Unlocking Innovation in Crop Resilience and Productivity: Breakthroughs in Biotechnology and Sustainable Farming

 

Naeem Khan1*

 

1Agronomy Department, University of Florida, Gainesville, Florida, USA

 

*Correspondence to: Naeem Khan, PhD, Senior Scientist, Agronomy Department, University of Florida, Gainesville, 32608, Florida, USA; Email: naeemkhan@ufl.edu

 

DOI: 10.53964/id.2024028

 

Abstract

Recent advancements in agricultural biotechnology and sustainable practices are revolutionizing crop production and resilience, addressing global food security challenges. This review highlights cutting-edge innovations in plant sciences, including genetic engineering, genome editing technologies, and biotechnological interventions that enhance crop resistance to biotic and abiotic stresses. It discusses the integration of precision agriculture and digital farming tools that optimize resource use and boost productivity, providing data-driven insights for better crop management. Additionally, sustainable agricultural practices such as agroecology, organic farming, and integrated pest management are examined for their potential to reduce environmental impact while maintaining high yield. The review investigates the key practices like conservation tillage, crop rotation, and biological pest control, emphasizing their roles in enhancing soil health, biodiversity, and agricultural resilience. Significant contributions of biotechnological interventions, including genetic engineering and genome editing, are explored for developing stress-resistant and high-yield crop varieties. Moreover, the integration of precision agriculture and digital farming technologies is discussed for their potential to optimize resource utilization and improve crop management through advanced data analytics.

 

Keywords: genetic engineering, CRISPR-Cas9, precision farming, crop resilience, biotechnology, innovative agriculture

 

1 INTRODUCTION

The escalating global population and rising food demand present unprecedented challenges to the agricultural sector. Traditional farming methods, which have sustained human societies for centuries, are increasingly proving inadequate to meet the needs of a burgeoning population. These conventional practices often struggle to cope with rapidly changing environmental conditions, including climate change, which impacts temperature, precipitation patterns, and the frequency of extreme weather events[1,2]. Additionally, the prevalence of pests and diseases further exacerbates the difficulties faced by farmers, threatening crop yields and food security[3]. In response to these challenges, there is a pressing need for innovative approaches that can enhance crop resilience, improve yield, and promote sustainable agricultural practices. Recent advancements in agricultural biotechnology have emerged as key solutions to address these pressing issues. Genetic engineering and genome editing technologies, in particular, offer transformative potential for modern agriculture by enabling precise and efficient modifications to crop genomes[4-6].

 

Genetic engineering has been pivotal in the development of genetically modified organisms (GMOs), which have revolutionized agriculture by introducing crops with enhanced traits such as increased resistance to pests, diseases, and environmental stress[7]. These GMOs have been widely adopted due to their ability to improve crop performance and stability. For instance, Bacillus thuringiensis (Bt) cotton, which produces a toxin to protect against insect pests, and Roundup Ready crops, which are resistant to glyphosate herbicide, are examples of successful applications of genetic engineering that have had substantial impacts on crop management and yield[8]. More recently, genome editing technologies, such as CRISPR-Cas9, have emerged as powerful tools for precise genetic modifications. Unlike traditional genetic engineering, which often involves the introduction of foreign DNA, genome editing allows for targeted alterations of the existing genome, enabling the precise enhancement of desirable traits[9,10]. This approach has opened new avenues for crop improvement, allowing for the development of varieties with enhanced stress tolerance, disease resistance, and improved nutritional profiles without the potential issues associated with transgenic organisms[11].

 

This review investigates the forefront of genetic engineering and genome editing, examining their cutting-edge applications and advantages in modern agriculture. It explores the intersections of these technologies with biotechnological interventions in agriculture, phytohormonal interactions in plant stress responses, precision agriculture, and digital farming. Furthermore, we analyze how these advancements can support sustainable agricultural practices. By addressing the challenges and future directions of these innovations, this review aims to provide a comprehensive understanding of their role in creating resilient and sustainable food systems.

 

2 GENETIC ENGINEERING AND GENOME EDITING

2.1 CRISPR-Cas9 and Other Genome Editing Technologies

The advent of CRISPR-Cas9 has ushered in a new era in plant biotechnology, offering unprecedented precision and efficiency in genome editing. This revolutionary technology has significantly expanded the possibilities for crop improvement, enabling targeted modifications of specific genes with remarkable accuracy. The versatility of CRISPR-Cas9 has proven instrumental in developing crops with enhanced traits, including increased yield potential, abiotic stress tolerance, and disease resistance[12,13]. The precision afforded by CRISPR-Cas9 allows for nuanced genetic alterations while minimizing unintended off-target effects, a significant advantage over earlier genetic modification techniques[14].

Recent studies have demonstrated the efficacy of CRISPR-Cas9 in addressing critical challenges in agriculture. For instance, Zeng et al.[15] successfully employed CRISPR-Cas9 to enhance drought resistance in wheat by editing the TaDREB2 gene, a key regulator in the plant’s response to water deficit. This research not only showcases the potential of CRISPR-Cas9 in mitigating the impacts of climate change on agriculture but also highlights the technology's capacity to manipulate complex physiological processes with precision. Similarly, Oliva et al.[16] utilized CRISPR-Cas9 to develop rice varieties with increased resistance to bacterial blight by targeting the OsSWEET14 gene, illustrating the technology's utility in enhancing crop resilience to biotic stresses.

