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Review

Technological Innovations for Agricultural Production from an Environmental Perspective: A Review

by
Patricio Vladimir Méndez-Zambrano
1,*,
Luis Patricio Tierra Pérez
1,
Rogelio Estalin Ureta Valdez
2 and
Ángel Patricio Flores Orozco
3
1
Grupo de Investigación Innovación y Tecnología Morona Santiago, Escuela Superior Politécnica de Chimborazo, Sede Morona Santiago, Macas 140101, Ecuador
2
Grupo de Investigación de Recursos Mineros e Ingeniería, Escuela Superior Politécnica de Chimborazo, Sede Morona Santiago, Macas 140101, Ecuador
3
Grupo de Investigación Integral Para el Desarrollo Sustentable, Escuela Superior Politécnica de Chimborazo, Sede Morona Santiago, Macas 140101, Ecuador
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(22), 16100; https://doi.org/10.3390/su152216100
Submission received: 13 September 2023 / Revised: 15 November 2023 / Accepted: 15 November 2023 / Published: 20 November 2023
(This article belongs to the Section Sustainable Agriculture)
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Abstract

:
Information and communication technology (ICT) in developing countries is a key element for growth and economic development. This work conducted an evaluation regarding the use of ICT to reduce the socioeconomic gaps of rural populations and promote its inclusion in development plans, considering its use to guarantee a sustainable development model. For this, a systematic review of 280 articles was carried out using the Scopus, Latindex, Scielo, Dialnet, Redalyc, and Google Scholar databases during the period from 2018 to 2023, of which 40 articles were selected that address the use of ICTs and the agricultural digitalization for the management of soil, water, and the application of fertilizers and agrochemicals, which guarantee sustainable agricultural development. The results show that there are numerous digital tools available based on artificial intelligence (AI), machine learning (ML), drones, apps, and the Internet of Things, which aid in soil and water management and make use of agrochemicals and water, thus improving efficiency and reducing pollution problems. However, there is a large gap at the international level in acquiring state-of-the-art technological equipment that takes advantage of the potential that exists in terms of new technologies and their efficient use. Much of the research on the use of ICTs in the agricultural field comes from countries with medium or high levels of technological development, especially from Asia, Europe, or North America. As a result, Latin America lags behind in this regard.

1. Introduction

Developing countries face significant challenges in their pursuit of economic growth [1], given that they possess more traditional production systems compared to developed countries [2]. It is natural for these countries to seek new technologies for implementation across various sectors of society in order to enhance and expand their existing capabilities in terms of producing goods and services.
Information and communication technologies (ICTs) are considered tools that enhance productivity and competitiveness within companies and production units. These benefits increase as the usage and adoption of ICTs grow [3]. Similarly, agricultural enterprises are under pressure to adopt information and communication technologies due to quality and safety requirements. Consumers are adopting models like those in developed countries, compelling businesses to compete in regional and local markets with established standards for traded products [4].
Therefore, it is crucial to implement effective strategies that contribute to growth and economic development in tropical agricultural regions. These regions produce the food demanded by the global population despite challenges posed by climate conditions [5] and soil composition [6]. Among these strategies are ICTs, which encompass a wide range of devices and services that assist farmers in collecting, storing, analyzing, and sharing information. These technologies grant access to services such as mobile banking, satellite-provided up-to-date weather reports, as well as drones for detailed aerial imagery in numerous ways [7].
Information and communication technologies (ICTs) play a pivotal role in developing countries, offering opportunities for global integration. They improve access to more affordable connectivity, including broadband availability, transform the provision of basic services, drive innovation and productivity growth, and enhance competitiveness. Nevertheless, within this context, it is imperative to ensure optimal management of soil and water resources to minimize the impact of excessive agrochemical use, particularly insecticides [8], fertilizers [9], and herbicides [10].
To achieve greater efficiency in natural resource management in agricultural production, production systems are shifting toward precision agriculture [11], evolving into smart agriculture [12]. This approach relies on technological innovations that enable the handling of vast amounts of data for decision-making during the application of fertilizers, insecticides, and herbicides. The most commonly used tools are based on artificial intelligence, machine learning [13], drones [14], mobile apps [15], and the Internet of Things [16], which facilitate soil and water management.
According to [17], most countries in Latin America and the Caribbean are still in the early stages of utilizing ICTs in small and medium-sized agriculture due to various limitations. Despite this, they are developing projects related to the productive use of telecommunications, electronics, and ICTs, contributing to the strengthening of socioecological independence. However, this is insufficient to meet demand, alongside strong imports, volumes, and restrictions that negatively impact the region’s development, particularly in terms of innovation and job creation [18].
Among the primary concerns of international organizations analyzing the global economic and social situation is the inequality between populations in developed and developing countries. This is particularly evident in the technological field, leading to a significant digital divide caused by factors such as the inability to access new technologies, inefficiency in their use, unawareness of the benefits of new technologies for individual well-being, and a lack of digital competencies for effective participation and adoption of new technologies [19].
On the other hand, the importance of these technologies, the internet, and digital public services lies in ensuring that all of society can utilize them and all their functions fairly and equitably. Therefore, it is understood that cities are at the forefront of balancing equal access to services, efficiency, availability, choice, security, and the rights of all citizens. However, rural communities, which are responsible for the country’s agricultural production, also have this need [20].
The main challenge lies in identifying the most effective strategies to bridge the digital divide, thereby driving robust economic development and sustainable agricultural competitiveness in developing countries [21]. How can mitigating the digital divide catalyze economic progress and strengthen sustainability and competitiveness in agriculture in these nations? This research focuses on mapping digital tools that empower Latin American communities to adopt innovations that increase agricultural productivity while fostering responsible environmental stewardship [22]. The study pays special attention to the precise and rational application of fertilizers, insecticides, and herbicides to reduce the environmental and health risks associated with their excessive use, thus reducing the contamination of soil and water resources.

