption; and data solutions and service technologies. For distribution and logistics regarding the agricultural and livestock industry, various ICTs such as big data, IoT, AI, and cloud computing are combined to implement a smart production and logistics system and smart shops. Figure 2 depicts these concepts. Figure 2. Concept of smart agriculture in South Korea [25]. |
Point 6: What do you mean with 'epistemic uncertainty can stem from either lack of knowledge or information about a phenomenon, topic, or diverging frames about the information'. [223-224]
Response 6: Following the reviewer’s comments, we have revised the sentence, as highlighted below [Page 5, lines 208–213].
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(Before) In particular, epistemic uncertainty can stem from either lack of knowledge or information about a phenomenon, topic, or diverging frames about the information.
(After) Apparently, uncertainty in decision-making is associated with three knowledge attributes: incompleteness of knowledge, unpredictability from the complex interaction, and diverging frames about knowledge. Arguably, in principle, epistemic uncertainty from the incompleteness of knowledge can be reduced by collecting more information. Therefore, studies on uncertainty focus on bridging the lack of knowledge by developing a systematic framework [30]. |
Point 7: From 273 to 279 there is a too long, not clear sentence.
Response 7: Following the reviewer’s comments, we have revised the sentences [Page 6, lines 254–266].
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(Before) Similarly, Dale and Marshall [52] argued that because governments play a facilitative role in setting policy frameworks for agricultural development, they should develop frameworks for collaborative planning at the regional scale between the governments, private sector, and rural communities to ensure agricultural development. (After) Similarly, Dale and Marshall [52] argue that policy frameworks should be developed to facilitate cooperation at the local scale among governments, the private sector, and rural communities to ensure agricultural development.
(Before) Meanwhile, Noor et al. [51] stressed that public research institutions in the agricultural sector play an essential role in supporting rural communities by creating knowledge that becomes a source for future sustained growth and providing agriculture extension services that improve farmers’ productivity, income, and employment through the conceptual public researcher-farmer partnership framework. (After) Meanwhile, Noor et al. [51] emphasized the essential role of public research institutes in agriculture to provide agricultural expansion services that improve farmers' productivity, income, and employment and generate knowledge for future sustainable growth. |
Point 8: The main research questions (RQs) appear questions not research questions to be investigated. RQ is a statement of a long-term objective expected to be achieved by the study.
Response 8: Following the reviewer's comments, we have revised the key research questions, as highlighted in the box below [Pages 7–8, lines 305–351]. Moreover, we have revised the relevant paragraph of the Discussion section of the manuscript, as per the revised research questions [Page 33–34, Lines 685–721].
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(Revised) 1.1.3. Research Purpose and Questions The target research area should be divided into small areas, and the status and trends of the sub-research areas must be examined to establish a collaboration ecosystem and R&D investment framework for smart agriculture in Korea. As noted in prior studies [60-62], this procedure is fundamental to ensuring enhanced stakeholder collaboration by reducing information uncertainty on the knowledge status in various target fields, thereby improving the quality of decision-making on national R&D. Therefore, this study presents timely, comprehensive, and useful information on the state of R&D activities in the smart agricultural sector in 17 regions of Korea using the proposed framework. The main research questions (RQs) are as follows:
RQ1: What information is required to establish the direction of investment in the agricultural R&D sector of the Korean government that this proposed framework can provide?
RQ2: Has the Korean government’s investment trend been consistently implemented since the government announced key agricultural R&D policies, such as the announcement of the 2018 Smart Farm Expansion Plan, and does such government R&D investment implementation differ per the perspective of individual regions and various innovation-performing organizations?
RQ3: Can the proposed framework generate knowledge and strategies for various stakeholders to identify the role of the R&D cooperative ecosystem for sustainable smart farming and potential collaborators, and can it be demonstrated via the case of strawberries, a representative crop item at the forefront of smart agriculture in Korea?