 

Additionally, CRISPR-Cas9 has been applied to improve fruit quality and shelf life in crops like tomatoes. For example, Nonaka et al.[17] used CRISPR-Cas9 to edit the SlNAC4 gene, which plays a role in fruit ripening. The resulting tomato lines exhibited delayed ripening and extended shelf life, demonstrating the utility of CRISPR in enhancing post-harvest traits. In maize, Liu et al.[18] targeted the ZmNAC111 gene, resulting in improved tolerance to nitrogen-deficient conditions, which is crucial for sustaining crop productivity under nutrient-limited soils.

 

While CRISPR-Cas9 has dominated the field of genome editing in recent years, alternative technologies such as transcription activator-like effector nucleases (TALENs) and zinc finger nucleases (ZFNs) continue to play important roles in plant biotechnology. These methods, although less widely adopted than CRISPR-Cas9, offer distinct advantages in certain contexts. TALENs, for example, have demonstrated high specificity and low cytotoxicity in some applications[19,20]. Wan et al.[21] successfully employed TALENs to enhance resistance to powdery mildew in grapes by disrupting the VvMLO3 gene, showcasing the continued relevance of this technology in crop improvement. successfully employed TALENs to enhance resistance to powdery mildew in grapes by disrupting the VvMLO3 gene, showcasing the continued relevance of this technology in crop improvement.

 

A critical comparison of these genome editing technologies reveals that while CRISPR-Cas9 offers unparalleled ease of use and versatility, TALENs and ZFNs may provide advantages in terms of specificity and reduced off-target effects in certain scenarios. Zhang et al.[22] conducted a comprehensive analysis of off-target effects across these platforms, finding that TALENs exhibited lower off-target activity compared to CRISPR-Cas9 in some plant species. This underscores the importance of selecting the appropriate genome editing tool based on the specific requirements of each research objective (Figure 1).

 

Figure 1. This Diagram Illustrates the Genetic Engineering and Genome Editing Process. Different nodes represent different steps and techniques involved in the process.

 

Furthermore, the regulatory landscape surrounding genome-edited crops remains complex and varies significantly across jurisdictions. While some countries have adopted more permissive stances towards CRISPR-edited crops, others maintain stricter regulations. This regulatory heterogeneity poses challenges for the global adoption and commercialization of genome-edited crops. Addressing these regulatory disparities and establishing science-based frameworks for the assessment of genome-edited plants is crucial for realizing the full potential of these technologies in addressing global food security challenges. While CRISPR-Cas9 has undoubtedly revolutionized plant biotechnology, a nuanced understanding of the strengths and limitations of various genome editing technologies is essential. The continued development and refinement of these tools, coupled with advancements in our understanding of plant genetics and physiology, promise to accelerate crop improvement efforts. However, realizing the full potential of genome editing in agriculture will require not only technological innovations but also careful consideration of ethical implications, public acceptance, and the development of appropriate regulatory frameworks.

 

2.2 Transgenic Crops

Genetically modified (GM) crops represent a significant achievement in agricultural biotechnology, providing novel solutions to some of the industry's toughest challenges. By incorporating foreign genes into crop plants, scientists have been able to confer traits such as herbicide resistance and improved nutritional content[23,24]. One of the most notable examples is Bt cotton, which expresses a toxin derived from the bacterium Bt. This genetic modification provides effective protection against key insect pests, resulting in substantial reductions in pesticide use and increased yields. The success of Bt cotton highlights how genetic engineering can contribute to more sustainable agricultural practices by reducing the environmental impact of chemical pesticides[25,26]. Similarly, herbicide-resistant soybean, which incorporates the CP4 EPSPS gene from Agrobacterium tumefaciens, offers resistance to glyphosate and supports efficient weed management[27]. Virus-resistant papaya, developed by incorporating the Papaya Ringspot Virus (PRSV) coat protein gene, saved the Hawaiian papaya industry by preventing PRSV outbreaks[28]. Another impactful example is Bt brinjal, engineered with the Cry1Ac protein to target the brinjal fruit and shoot borer, significantly reducing pest damage in South Asia[29].

 

Similarly, Golden Rice, engineered to produce provitamin A (beta-carotene) in the endosperm, addresses vitamin A deficiency in many developing countries[30]. This biofortified crop has the potential to significantly improve the nutritional status of millions of people who rely on rice as a staple food. The development of Golden Rice exemplifies how genetic engineering can be harnessed to tackle public health issues and improve global food security[31].