2. Materials and Methods

2.1. Bibliometric Analysis

The quantitative analysis of the information provided by Scopus is conducted using a bibliometric approach to assess the scientific production related to the importance of ICTs and agricultural digitization from an environmental perspective. Furthermore, the study provides a qualitative method by examining published research papers in the relevant field. It is also applied to a bibliographical review to describe various authors’ stances on the proposed topic. Data collection was conducted through the Scopus platform, using a methodological approach structured in three essential phases:
Phase 1: Data Collection. We initiated the exhaustive search for relevant information in the Scopus database, employing specific keywords and search criteria to ensure the collection of relevant and up-to-date data.
Phase 2: Article Selection. We proceeded to the selection of publications, filtering the results according to their relevance, quality, and pertinence. This critical process ensured that only articles that met the standards and objectives of the study were considered for further analysis.
Phase 3: Interpretation of the Information. Finally, we analyzed and interpreted the data obtained, drawing meaningful conclusions and identifying patterns and trends within the field of study. This stage was crucial for a thorough understanding of the subject and contribution to the existing body of knowledge.

2.2. Information Search Method

For the development of this research, a bibliographical review methodology was applied using the technique of documentary exploration. The research was conducted in two stages: the heuristic stage, based on the identification of valuable information sources, refers to experts in the field who carried out a review of the interfaces and processes involved, and the hermeneutic stage, which synthesized the information and generated commentary based on theoretical foundations [23].
The method employed in the research allowed the analysis of a wide range of papers and provided an easier comparison of relevant topics. It also drew together a significant number of bibliographical sources, taking into consideration their different perspectives and research strategies, including hermeneutics.

2.3. Techniques Used

After the initial selection of the information, the key issues were identified and classified according to their impact, which facilitated a direct and thorough evaluation of each publication. Subsequently, the most relevant data were extracted to ensure accurate and appropriate interpretation.

2.4. Inclusion Criteria

The articles selected for this study contain terminology related to the title and meet the inclusion criteria, in addition to having been published within the designated period from 2018 to 2023. The search strategy was focused on specific terminology to align the results obtained with the expected objectives and previous studies about the relevance of ICT and digitization in agriculture from an environmental perspective. The sources consulted included recognized databases and digital journals, such as Google Scholar, Latindex, and Scopus, with special interest in technological innovations applied to the agricultural sector in Latin America and with particular attention to the efficient management of soil and water and the use of fertilizers and agrochemicals to promote sustainable agricultural development.