Eight subcategory RQs to be examined in-depth to solve the three main RQs follows:
(Revised) 4. Discussion 4.1. R&D Investment Strategy and Collaborative Ecosystem Framework for Sustainable Smart Agriculture in Korea
The proposed framework for sustainable smart agriculture in Korea provides a variety of useful information regarding research areas, regions, and stakeholders. Three RQs (eight subcategory RQs) were raised to demonstrate the usability of the framework. First, based on RQ1-1 and RQ1-2, the overall and regional status of government R&D investment in smart agriculture during 2015–2021 was revealed. First, regarding RQ1, the study provided useful information to establish the investment direction of the Korean government in the agricultural R&D sector. Specifically, regarding RQ1-1 and RQ1-2, the study revealed the overall and regional status of government R&D investment in smart agriculture during the 2015–2021 period to provide evidence to stakeholders to discuss the appropriateness of R&D investment from the Korean central and local government perspective. Regarding RQ1-3, the study examined the investment situation of government R&D from the perspective of research areas on smart agriculture in Korea to provide information to determine the concentration of research areas, thereby discussing the degree of government R&D investment in each research area. Second, based on RQ2-1, we investigated changes in the government R&D investment trend as of 2018 when the Smart Farm Expansion Plan was announced. Second, regarding RQ2, we investigated changes in the government R&D investment trend as of 2018 when the Smart Farm Expansion Plan was announced. Moreover, the implementation of such government R&D investment was analyzed for differences per individual regions and innovative organizations performing R&D. The emergent result showed that the total amount of government R&D investment increased significantly, and the direction of the investment shifted from protected agriculture, such as smart farming, to open-field agriculture. Further, the government focused on smart energy R&D while considering the global environmental issue of carbon neutrality. Thus, stakeholders can use this information to discuss the allocation of government R&D investment for the next national smart agriculture plan. Regarding RQ2-2, the study investigated the status of public R&D investment concerning technology cluster, region, and organizations. The results showed the degree of R&D capabilities of the industry-university-institutes in the regions and the regional research competitiveness, which can be the starting point to build and support an R&D collaboration ecosystem for a research area. Moreover, for central and local policymakers in charge of developing collaboration programs, these results can be adopted as fundamental information to enhance a strategic R&D collaboration or partnership in a specific research domain. Third, we chose the case of strawberry to exemplify the usability of the framework to create an R&D collaboration ecosystem. Third, regarding RQ3, the proposed framework presents the information needed to establish knowledge and strategies for various stakeholders to discover the role of the R&D cooperation ecosystem for sustainable smart farming and potential collaborators. Furthermore, we demonstrated the usefulness of the framework in creating an R&D collaboration ecosystem through the strawberry case.
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Point 9: Please explain soon why you will select strawberry sector in method section.
Response 9: Following the reviewer’s comments, the revised manuscript briefly presents the reason for selecting the strawberry sector in the methods section as follows [Page 11].
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(Before) 2.2. Clustering Process Based on previous studies [58], a co-occurrence analysis was employed to discover smart agriculture-related research areas. The number of times the ASJC codes appeared together in a project group revealed the relevance of that project. Particularly, the co-occurrence matrix revealed the number of times that elements i (from the first list) and j (from the second list) appeared together in the text, namely, i,j = ASJC codes. Then, the network was created based on the number of appearances of the ASJC codes in the projects, and it was defined using the co-occurrence matrix. All nodes in the network were drawn according to the titles of the research areas present in the ASJC codes, and the font size indicated the frequency of co-occurrence of each ASJC code compared with that of the others. By visualizing this network structure that created by the VOSViewer (Version 1.6.18, Leiden University, Leiden, The Netherlands), the relationship between the ASJC codes could be elucidated. The mapping and clustering were conducted based on previous studies [58–63]. The number of clusters ranged from 1 (γ = 0.1) to 9 (γ = 2.0). To analyze the semantic network, nine clusters were selected according to the number and combination of items (ASJC codes) in each cluster. 2.3. Definition of Research Areas Related to Smart Agriculture Smart agriculture-related research areas were labelled in consideration of reviewing the content of the R&D projects and the list of the ASJC codes in each area. The labels for research areas were determined by discussions among experts in smart agriculture and specific research areas. In the discussion process, both the distribution of ASJC codes comprising each cluster and then titles and abstracts of the R&D projects in the clusters were provided to the experts. Furthermore, to provide strategic implications, we chose the strawberries as a targeted collaborative research area. The 157 projects that contained the keyword, strawberries, were reselected from the final dataset. The entire process is presented in Figure 4.
(After) 2.2. Clustering Process The study identified smart-agriculture research areas via the co-occurrence matrix and investigated the relationship between ASJC codes by understanding the network structure visualized by the VOSViewer (Version 1.6.18, Leiden University, Leiden, The Netherlands) [60-65]. The number of clusters ranged from 1 (γ = 0.1) to 9 (γ = 2.0) by adjusting a resolution parameter (γ). Given the items (ASJC codes) and titles and abstracts of research projects in each cluster, eight clusters were selected.