 

2.3 Case Studies

The application of genome editing and genetic engineering in agriculture has yielded several notable success stories. The development of drought-tolerant maize through the introduction of the cold shock protein B (CspB) gene from Bacillus subtilis is one such example. This transgenic maize variety has shown improved yield under water-limited conditions, demonstrating the potential of genetic engineering to mitigate the impacts of climate change on agriculture[32]. Another significant case study involves the use of CRISPR-Cas9 to develop tomato plants with enhanced resistance to the Tomato Yellow Leaf Curl Virus (TYLCV). By targeting the SlTYLCV-resistant gene, researchers have generated tomato plants with significantly reduced viral symptoms and improved fruit yield, showcasing the practical benefits of CRISPR-Cas9 in addressing crop disease challenges[33,34]. Zhang et al.[35] provides a comprehensive overview of CRISPR applications in developing disease-resistant and stress-tolerant crop varieties. The paper emphasizes the role of CRISPR in enhancing resistance to biotic stresses, such as bacterial and fungal diseases, through targeted gene knockout and regulation strategies. In addition, transgenic sugarcane expressing the DREB2A gene from Arabidopsis thaliana has shown a 20% increase in yield under drought conditions in Brazilian trials, illustrating the crop's improved resilience[38]. Biofortified bananas, engineered to produce higher levels of beta-carotene, also provide a nutritional intervention in regions with high vitamin A deficiency, offering a sustainable solution to malnutrition[36].

 

3 BIOTECHNOLOGICAL INTERVENTIONS

3.1 Marker-Assisted Selection and Genomic Selection

Marker-assisted selection (MAS) and genomic selection (GS) are powerful tools that enhance the efficiency and precision of plant breeding programs. MAS involves identifying and using specific genetic markers linked to desirable traits to accelerate the selection process. This approach has proven effective in improving traits such as disease resistance, yield, and stress tolerance. For instance, MAS has been successfully used to develop wheat varieties resistant to rust diseases by incorporating resistance genes identified through molecular markers[37,38]. For example, submergence-tolerant rice varieties have been developed through MAS by incorporating the Sub1A gene, enabling rice to survive under flooded conditions for up to 14 days[39]. This approach not only speeds up the breeding process but also increases the accuracy of selecting plants with desired traits[40]. In maize, GS has been applied to identify drought tolerance-associated genomic regions, resulting in the release of ‘DroughtTEGO,’ a variety that demonstrates stable performance under low-water conditions[41].

 

Genomic selection (GS), on the other hand, utilizes genome-wide markers to predict the genetic value of breeding candidates. This method allows for the selection of superior genotypes at an early stage, significantly reducing the breeding cycle time and increasing genetic gains. Recent advancements in high-throughput genotyping and computational tools have facilitated the implementation of GS across various crops. A notable example is the application of GS in maize, where it has accelerated the development of hybrids with enhanced yield and drought tolerance. This demonstrates how genomic selection can drive rapid improvements in crop performance and resilience[42,33] (Figure 2).

 

Figure 2. The Schematic Shows Various Biotechnological Approaches Viz. Transgenic Plants, Marker-Assisted Selection, Pest Resistance, Disease Resistance and Environmental Stress Resistance. Arrows in dark blue depict the interconnections between these approaches. This visualization highlights the integrated methods used to enhance crop improvement.

 

3.2 Plant-Microbe Interactions in Biotechnological Interventions

Harnessing beneficial plant-microbe interactions presents a promising frontier in biotechnological interventions, offering significant potential to enhance nutrient uptake, stimulate plant growth, and bolster resistance to biotic and abiotic stresses. Symbiotic relationships with microbes such as arbuscular mycorrhizal fungi (AMF) and rhizobia are particularly noteworthy. For example, the inoculation of AMF has been shown to enhance phosphorus uptake in crops such as maize and wheat, leading to improved growth and yield under nutrient-limited conditions. This finding highlights the potential of AMF in improving soil fertility and crop productivity through natural symbiosis[44]. Similarly, the use of rhizobia to enhance nitrogen fixation in legumes has been a cornerstone of sustainable agriculture, reducing the need for chemical fertilizers and improving soil health. This practice underscores the importance of integrating microbial solutions into crop management strategies for sustainable agricultural practices[45].

 

These microorganisms facilitate essential nutrient exchange, with AMF aiding in phosphorus uptake and rhizobia enhancing nitrogen fixation, thereby reducing the need for chemical fertilizers, and improving soil health[46,47]. Recent advancements in molecular biology and genomics have deepened our understanding of these intricate interactions. Studies have elucidated the signaling pathways and genetic mechanisms that underpin symbiosis, revealing how plants and microbes communicate and coordinate their metabolic processes. For instance, research has identified key genes involved in the formation and maintenance of mycorrhizal associations, as well as those regulating nodule formation in leguminous plants[48]. Biotechnological applications are now leveraging this knowledge to develop innovative strategies aimed at improving crop productivity. For example, bioinoculants containing beneficial microbes are being engineered to enhance their efficacy and stability under field conditions. Additionally, genetic modification of crops to improve their compatibility with symbiotic microbes is being explored, with the goal of optimizing nutrient acquisition and stress resilience[49-51]. Furthermore, these biotechnological interventions have implications for sustainable agriculture. By promoting plant-microbe symbiosis, it is possible to reduce dependence on synthetic fertilizers and pesticides, mitigate environmental impacts, and enhance soil fertility. This approach aligns with the principles of agroecology, aiming to create resilient agricultural systems that are both productive and environmentally sustainable[52,53].