2.5. Exclusion Criteria

Publications that deviated from the content of this study or lacked logical coherence were not taken into consideration. Publications lacking a scientific foundation and reference databases derived from unrelated survey products were excluded. Abstracts and conference communications were also excluded from the study.

2.6. Quality of the Selected Articles

The determination of the methodological quality of the consulted documents followed the application of the “Critical Review Form for Quantitative Studies,” which provides a systematic and standardized framework. This instrument assesses the quality of manuscripts based on the following categories: poor methodological quality ≤ 11; acceptable methodological quality 12–13; good methodological quality 14–15; very good methodological quality 16–17; and excellent methodological quality ≥ 18 [24,25].
Additionally, scientific documents that reported the results of qualitative studies will be selected. From these, those with an average citation count (ACC) index greater than 1.50 will be chosen. The ACC index will be determined using the “Average Citation Count” instrument.

3. Results

From the document review, 40 articles were selected. These articles pertain to the use of ICTs and agricultural digitization from an environmental perspective during the period from 2018 to 2023. They are categorized into five distinct categories, as depicted in Figure 1:
From the bibliometric analysis, it is evident that the majority of articles considering the use of ICTs and agricultural digitization from an environmental perspective are related to the employment of artificial intelligence (AI) with thirteen articles, followed by machine learning (ML) with eight articles. Articles that discuss the use of drones follow with four articles, and finally, the least reported categories are mobile apps and the Internet of Things (IoT), each with two articles, as depicted in Figure 2.
On the other hand, in relation to environmental issues monitored by ICTs and digital tools during the period from 2018 to 2023 (Figure 3), applications have been most frequently used for natural resource management (soil and water management: 40%), as well as agronomic management (fertilizer and agrochemical application: 40%). Additionally, they have been utilized for monitoring overall agricultural production (20%).
After completing the bibliometric analysis, we proceeded to apply hermeneutics, an interpretative method aimed at revealing the deep meaning of the texts, on the 40 chosen articles. Specifically, the initial articles highlight the relevance assigned to the implementation of digital tools in agricultural production systems during the period from 2018 to 2023. The main findings are condensed in Table 1, with a detailed explanation presented below:
Innovations in the agricultural field, focused on precision agriculture and the intensive use of ICTs, have marked a turning point in the efficiency and sustainability of the sector. The automation of agricultural activities, as highlighted in the studies reviewed, has resulted in significant time savings and greater precision in the application of resources such as herbicides, insecticides, and fertilizers [26]. In addition, the adoption of digital tools, including machine learning, has expanded the scope of agriculture beyond productivity, addressing crucial environmental challenges such as climate change and water quality [27]. The integration of ICTs in agriculture has facilitated knowledge management and innovation, optimizing the management of natural resources and improving the quality of final products, as seen in specific examples from countries such as Ecuador [28,29].
Technological advances in agriculture, especially through the Internet of Things (IoT) and the use of drones, have provided essential tools to predict and adapt to changes in microclimates and to collect data more accurately and efficiently [30]. These emerging technologies not only improve agricultural productivity and efficient information management but are also crucial for meeting the challenges of climate change and ensuring the sustainable development of the sector [31]. Drones, in particular, have revolutionized data collection, enabling more accurate and regular monitoring of agricultural conditions, resulting in reduced costs and more efficient crop management [32]. Together, these technologies represent a fundamental transformation in agriculture, offering innovative solutions for resource management and adaptation to environmental challenges.
The second group of articles highlights the importance of digital tools used for water management during the period from 2018 to 2023, as listed in Table 2, with their main findings described below:
The incorporation of ICTs in water management has proven to be fundamental in improving access to crucial information and increasing participation in environmental decisions. Digital tools, especially in irrigation and drinking water management, have proven to be effective in addressing the challenges of depleting high-quality water sources [33]. Advances in hardware and software not only optimize data acquisition in agriculture but also facilitate the management of an adequate water balance for crops, highlighting their relevance in scalability and adaptability to the future needs of the sector [34].
The use of machine learning in applications such as early warning, mapping, and remote sensing has significantly improved watershed management and agricultural planning [35]. These methods have enabled efficient analysis and modeling of hydrometeorological data, which is crucial for sustainable water management. In addition, the controlled management of irrigation systems through the Internet of Things (IoT) and the use of big data and machine learning have proven to be essential for more efficient and environmentally sustainable water management, reducing costs and ensuring water quality for human consumption [36,37,38].