2.3. Definition of Research Areas Related to Smart Agriculture Smart-agriculture research areas were labeled after reviewing the content of the R&D projects and the list of the ASJC codes in each area. The labels for research areas were determined via discussions among experts in smart agriculture and relevant research areas. In the discussion, the distribution of ASJC codes comprising each cluster and titles and abstracts of the R&D projects in the clusters were provided to the experts.
2.4. Targeted Collaborative Research Area: Strawberries
Furthermore, to provide strategic implications, the study targeted strawberries as a collaborative research area. Strawberry production in Korea accounted for 10.9% (1,023 million) of the total vegetable production, ranking as the largest among vegetable crops in 2021. The penetration rate of domestic strawberry varieties exceeded 96.3% relative to 9% in 2005, and the export amount of strawberries reached 53.7 million dollars relative to 4.4 million dollars in 2005. From the regional perspective, Gyeongsangnam-do, Jeollanam-do, and Jeollabuk-do were ranked as the largest strawberry cultivation area [66]. The 157 projects that contained the keyword, strawberries, were reselected from the final dataset. Figure 4 presents the entire process. |
Point 10: The research areas related to smart agriculture were divided into eight clusters....maybe they appear too much otherwise try to summarize in a better way. All in all the paper appears too long and in some point difficult to read because it is necessary to sum up some parts and reduce the paper in a more readable way. In some parts, the paper does not appear replicable and easy to follow. Please try to structure it and systematize the steps (reducing the 'blabla') in a better way.
Response 10: We agree with the reviewer's comments that the description of the cluster is too long and therefore needs to be trimmed. Accordingly, we have summarized and simplified the paragraph as follows [Page 14].
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(Before) 3.1.1. Goals of Cluster 1 (Crops and Livestock): Crop Production, Growth, Livestock Growth, and Health Management Technology for Smart Agriculture • Technology for measuring crop growth (height, lateral area, stem/leaf thickness, tree shape, lateral water, flowering, fruit, etc.) and physiology (photosynthesis, respiration, nutrient deficiency, and livestock specifications [height and body shape, weight and growth rate, fat layer thickness and muscle fat ratio, etc.]) • Technology for intelligently and automatically controlling the optimal amount/type of feed and water supply based on the measurement and measurement values of feed and water intake (plus excretion, or even separation of excrement) depending on the breed to be raised • Technology to detect the presence or absence of pathogens (bacteria, fungi, viruses, and insects) that pose a threat to crop and livestock growth, or to measure and differentiate pests and diseases based on measurements of biometric and specification information and image and image information • Technologies such as machines and devices that provide appropriate methods and means of action preemptively or post-mortem based on diagnostic and measurement values for pests and health, or that take measures automatically and intelligently to some extent • Technology to control the growth and production environment to produce the ingredients and nutrients desired for each crop and livestock of the maximum amount and quality • Biological detection of antibodies, antigens, enzymes, proteins, immune molecules, DNA, etc., using a variety of substances, ranging from nanoparticles, nanotubes, and nanorods, to nanowires • A platform for optimizing resource management, improving resource productivity, and providing information for resource utilization efficiency, such as facility horticulture or livestock resources, cost reduction, and environmental load reduction
3.1.2. Goals of Cluster 2 (Smart Energy): Renewable Energy Utilization Technology for Agricultural Power Generation for Smart Agriculture • Technology to maintain and manage homeostasis in optimal conditions using minimal energy for temperature and air quality inside the facility according to crops and livestock to be cultivated • Technology that utilizes various new and renewable energy such as a combination of solar, hydropower, and natural gas to be used as agricultural energy
3.1.3. Goals of Cluster 3 (Agri-Food/Supply Platform): Integrated Management Platform (Distribution, Logistics, and Consumption) for Digital Agriculture • Integrated management and marketing support platform to ensure the convenience of producers and consumers through information sharing; supply and demand management; distribution management; and distribution management between suppliers and consumers of producers, distributors, small and medium-sized businesses, and logistics companies
3.1.4. Goals of Cluster 4 (Data·Network·AI): AI for Digital Agriculture • Information providing platform for optimal environmental control and management through real-time data collection in facility horticulture or livestock and big data analysis, such as information on temperature, humidity, light, mineral, light wavelength, and oxygen and carbon dioxide concentrations • A platform for collecting information on environmental growth, agricultural work, management, and facility structure; controlling data in smart farms in real time; providing an analyzable work environment (interface) using AI algorithms, etc.