 

The exploitation of beneficial plant-microbe interactions through biotechnological interventions holds considerable promise for advancing agricultural productivity and sustainability. Continued research into the molecular mechanisms governing these interactions, coupled with innovative biotechnological applications, will be pivotal in addressing the challenges of modern agriculture and ensuring food security in a changing climate.

 

3.3 Biotechnology in Disease and Pest Management

Biotechnological interventions have significantly transformed disease and pest management strategies in agriculture, offering innovative solutions to longstanding challenges. The development and widespread adoption of transgenic crops expressing insecticidal proteins derived from Bacillus thuringiensis (Bt) represent a paradigm shift in pest control methodologies. Bt crops, particularly Bt cotton and Bt maize, have demonstrated remarkable efficacy in mitigating crop losses attributed to insect pests, while simultaneously reducing the agricultural sector's dependence on conventional chemical insecticides[54-56]. The success of Bt crops is multifaceted, encompassing both economic and environmental benefits. By expressing specific insecticidal proteins, these genetically modified crops provide targeted pest control, significantly reducing the need for broad-spectrum insecticides. This reduction in chemical inputs not only mitigates environmental contamination but also contributes to the preservation of beneficial insects and natural enemies, thereby promoting ecological balance within agroecosystems. Furthermore, the decreased exposure to pesticides has positive implications for farmer health and safety, addressing a critical concern in agricultural communities worldwide[57].

 

However, the widespread adoption of Bt crops has not been without challenges. The emergence of resistance in target pest populations poses a significant threat to the long-term viability of this technology. Recent studies have documented cases of field-evolved resistance to Bt toxins in several major pest species, including Helicoverpa zea in the United States and Pectinophora gossypiella in India[58,59]. These findings underscore the critical need for proactive resistance management strategies and the continued development of novel insecticidal proteins to maintain the efficacy of transgenic crop technologies.

 

In parallel with transgenic approaches, RNA interference (RNAi) technology has emerged as a promising frontier in pest and disease management. RNAi operates by selectively silencing genes crucial for pest survival or pathogen virulence, offering a highly specific and potentially environmentally benign method of crop protection. The application of RNAi in agriculture extends beyond insect control to encompass fungal pathogens, nematodes, and viruses, demonstrating its versatility as a crop protection tool[60,61]. Recent advancements in RNAi technology have led to the development of exogenously applied dsRNA sprays, exemplified by their successful application against the Colorado potato beetle[62]. This approach represents a significant leap forward in the integration of RNAi into integrated pest management (IPM) frameworks, offering a non-transgenic alternative that aligns with consumer preferences for non-GMO products while maintaining a high degree of pest control efficacy.

 

Despite its promise, the widespread implementation of RNAi-based pest control faces several hurdles. These include challenges in dsRNA delivery, potential off-target effects, and the development of resistance mechanisms in target organisms. Moreover, the regulatory landscape for RNAi-based crop protection products remains complex and evolving, necessitating careful consideration of biosafety and environmental impact assessments[63,64].

 

The integration of these biotechnological approaches into comprehensive IPM strategies presents both opportunities and challenges. While Bt crops and RNAi technologies offer powerful tools for pest management, their efficacy and sustainability depend on judicious implementation within broader ecological contexts. Recent research emphasizes the importance of diversified pest management strategies that combine biotechnological interventions with cultural practices, biological control, and selective use of chemical pesticides to achieve durable and environmentally sustainable crop protection[65,66]. As the field of agricultural biotechnology continues to evolve, emerging technologies such as CRISPR-Cas9 gene editing hold promise for further innovations in pest and disease management. These advanced genetic tools offer unprecedented precision in modifying crop genomes to enhance resistance against pests and pathogens, potentially circumventing some of the regulatory challenges associated with transgenic approaches.

 

4 PHYTOHORMONAL INTERACTIONS IN PLANT STRESS RESPONSES

Phytohormones are pivotal in orchestrating plant responses to environmental stresses by regulating intricate signaling networks. These small molecules, including abscisic acid, auxins, cytokinins, gibberellins, ethylene, jasmonic acid, and salicylic acid, individually and interactively modulate plant growth, development, and stress resilience. An in-depth understanding of phytohormonal interactions is crucial for advancing our grasp of plant stress physiology and for developing effective strategies to enhance crop resilience and productivity.

 

4.1 Crosstalk Between Phytohormones

Phytohormonal signaling is characterized by extensive crosstalk, which integrates multiple environmental signals to elicit appropriate responses. This crosstalk involves complex interactions among signaling pathways, allowing plants to adapt to fluctuating environmental conditions. For instance, ABA, a central regulator of drought stress, does not act in isolation. It interacts with ethylene and gibberellins to modulate critical processes such as growth inhibition and stomatal closure. This interaction helps balance water loss and gas exchange, optimizing the plant's water-use efficiency and enhancing survival under drought conditions[67]. Understanding these crosstalk mechanisms is essential for designing interventions that can fine-tune plant responses to specific stresses (Figure 3).