Emerging technologies such as big data and machine learning are revolutionizing hydrology and environmental studies. The implementation of hybrid machine learning models, such as those based on decision trees, has improved the accuracy of short-term water quality prediction [39]. This accuracy is invaluable in contexts of water scarcity, ensuring effective management of water resources [40]. Furthermore, the integration of these technologies with advanced agrometeorological networks and state-of-the-art sensors enables real-time data acquisition and analysis, facilitating informed and accurate decisions in agriculture and water management.
The third group of articles highlights the importance of digital tools used for land management during the period from 2018 to 2023, listed in Table 3, with their main findings described below:
The use of digital tools, especially artificial intelligence (AI), has revolutionized soil management in agriculture. These technologies have enabled controlled and efficient access to information, facilitating the planning and management of natural resources in open field and greenhouse agriculture. Advances in deep learning (DL) and machine learning (ML) have shown a significant impact on the investigation of phenomena such as desertification, providing a more interdisciplinary and global approach [41]. In addition, AI has proven to be crucial in agricultural policy formulation, identifying areas with agricultural potential and determining best practices to preserve soil suitability and promote sustainable agriculture [42].
The integration of hybrid intelligent models in soil management has significantly improved efficiency in areas such as soil moisture, infiltration, and erosion [43]. These models, which include advanced AI techniques such as artificial neural networks, support vector machines, and cubistic regression, have improved the accuracy in estimating crucial variables such as soil organic carbon variability and susceptibility to erosion [44,45]. In addition, the application of AI in the investigation of remediation methods contributes to the remediation of contaminated soils, reducing costs and minimizing environmental impact, which underlines the relevance of these technologies in sustainable soil management [46,47].
The fourth group of articles highlights the importance of digital tools used for fertilizer application during the period from 2018 to 2023, listed in Table 4, with their main findings described below:
Mobile applications and artificial intelligence (AI) technologies are revolutionizing fertilizer dosing in agriculture by providing intuitive and customizable interfaces that adapt to various agroecosystems [48,49]. This knowledge can be used to develop a recommendation system based on machine learning approaches [50]. These tools not only facilitate data management and acquisition but also improve resource use efficiency and reduce environmental pollution [51]. The ability of these applications to connect with neural networks and adapt to variations in the soil significantly increases yields and profitability while improving environmental sustainability.
Complementing AI with machine learning programs in agriculture provides valuable insights to optimize agricultural decisions. Algorithm-based systems such as support vector machines and random forests enable accurate recommendations on fertilizer types and amounts, improving productivity and minimizing environmental impact [52,53]. These technological advances facilitate more effective soil nutrient management, contributing to soil fertility and long-term sustainability.
The integration of machine learning models in intelligent fertilization systems represents a significant advance in precision agriculture [54]. These systems not only improve agricultural yield predictions but also enable efficient resource management under constrained soil and environmental conditions. The application of AI based on nitrogen–phosphorus–potassium (NPK) spectroscopy in greenhouses and hydroponic systems highlights the ability of these technologies to increase agricultural productivity in small spaces, thus addressing the challenges of modern agriculture [55].
The final group of articles highlights the importance of digital tools used for agrochemical application during the period from 2018 to 2023 period, listed in Table 5, with their key findings described below:
Technological innovations in agriculture, especially the use of artificial intelligence (AI) and intelligent sensing and application systems, are transforming agrochemical management [56]. These technologies enable more precise and localized dosing of herbicides and other products, significantly reducing the overuse and risks associated with agrochemicals [57]. Advanced weed detection systems and variable rate sprayers, such as the VGG-16 model, have proven to be effective in reducing costs, minimizing environmental pollution risks, and promoting more sustainable agricultural practices that are safer for human health [58,59,60].
The use of drones in agrochemical applications represents a significant advance in precision agriculture, offering considerable economic and environmental advantages. Despite the high initial investment cost, drones save time and resources, reduce the use of water and pesticides, and minimize environmental impact [61]. Experimental results confirm the efficiency of these systems in various agricultural contexts, from small properties to large farms [62,63]. Their ability to apply products accurately and efficiently results in lower management costs and reduced environmental impact, marking an important step towards more sustainable and responsible agricultural practices.