3.1.5. Goals of Cluster 5 (Agricultural Machinery): Smart Agricultural Machinery and Agricultural Drone for Precision Agriculture • Technology that utilizes agricultural machinery and robots such as for sowing; formal transplantation; harvesting; irrigation; management of government expenses; pesticide spraying; management of specifications such as standing, feeding, water supply, and feeding of livestock; milking; fertilization; composting; cleaning, etc. • Technology that collects data from agricultural sites with imaging equipment and sensors mounted on unmanned aerial vehicles, analyzes crops with soil and water quality information, and utilizes soil and land development sites
3.1.6. Goals of Cluster 6 (Farm Robots): AI Farmbots for Smart Farms • AI robot technology that can autonomously perform optimal agricultural work according to the situation by measuring and monitoring the growth and physiological status of crops and livestock specifications, health information, and dynamic status in real time
3.1.7. Goals of Cluster 7 (Environmental Information): Complex Environmental Information Measurement and Control Technology for Smart Agriculture • Technology to measure external factors affecting the growth and development of crops and livestock, such as temperature, humidity, and air quality (light, oxygen, carbon dioxide, ammonia, etc.) in facilities for cultivation and breeding of agriculture and livestock, respectively • Technology that intelligently and automatically controls optimal environmental conditions that can secure the best quality and productivity for crops to be cultivated and livestock raised based on environmental information measurement values • Technology to measure the amount of water and nutrients in soil, medium, and nutrient solution; composition of ingredients; conditions of ingredients (pH, electrical conductivity, osmotic pressure, etc.); absorption rate, etc., depending on the crop to be cultivated • Technology for intelligently and automatically controlling the optimal amount of water and nutrients, component composition, and component conditions that can ensure the best quality and quantity of crops to be cultivated based on the irrigation pipe ratio measurement value.
3.1.8. Goals of Cluster 8 (Plant Factory): Urban Agriculture Technology Including Indoor Vertical Farming System or Plant Factory for Smart Farms • Technology to design, control, and utilize complex facilities and equipment to realize the prelude for crop and livestock production activities in a completely closed space (building, container, sterile room, etc.) for special purposes such as controlling production time and growth speed, minimum land use, and enhancement
(After) 3.1.1. Goals of Cluster 1 (Crops and Livestock): Crop Production, Growth, Livestock Growth, and Health Management Technology for Smart Agriculture. It included technologies for measuring crop growth and physiology, and detecting the presence of pathogens, identifying pests and diseases.
3.1.2. Goals of Cluster 2 (Smart Energy): Renewable Energy Utilization Technology for Agricultural Power Generation for Smart Agriculture. It covered technologies to maintain and manage homeostasis in optimal conditions using minimal (renewable) energy.
3.1.3. Goals of Cluster 3 (Agri-Food and Supply Platform): Integrated Management Platform (Distribution, Logistics, and Consumption) for Digital Agriculture. It implied a platform that optimizes efficient management and marketing by sharing information about producers, consumers, and logistics companies.
3.1.4. Goals of Cluster 4 (Data·Network·AI): AI for Digital Agriculture. It contained technologies that collect real-time big data in facility horticulture or livestock and optimize environmental conditions in the AI algorithms.
3.1.5. Goals of Cluster 5 (Agricultural Machinery): Smart Agricultural Machinery and Agricultural Drone for Precision Agriculture. It included technologies that utilize agricultural machinery and robots and collect data from agricultural sites with imaging equipment and sensors mounted on unmanned aerial vehicles.
3.1.6. Goals of Cluster 6 (Farm Robots): AI Farmbots for Smart Farms. It covered technologies that can autonomously perform optimal agricultural work, as per the situation, by analyzing the status of crops and livestock.
3.1.7. Goals of Cluster 7 (Environmental Information): Complex Environmental Information Measurement and Control Technology for Smart Agriculture. It included technologies to measure external factors like temperature, humidity, and air quality.
3.1.8. Goals of Cluster 8 (Plant Factory): Urban Agriculture Technology, including Indoor Vertical Farming System or Plant Factory for Smart Farms. It included technology to design, control, and utilize complex facilities and equipment to realize the prelude for crop and livestock production activities in a completely closed space. |
Point 11: Affirmation as 'Policymakers and stakeholders of central and local governments can view the investment concentration and regional distribution and set directions to consider the appropriate government investment to enhance regional competitiveness and capabilities' are preferable in the conclusion section.