 

Figure 3. This Figure Illustrates the Complex Interactions Between Various Phytohormones and Their Roles in Plant Stress Responses. The nodes represent different phytohormones and stress factors, while the edges indicate the nature of their interactions.

 

4.2 Synergistic and Antagonistic Interactions

Phytohormonal interactions can be classified as either synergistic or antagonistic. Synergistic interactions occur when hormones work in concert to amplify a stress response. For example, the combined action of jasmonic acid and ethylene is crucial for mounting a robust defense response against necrotrophic pathogens, which cause tissue necrosis and can significantly reduce crop yield[68]. Conversely, antagonistic interactions involve one hormone inhibiting the action of another, creating a balance between different stress responses. A well-documented example is the antagonism between ABA and salicylic acid, where ABA's promotion of stomatal closure and stress responses can counteract the immune-enhancing effects of salicylic acid, which is critical for plant defense against biotic stresses[69]. This balance is crucial for optimizing plant responses to diverse stress factors and avoiding detrimental over-reactions.

 

4.3 Regulation of Hormonal Homeostasis

Maintaining hormonal homeostasis is vital for optimal stress responses and overall plant health. Phytohormone levels are regulated through complex processes including biosynthesis, degradation, and conjugation. For instance, ABA and gibberellins are dynamically regulated during seed germination and dormancy. ABA promotes seed dormancy and stress tolerance, whereas gibberellins facilitate seed germination and growth. Disruptions in this hormonal balance can lead to impaired stress responses and reduced plant fitness [70]. Research into the regulatory mechanisms that control hormonal homeostasis can provide insights into how plants maintain balance under stress and identify targets for genetic or chemical intervention to enhance stress resilience.

 

4.4 Hormonal Regulation of Gene Expression

Phytohormones influence the expression of a wide array of stress-responsive genes through interactions with transcription factors. For example, ABRE-binding factors (ABFs) in the ABA signaling pathway play a crucial role in regulating genes involved in drought tolerance. These transcription factors modulate gene expression patterns to enhance the plant’s ability to cope with water scarcity[71]. Similarly, ethylene-responsive factors (ERFs) are key players in the transcriptional reprogramming that occurs during both biotic and abiotic stress responses. ERFs regulate the expression of genes involved in pathogen defense and stress adaptation, highlighting the integrative nature of phytohormonal regulation[72]. This complex regulatory network underscores the importance of understanding how hormonal signals are translated into specific gene expression profiles that drive stress responses.

 

4.5 Implications for Crop Improvement

A comprehensive understanding of phytohormonal interactions offers significant potential for crop improvement. By manipulating hormonal pathways, it is possible to enhance stress tolerance, improve yield stability, and optimize resource use under adverse conditions. Advances in genetic engineering and genome editing technologies, such as CRISPR-Cas9, enable targeted modifications of key genes involved in hormonal biosynthesis and signaling. This approach has the potential to create crops that are better equipped to withstand environmental stresses and improve agricultural productivity[73]. However, translating these advances into practical applications requires careful consideration of the potential ecological and agronomic impacts of genetically modified crops.

 

Future research should focus on elucidating the detailed mechanisms of phytohormonal interactions and their impact on plant stress physiology. Advanced omics technologies, including transcriptomics, proteomics, and metabolomics, coupled with systems biology approaches, can provide comprehensive insights into the dynamic hormonal networks that regulate plant responses to stress. Additionally, interdisciplinary collaboration and innovative methodologies will be essential to bridge the gap between fundamental research and practical applications in sustainable agriculture. Exploring how phytohormonal signaling pathways can be integrated into crop breeding and management strategies will be crucial for developing resilient crops that can thrive in the face of changing environmental conditions.

 

5 PRECISION AGRICULTURE AND DIGITAL FARMING

5.1 Remote Sensing and GIS Technologies

Precision agriculture utilizes cutting-edge technologies such as remote sensing and Geographic Information Systems (GIS) to revolutionize crop management practices. Remote sensing employs satellites, drones, and other aerial platforms to gather extensive data on crop health, soil conditions, and environmental factors[74-76]. This data is analyzed to optimize key agricultural practices including irrigation, fertilization, and pest management, significantly enhancing efficiency and productivity. Sabir et al.[77] focuses on the impact of precision agriculture on sustainable crop production, linking the use of remote sensing and GIS technologies with improved environmental outcomes.