4. Discussion

The results show the importance of technological innovations for optimal environmental management of natural resources within the context of sustainable agricultural production. Despite the heavy reliance of Latin American countries on agriculture, the development of prototypes to enhance agricultural production mainly originates from technologically advanced countries. These countries have developed mobile applications, artificial intelligence systems, big data management [64], drone usage [65], and automated algorithms [66] to enhance decision-making, especially in aspects related to production, such as fertilization, risk assessment, and pest and disease control.
While the range of innovation is diverse, the importance of technological innovations for soil management was prominently highlighted. Soil is highly affected by degradation processes due to contamination [67], salinization [68], erosion [69], and acidification [70]. Addressing these issues requires changes in land use patterns, including mechanization [71], fertilization [72], and agrochemical use [73] to minimize environmental impact.
Another resource requiring optimized management is water, which is impacted by pollution and climate change [74]. Water scarcity affects both agricultural production [75] and consumption of potable water [76]. Monitoring water quantity and ensuring quality is crucial due to the increasing accumulation of contaminants from anthropogenic activities [77], impacting aquatic life [78], aquatic flora [79], and populations consuming contaminated water [80].
Naseem et al., 2021 [81] examine the environmental impact of agriculture in Latin America and the Caribbean from 1971 to 2018, finding a positive correlation between agricultural practices and increased CO2 emissions, as well as a fluctuating influence of GDP and renewable energy on environmental degradation. Using the ARDL methodology, the urgency of comprehensive approaches to align economic development with sustainability is highlighted. It also suggests the redefinition of rural development policies towards equity and sustainability, promoting community self-sufficiency, resource conservation, and food security, supported by successful local experiences and the adoption of sustainable technological assessments [82]. Finally, it discusses the importance of combining well-founded policies with their inclusion in international agendas for the success of sustainable urban food strategies [83].
The digitization of the agricultural sector is progressing with a focus on pervasive networks, raising enthusiasm for its potential for efficiency and sustainability, although there are also concerns about its social repercussions and the accumulation of power and data [84]. Although automation and digitization promise to increase efficiency and sustainability in agriculture, high costs, and the digital skills gap limit their adoption, particularly in low-income nations [85]. In Latin America, an era of technological and digital modernization is emerging, where innovation in clean energy and the use of conventional resources are converging. The lithium boom and the move towards precision agriculture are emerging as catalysts for economic change and adaptation to the new post-pandemic reality [86].
Lastly, the most significant advancements have been in agrochemical application optimization. Reports demonstrate tools in precision agriculture based on automated algorithms [87] and drone usage [88]. Although these advancements may not have led to greater pest and disease control efficiency, they have yielded economic and environmental benefits. These include reduced application time, decreased agrochemical usage, minimized health risks to workers and surrounding populations, and lowered soil and water contamination risks.
Technological innovations in agricultural production offer a double benefit: they revolutionize farming techniques and improve management of the environmental impact of agriculture [89]. These emerging technologies can be catalysts for the development of policies that promote more sustainable agricultural practices, such as providing subsidies for the acquisition of advanced machinery and training in cutting-edge technologies [90]. In addition, technology integration in agriculture improves traceability and transparency, enabling consumers to make more informed decisions and support environmentally friendly farming practices [91].

5. Conclusions

This research highlights the crucial role of digital tools in agricultural development in Latin America, underlining that the adoption of technological innovations is key to increasing productivity in the sector and fostering sustainable environmental management. This technological transformation represents a significant change for agricultural communities in the region, allowing them to advance economically while protecting their ecosystems. In addition, it highlights the importance of reducing the digital divide as an essential factor for economic progress, as it improves the sustainability and competitiveness of agriculture on a global scale. Equal access to technology and information leads to more efficient, productive, and environmentally friendly agricultural practices. The integration of digital technology in the agricultural sector not only opens up new markets and business opportunities but also strengthens the position of nations in the global economy. In short, bridging the digital divide is a fundamental step towards a more advanced, environmentally sustainable, and internationally competitive agriculture.
The conclusion of this literature review, structured in three methodological phases, reveals a rigorous and comprehensive approach to researching the topic. The first phase achieved a comprehensive data collection through recognized databases, initially selecting 40 relevant articles from the period 2018 to 2023. The second phase focused on the critical evaluation of these articles and refined the selection to eight papers based on their relevance, quality, and pertinence. The final phase, dedicated to detailed analysis and interpretation, enabled meaningful conclusions to be drawn, ensuring a thorough and comprehensive understanding of the topic. This meticulous methodological process guarantees the reliability and relevance of the review findings, providing a solid basis for future research in the subject area.