Response 11: We agree with the comments that the above sentence is preferred for the Conclusion section. Therefore, we have incorporated that sentence into the conclusion section of the revised manuscript [Page 35, lines 756–769].
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(Before) nationwide. Policymakers and stakeholders of central and local governments can view the investment concentration and regional distribution and set directions to consider the appropriate government investment to enhance regional competitiveness and capabilities.
(After) 4.2. Conclusions This study makes two important contributions. First, it suggested the framework for government R&D investment and collaboration in the smart-agriculture sector. Many prior studies [49–53] provided directions or recommendations to develop better smart agricultural policies without considering government R&D investment information. However, it may create a bias in stakeholders during decision-making [45], thereby increasing ambiguity and the number of differing perspectives held by stakeholders [30, 31]. This study addressed the limitation in the literature [49–53] by discussing the fundamental functions of a robust framework that enables stakeholders to understand the research investment situation, monitor research investment progress, and identify challenges in different technological areas and regions that need collaboration to ensure sustainability [35, 39]. Thus, policymakers and stakeholders of central and local governments can view the investment concentration and regional distribution and set directions to consider the appropriate government investment to enhance regional competitiveness and capabilities. |
Point 12: I don't understand well the sense of the following sentence 'Future research can also demonstrate the procedural effects, including of the use of information, conflict management, and increased legitimacy.'
Response 12: Following the reviewer’s comments, we have revised the sentence as follows [Page 35, 800–806].
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(Before) Future research can also demonstrate the procedural effects, including the use of information, conflict management, and increased legitimacy.
(After) Meanwhile, to ensure the legitimacy of policy decision-making, future studies must develop a fair procedure that can reduce conflicts between stakeholders. Thus, for decision-makers, future studies can conduct a qualitative analysis of the degree of fairness in the information production procedure of the proposed framework and whether the information included multiple perspectives and greater transparency and investigated how the legitimacy is affected by participants' perspectives in an extended consideration. |
Author Response File: Author Response.pdf
Reviewer 3 Report
Dear authors,
I congratulate you on your chosen topic.
My main suggestions are as follows:
Please remove the hyphen after the word "short" in line L31.
Perhaps it should be specified what agriculture 4.0 means, just after the L41 line.
Please provide a research hypothesis for each research question.
Please check if figure 4 has the same text font as the rest of the article.
Please write the name of the regions for figure 8.
Author Response
Point-by-point responses to reviewers’ comments (details of the revisions)
Thank you for reviewing our manuscript (Sustainability—1707890) entitled “National Investment in Research and Development and Collaboration Ecosystem Framework for Sustainable Smart Agriculture in South Korea.”
We are grateful for the opportunity to submit a revised version of our manuscript and sincerely thank the reviewers for their constructive criticism and helpful comments. We believe our manuscript has improved as a result. We look forward to hearing from you and would be happy to make further changes if required.
Kindly find the responses to reviewer comments below. We sincerely appreciate the reviewers’ expert review and constructive assessment of our manuscripts and hope the responses prove to be satisfactory.
Reviewer #3 and Author's Response to the Review Report (Reviewer 3):
Comments and Suggestions for Authors :
Dear authors,
I congratulate you on your chosen topic.
My main suggestions are as follows:
Point 1: Please remove the hyphen after the word "short" in line L31.
Response 1: Following the reviewer’s comments, I have removed the hyphen after the word “short” on page 1 (kindly see below) [Page 1, line 30].
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(Before) Both short- and long-term environmental challenges—including climate change events, (After) Short and long-term environmental challenges—including climate change events, |
Point 2: Perhaps it should be specified what agriculture 4.0 means, just after the L41 line.
Response 2: Following the reviewer’s comments, we have stated what agriculture 4.0 (kindly see below) [Page 1, line 39–41].
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(Before) This concept has been expressed using different terms, including smart farming, precision agriculture, precision farming, digital agriculture, and agriculture 4.0 [4].
(After) This concept, expressed through different terms, including smart farming, precision agriculture, precision farming, digital agriculture, and agriculture 4.0, aims to strengthen the efficiency of agricultural activities by adopting smart systems that provide operational solutions based on data from agricultural production [4]. |
Point 3: Please provide a research hypothesis for each research question.
Response 3: Following the reviewer's comments, we have revised the key research questions, as highlighted in the box below [Pages 7–8, lines 305–351]. Moreover, we have revised the relevant paragraph of the Discussion section of the manuscript, as per the revised research questions [Page 33–34, Lines 685–721].