 

Multispectral and hyperspectral imaging technologies are at the forefront of remote sensing. Drones equipped with these imaging systems can identify early signs of nutrient deficiencies, diseases, or water stress in crops. By detecting these issues at an early stage, farmers can implement timely and targeted interventions, which not only improves crop health but also prevents potential yield losses[78,79]. For instance, in vineyards in Spain, multispectral imaging has been used to monitor grape ripeness, enabling precise harvest timing that enhances wine quality and yield. Similarly, in wheat fields in the United States, hyperspectral imaging has identified nitrogen deficiencies early in the season, allowing targeted fertilization to optimize grain protein content

 

GIS technologies further enhance precision agriculture by offering spatial analysis and mapping capabilities. GIS integrates data from various sources, creating detailed maps that reveal spatial variability within fields. This spatial information helps farmers make informed decisions on site-specific management practices, such as variable rate fertilization and targeted irrigation, thereby optimizing resource use and improving crop performance[80,81]. The integration of remote sensing and GIS facilitates a holistic approach to field management, aligning agricultural practices with spatial and temporal variations (Figure 4).

 

Figure 4. Infographic Illustrating Various Tools and Technologies Used in Precision Agriculture. Including drones for aerial data collection, sensors for soil and crop monitoring, GPS-guided equipment for accurate planting and harvesting, data analytics for optimizing decision-making, automated irrigation for precise water application, and precision fertilization for optimal nutrient application. The connections between these technologies highlight their integrated roles in optimizing resource use and improving crop management.

 

5.2 Internet of Things (IoT) and Smart Farming

The IoT is a transformative force in agriculture, connecting an array of sensors, devices, and equipment to collect and exchange real-time data. IoT-enabled devices monitor critical environmental parameters such as soil moisture, temperature, and humidity, providing farmers with actionable insights that drive data-driven decision-making[82]. Smart irrigation systems exemplify the benefits of IoT in agriculture. For example, in Israel, IoT-based smart irrigation systems in almond orchards have reduced water use by 40% while increasing nut yield by 20%[83]. In China, autonomous rice-planting robots equipped with IoT sensors have achieved precision planting, improving crop establishment by 25% compared to manual methods[84].  Fuentes-Peñailillo et al.[85] explores how AI and big data are being used to optimize irrigation, soil health monitoring, and precision spraying techniques. This targeted approach not only conserves water but also promotes healthier crop growth and maximizes yield.

 

Automated machinery, equipped with IoT sensors, further enhances operational efficiency. Tasks such as planting, weeding, and harvesting can be performed with high precision, minimizing labor costs and reducing human error. For example, autonomous tractors equipped with GPS and sensor technology can execute planting patterns that optimize seed placement and spacing, thereby improving crop establishment and yield[86]. The integration of IoT in smart farming supports sustainable practices by improving resource efficiency and reducing the environmental footprint of agricultural operations (Figure 5).

 

Figure 5. PCA Biplot of Digital Forming Techniques. PCA biplot and hierarchical clustering dendrogram illustrating the relationships and clustering among digital farming techniques (Farm Management Software, IoT Devices, and Precision Agriculture) based on yield, growth rate, and water usage. The biplot shows variance explained by principal components, and the dendrogram highlights the hierarchical clustering patterns.

 

5.3 Big Data and AI in Agriculture

The integration of big data analytics and artificial intelligence (AI) is driving the next frontier of precision agriculture, enabling predictive and prescriptive farming strategies. By analyzing vast datasets from diverse sources, including remote sensing, IoT devices, and historical records, AI algorithms can forecast crop yields, anticipate disease outbreaks, and predict pest infestations, leading to proactive and informed management decisions[87]. Machine learning models have been developed to predict crop yields based on historical data, current weather patterns, and satellite imagery. These models assist farmers in planning their activities more effectively, optimizing resource use, and maximizing yield potential[88,89]. For example, predictive analytics can help in determining the best planting dates and estimating the impact of climate variability on crop production.

 

AI-powered decision support systems offer tailored recommendations for various aspects of farm management. In California, machine learning models have been used to determine optimal irrigation schedules for almond orchards, reducing water use by 35% and improving nut quality. These systems can advise on the selection of crop varieties that are best suited to specific environmental conditions, optimal planting times, and effective pest control strategies. Such precision in decision-making enhances overall farm productivity and resilience to environmental challenges[90]. However, it is crucial to address challenges related to data privacy, the need for robust data integration, and the potential biases in AI algorithms to fully realize the benefits of big data and AI in agriculture.

 

6 SUSTAINABLE AGRICULTURE PRACTICES

6.1 Conservation Tillage and Soil Health

Conservation tillage, including no-till and reduced-till practices, represents a fundamental approach to sustainable agriculture by minimizing soil disturbance. This method helps to reduce soil erosion, enhance water retention, and build soil organic matter, contributing to improved soil health. Unlike conventional tillage, which disrupts the soil structure and depletes organic matter, conservation tillage preserves the natural soil ecosystem, fostering higher microbial activity and biodiversity. This is crucial for maintaining soil fertility and promoting long-term productivity.

 

Research highlights the benefits of conservation tillage: for instance, no-till farming has been shown to significantly increase soil organic carbon and nitrogen levels compared to traditional tillage methods. This results in more stable soil structure and improved water infiltration, which are vital for sustaining agricultural productivity under varying climatic conditions[91]. However, it is important to note that the effectiveness of conservation tillage can be influenced by factors such as soil type, climate, and crop system, necessitating tailored approaches for different agricultural contexts (Table 1).