Author Contributions

Conceptualization, P.V.M.-Z. and L.P.T.P.; methodology, R.E.U.V. and Á.P.F.O.; formal analysis, L.P.T.P.; research, P.V.M.-Z., L.P.T.P., R.E.U.V. and Á.P.F.O.; writing—preparation of the original draft, P.V.M.-Z.; writing—revising and editing, R.E.U.V., L.P.T.P. and Á.P.F.O.; supervision, P.V.M.-Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

To the Escuela Superior Politécnica de Chimborazo, Sede Morona Santiago, Macas, Ecuador.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 16100 g001
Figure 1. Categories addressed to analyze the use of ICTs and agricultural digitization from an environmental perspective during the period from 2018 to 2023.
Figure 1. Categories addressed to analyze the use of ICTs and agricultural digitization from an environmental perspective during the period from 2018 to 2023.
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Figure 2. Articles considering the use of ICTs and digital tools in agricultural transformation from an environmental perspective during the period from 2018 to 2023.
Figure 2. Articles considering the use of ICTs and digital tools in agricultural transformation from an environmental perspective during the period from 2018 to 2023.
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Figure 3. Articles addressing monitoring by ICTs and digital tools for natural resource management and identification of environmental issues during the period from 2018 to 2023.
Figure 3. Articles addressing monitoring by ICTs and digital tools for natural resource management and identification of environmental issues during the period from 2018 to 2023.
Sustainability 15 16100 g003
Table 1. Digital tools employed in agricultural production systems during the period from 2018 to 2023.
Table 1. Digital tools employed in agricultural production systems during the period from 2018 to 2023.
TitleYearAuthorsDatabase
Artificial cognition for applications in smart agriculture: A comprehensive review.2020[26]Scopus
Systematic literature review of implementations of precision agriculture.2020[27]Scopus
Machine learning in agriculture: A comprehensive updated review2021[28]Google Scholar
Knowledge management for innovation in agri-food systems: a conceptual framework2023[29]Scopus
Development of precision agriculture and ICT application thereof to manage spatial variability of crop growth2020[30]Scopus
Precision Agriculture and Wireless Sensor Networks: Analysis of Implementation and Advantages in Ecuador2021[31]Latindex
A comprehensive review on the application of Internet of Thing (IoT) in smart agriculture.2022[32]Scopus
Use and adaptations of machine learning in big data—Applications in real cases in agriculture.2021[33]Scopus
Drone implementation in precision agriculture–a survey.2022[34]Scopus
Table 2. Digital tools used for water management during the period from 2018 to 2023.
Table 2. Digital tools used for water management during the period from 2018 to 2023.
TitleYearAuthorsDatabase
Stakeholder Engagement around Water Governance: 30 Years of Decision-Making in the Bogotá River Basin.2023[35]Scopus
Smart water resource management using Artificial Intelligence—A review.2022[36]Scopus
Machine Learning as a Tool for Determining Water Resources Variation.2021[37]Google Scholar
Iot-based intelligent irrigation system for paddy crop using an internet-controlled water pump.2021[38]Scopus
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions.2019[39]Scopus
Smart IoT and machine learning-based framework for water quality assessment and device component monitoring.2022[40]Scopus
Hybrid decision tree-based machine learning models for short-term water quality prediction.2020[41]Scopus
Estimation of daily potato crop evapotranspiration using three different machine learning algorithms and four scenarios of available meteorological data.2020[42]Scopus
Table 3. Digital tools used for soil management during the period from 2018 to 2023.
Table 3. Digital tools used for soil management during the period from 2018 to 2023.
TitleYearAuthorsDatabase
Study of Artificial Intelligence Techniques Applied for Soil Analysis in the Agricultural Sector2021[43]Latindex
Potential of Artificial Intelligence to Advance Desertification Studies2021[44]Scopus