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(After) 1.1.3. Research Purpose and Questions The target research area should be divided into small areas, and the status and trends of the sub-research areas must be examined to establish a collaboration ecosystem and R&D investment framework for smart agriculture in Korea. As noted in prior studies [60-62], this procedure is fundamental to ensuring enhanced stakeholder collaboration by reducing information uncertainty on the knowledge status in various target fields, thereby improving the quality of decision-making on national R&D. Therefore, this study presents timely, comprehensive, and useful information on the state of R&D activities in the smart agricultural sector in 17 regions of Korea using the proposed framework. The main research questions (RQs) are as follows:
RQ1: What information is required to establish the direction of investment in the agricultural R&D sector of the Korean government that this proposed framework can provide?
RQ2: Has the Korean government's investment trend been consistently implemented since the government announced key agricultural R&D policies, such as the announcement of the 2018 Smart Farm Expansion Plan, and does such government R&D investment implementation differ per the perspective of individual regions and various innovation-performing organizations?
RQ3: Can the proposed framework generate knowledge and strategies for various stakeholders to identify the role of the R&D cooperative ecosystem for sustainable smart farming and potential collaborators, and can it be demonstrated via the case of strawberries, a representative crop item at the forefront of smart agriculture in Korea?
Eight subcategory RQs to be examined in-depth to solve the three main RQs follows:
(Revised) 4. Discussion 4.1. R&D Investment Strategy and Collaborative Ecosystem Framework for Sustainable Smart Agriculture in Korea
The proposed framework for sustainable smart agriculture in Korea provides a variety of useful information regarding research areas, regions, and stakeholders. Three RQs (eight subcategory RQs) were raised to demonstrate the usability of the framework. First, based on RQ1-1 and RQ1-2, the overall and regional status of government R&D investment in smart agriculture during 2015–2021 was revealed. First, regarding RQ1, the study provided useful information to establish the investment direction of the Korean government in the agricultural R&D sector. Specifically, regarding RQ1-1 and RQ1-2, the study revealed the overall and regional status of government R&D investment in smart agriculture during the 2015–2021 period to provide evidence to stakeholders to discuss the appropriateness of R&D investment from the Korean central and local government perspective. Regarding RQ1-3, the study examined the investment situation of government R&D from the perspective of research areas on smart agriculture in Korea to provide information to determine the concentration of research areas, thereby discussing the degree of government R&D investment in each research area. Second, based on RQ2-1, we investigated changes in the government R&D investment trend as of 2018 when the Smart Farm Expansion Plan was announced. Second, regarding RQ2, we investigated changes in the government R&D investment trend as of 2018 when the Smart Farm Expansion Plan was announced. Moreover, the implementation of such government R&D investment was analyzed for differences per individual regions and innovative organizations performing R&D. The emergent result showed that the total amount of government R&D investment increased significantly, and the direction of the investment shifted from protected agriculture, such as smart farming, to open-field agriculture. Further, the government focused on smart energy R&D while considering the global environmental issue of carbon neutrality. Thus, stakeholders can use this information to discuss the allocation of government R&D investment for the next national smart agriculture plan. Regarding RQ2-2, the study investigated the status of public R&D investment concerning technology clusters, regions, and organizations. The results showed the degree of R&D capabilities of the industry-university-institutes in the regions and the regional research competitiveness, which can be the starting point to build and support an R&D collaboration ecosystem for a research area. Moreover, for central and local policymakers in charge of developing collaboration programs, these results can be adopted as fundamental information to enhance a strategic R&D collaboration or partnership in a specific research domain. Third, we chose the case of strawberry to exemplify the usability of the framework to create an R&D collaboration ecosystem. Third, regarding RQ3, the proposed framework presents the information needed to establish knowledge and strategies for various stakeholders to discover the role of the R&D cooperation ecosystem for sustainable smart farming and potential collaborators. Further, we demonstrated the usefulness of the framework to create an R&D collaboration ecosystem through the strawberry case.
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Point 4: Please check if figure 4 has the same text font as the rest of the article.
Response 4: Following the reviewer’s comments, the text font in Figure 4 has been revised to match the rest of the article (kindly see below) [Page 11].
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See the attached. (After) |
Point 5: Please write the name of the regions for figure 8.
Response 5: Following the reviewer’s comments, we have marked the area names on the map in Figure 8 (kindly see below).
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See the attached.
(After)
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Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I am Happy and satisfid with the revisions and changes made by the authors. In the current forma...the paper appears really improved and suitable to the level and standards of the Journal. Good luck for the future of this research