 

Table 1. Impact of Sustainable Agricultural Practices on Soil Health, Biodiversity, and Crop Yield

 

6.2 Crop Rotation and Diversification

Crop rotation and diversification represent cornerstone practices in sustainable agriculture, offering a multitude of benefits that extend beyond mere pest and disease management to encompass soil health enhancement, ecosystem services provision, and agricultural resilience. These practices involve the strategic sequencing of different crop species across growing seasons and the integration of diverse plant types within agricultural landscapes, respectively. The implementation of these methods is grounded in agroecological principles that aim to optimize resource utilization, minimize environmental impacts, and sustain long-term productivity.

 

The efficacy of crop rotation in disrupting pest and disease cycles is well-documented, with recent meta-analyses providing robust evidence of its impact on yield stability and pest pressure reduction. A comprehensive study by Weisberger et al.[92] analyzed data from 2,800 comparisons and found that crop rotation increased yields by an average of 4.3% across diverse cropping systems globally. This yield enhancement is attributed to multiple factors, including improved soil structure, enhanced nutrient cycling, and reduced pathogen loads. The study also highlighted the particular benefits of incorporating legumes into rotations, which contributed to yield increases of up to 13% in subsequent cereal crops. The role of crop diversification in promoting soil fertility and ecosystem services has gained increased attention in recent years. Research by Tamburini et al.[93] demonstrated that diversified cropping systems can significantly enhance soil organic carbon sequestration, with potential implications for climate change mitigation. Their meta-analysis, encompassing 98 studies, revealed that diversified systems increased soil organic carbon by an average of 3.6% compared to simplified rotations. This improvement in soil carbon content has cascading effects on soil structure, water retention capacity, and microbial diversity, all of which contribute to enhanced agricultural resilience.

 

Furthermore, the integration of leguminous crops in rotations has been shown to have profound impacts on nitrogen cycling and soil fertility. A recent study by Jensen et al.[94] quantified the nitrogen fixation rates of various legume species in diverse agroecosystems, demonstrating that well-managed legume rotations can contribute up to 200kg∙N∙ha-1∙yr-1 to subsequent crops. This biological nitrogen fixation not only reduces the reliance on synthetic fertilizers but also mitigates the environmental impacts associated with nitrogen leaching and greenhouse gas emissions from agricultural soils. The benefits of crop rotation and diversification extend beyond soil health to encompass broader ecosystem services. Research by Dainese et al.[95] highlighted the positive impacts of crop diversity on pollinator abundance and diversity, with potential implications for crop yield stability and resilience to environmental stressors. Their global synthesis of 89 studies demonstrated that increasing crop diversity at both the field and landscape scales can enhance pollination services by up to 50%, underscoring the importance of considering spatial scales in agricultural diversification strategies.

 

Despite the well-documented benefits, the implementation of crop rotation and diversification faces significant challenges in modern agricultural systems. Market pressures, infrastructure limitations, and the need for specialized knowledge and equipment can act as barriers to adoption. A comprehensive review by Bowles et al.[96] identified key socio-economic and policy factors influencing farmers' decisions to diversify their cropping systems. The study emphasized the need for integrated policy approaches that combine financial incentives, technical support, and market development to facilitate the transition to more diverse and resilient agricultural systems (Figure 6).

 

Figure 6. The Figure Illustrates Sustainable Agricultural Practices with Three Panels. Crop rotation, showing a triangular cycle of corn, beans, and wheat; integrated pest management, represented by a pie chart divided into biological, cultural, mechanical, and chemical controls; and organic farming practices, highlighting composting, green manures, biological pest control, and crop rotation.

 

Recent advances in precision agriculture and remote sensing technologies offer new opportunities for optimizing crop rotation and diversification strategies. Research by Schut et al.[97] demonstrated the potential of machine learning algorithms and satellite imagery to inform spatially explicit crop rotation planning, considering soil variability, climate projections, and market dynamics. These technological innovations, coupled with participatory research approaches that integrate farmer knowledge, hold promise for developing context-specific diversification strategies that balance productivity, profitability, and environmental sustainability. In conclusion, crop rotation and diversification represent powerful tools for enhancing agricultural sustainability and resilience. The growing body of scientific evidence underscores their multifaceted benefits, from soil health improvement to ecosystem service provision. However, realizing the full potential of these practices requires a systems approach that addresses the complex interplay of agronomic, economic, and social factors influencing agricultural decision-making. Future research should focus on developing integrated strategies that leverage technological innovations, policy instruments, and farmer engagement to promote the widespread adoption of diversified cropping systems across diverse agricultural landscapes.

 

6.3 IPM

Integrated Pest Management (IPM) offers a comprehensive approach to pest control that combines biological, cultural, mechanical, and chemical methods to minimize environmental impact and economic costs. By utilizing natural predators, biocontrol agents, and habitat management practices, IPM reduces the reliance on chemical pesticides and promotes ecological balance. In practical terms, IPM strategies have demonstrated substantial success in various crops. For instance, the adoption of IPM in cotton production has led to notable reductions in pesticide use while maintaining high yields and profitability. This approach not only protects beneficial organisms and reduces chemical residues but also enhances the resilience of farming systems against pest outbreaks[98,99]. However, the effectiveness of IPM depends on the accurate identification of pest species, thorough monitoring, and timely intervention, which can be resource-intensive and require farmer training.