Automation and digitization of agriculture using artificial intelligence and internet of things2021[45]Scopus
Soil moisture simulation using hybrid artificial intelligent model: Hybridization of adaptive neuro fuzzy inference system with grey wolf optimizer algorithm2019[46]Scopus
Comparative analysis of artificial intelligence techniques for the prediction of infiltration process.2021[47]Scopus
Integration of artificial intelligence with meta classifiers for the gully erosion susceptibility assessment in Hinglo river basin, Eastern India2021[48]Scopus
Using machine learning algorithms to estimate soil organic carbon variability with environmental variables and soil nutrient indicators in an alluvial soil.2020[49]Scopus
Artificial neural network and multi-criteria decision-making methods for the remediation of soil oil pollution in the southwest of Iran2023[50]Scopus
Table 4. Digital tools used for agricultural crop fertilization during the period from 2018 to 2023.
Table 4. Digital tools used for agricultural crop fertilization during the period from 2018 to 2023.
TitleYearAuthorsDatabase
Development of the Fertiun App as a Mobile Tool for Optimal Management of Fertilizer Use in Regions Dedicated to Isabela Grape Cultivation in Valle del Cauca.2021[51]Latindex
Incorporating artificial intelligence technology in smart greenhouses2022[52]Scopus
Machine learning approach to recommend suitable crops and fertilizers for agriculture. Recommender System with Machine Learning and Artificial Intelligence:2020[53]Scopus
Prediction of crop yield and fertilizer recommendation using machine learning algorithms.2019[54]Scopus
Intelligent insecticide and fertilizer recommendation system based on TPF-CNN for smart farming2023[55]Scopus
Site-specific machine learning predictive fertilization models for potato crops in Eastern Canada.2020[56]Scopus
Predicting maize yield at the plot scale of different fertilizer systems by multi-source data and machine learning methods2021[57]Scopus
Hydroponics monitoring through UV-VIS spectroscopy and artificial intelligence: Quantification of nitrogen, phosphorous and potassium2021[58]Scopus
Table 5. Digital tools used for agrochemical application during the period from 2018 to 2023.
Table 5. Digital tools used for agrochemical application during the period from 2018 to 2023.
TitleYearAuthorsDatabase
Agricultural intensification and damages to human health in relation to agrochemicals: Application of artificial intelligence2019[59]Scopus
Development and evaluation of a low-cost and smart technology for precision weed management utilizing artificial intelligence2019[60]Scopus
Development of deep learning-based variable rate agrochemical spraying system for targeted weeds control in strawberry crop.2021[61]Scopus
Field evaluation of a deep learning-based smart variable-rate sprayer for targeted application of agrochemicals2023[62]Scopus
Image processing based real-time variable-rate chemical spraying system for disease control in paddy crop2020[63]Scopus
Proposed Spray System for Family Agriculture with A Remote-Controlled UAV (Small Drone or Helicopter) and An Economical Sprinkle2020[64]Scopus
Efficacy of drone technology in agriculture: A review: Drone technology in agriculture2020[65]Scopus
Preliminary study on pesticide application in paddy field using drone spraye2021[66]Scopus
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Méndez-Zambrano, P.V.; Tierra Pérez, L.P.; Ureta Valdez, R.E.; Flores Orozco, Á.P. Technological Innovations for Agricultural Production from an Environmental Perspective: A Review. Sustainability 2023, 15, 16100. https://doi.org/10.3390/su152216100

AMA Style

Méndez-Zambrano PV, Tierra Pérez LP, Ureta Valdez RE, Flores Orozco ÁP. Technological Innovations for Agricultural Production from an Environmental Perspective: A Review. Sustainability. 2023; 15(22):16100. https://doi.org/10.3390/su152216100

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Méndez-Zambrano, Patricio Vladimir, Luis Patricio Tierra Pérez, Rogelio Estalin Ureta Valdez, and Ángel Patricio Flores Orozco. 2023. "Technological Innovations for Agricultural Production from an Environmental Perspective: A Review" Sustainability 15, no. 22: 16100. https://doi.org/10.3390/su152216100

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