 

6.4 Organic Farming

Organic farming is characterized by the exclusion of synthetic chemicals, focusing instead on natural inputs and practices that promote ecological balance and biodiversity. Organic systems employ techniques such as composting, green manures, and biological pest control to enhance soil fertility and manage pests[100]. By fostering a diverse soil ecosystem, organic farming contributes to improved soil health and reduced environmental impact compared to conventional farming practices. Studies reveal that organic farming not only enhances soil fertility and biodiversity but also contributes to reduced environmental pollution and greater resilience to climatic stresses[26]. Organic systems can often adapt better to extreme weather conditions due to improved soil structure and moisture retention. However, organic farming faces challenges such as lower yields and higher labor costs, which necessitate continued research and development to optimize practices and enhance economic viability[101].

 

7 CHALLENGES AND FUTURE DIRECTIONS

7.1 Climate Change and Resource Scarcity

Climate change presents profound challenges to sustainable agriculture through its effects on temperature, precipitation patterns, and the frequency of extreme weather events. Increased temperatures can lead to heat stress in crops, reducing yields and altering growth cycles. Changes in precipitation can exacerbate water scarcity and affect soil moisture levels, which are critical for crop health and productivity. Additionally, more frequent extreme weather events such as floods and droughts can disrupt planting and harvesting schedules, further impacting food security[102]. To address these challenges, developing climate-resilient crop varieties and adaptive farming practices is essential. Breeding programs focused on drought tolerance, heat resistance, and improved water-use efficiency are crucial for maintaining agricultural productivity under changing climatic conditions. However, the development and deployment of such crops require significant investment in research and development, as well as the establishment of robust regulatory frameworks to ensure their safety and effectiveness.

 

Resource scarcity, particularly in terms of water and arable land, compounds these challenges. Efficient water management techniques, such as drip irrigation and rainwater harvesting, are critical for sustaining agricultural productivity. Yet, the implementation of these technologies often depends on infrastructure availability and economic viability, which can be barriers in resource-limited settings. Sustainable land management practices, including agroforestry and conservation agriculture, offer strategies to maximize resource use while preserving ecosystem services. However, these practices must be adapted to local conditions and integrated with broader land use planning to achieve long-term sustainability[103,104].

 

7.2 Socioeconomic and Policy Barriers

Socioeconomic factors significantly influence the adoption of sustainable agriculture practices. Access to markets, credit, and technology are critical for smallholder farmers, who constitute a substantial portion of agricultural producers in developing countries. These farmers often face challenges in accessing the resources and knowledge necessary for implementing sustainable practices. Effective policies are needed to support education, extension services, and infrastructure development to facilitate this transition[105].

 

Additionally, global trade policies and market dynamics play a crucial role in shaping agricultural practices. Incentives for sustainable farming, such as subsidies for organic inputs and price premiums for sustainably produced crops, can motivate farmers to adopt environmentally friendly methods. Nevertheless, aligning these incentives with global trade regulations poses a complex challenge. For instance, disparities in environmental standards between countries can create trade barriers or lead to unintended consequences, such as market distortions or increased environmental degradation in regions with less stringent regulations[106,107].

 

7.3 Technological Advancements and Innovations

Technological advancements are pivotal in addressing the challenges faced by sustainable agriculture. Precision agriculture technologies, such as remote sensing, IoT, and AI, offer the potential to optimize resource use, enhance crop management, and minimize environmental impacts. For example, precision irrigation systems that utilize real-time data to regulate water application can substantially improve water use efficiency and crop yields. However, the adoption of these technologies requires significant investment and infrastructure, which can be a barrier for smallholder and resource-limited farmers[108].

 

Biotechnological innovations, including CRISPR-based genome editing, present promising solutions for developing crops with enhanced stress tolerance, nutrient use efficiency, and pest resistance. These technologies can expedite the breeding process and contribute to the development of resilient crop varieties. However, the deployment of biotechnological solutions must be accompanied by careful consideration of ethical, regulatory, and societal implications. Public acceptance and regulatory approval are critical for the widespread adoption of these technologies, necessitating transparent communication and engagement with stakeholders to address concerns and ensure equitable access[109,110].

 

The limitations of precision agriculture and digital farming technologies, such as remote sensing, GIS, IoT, AI, and gene editing, present significant challenges that hinder widespread adoption and impact their effectiveness. High initial costs for advanced equipment like drones, IoT sensors, and autonomous machinery can be prohibitive, particularly for small-scale farmers. Additionally, issues related to data privacy, connectivity in rural areas, and the need for robust infrastructure pose barriers to implementation. Furthermore, the adoption of these technologies requires specialized technical expertise, which is often lacking in rural communities. Gene editing, while promising, faces ethical and ecological concerns, along with strict regulatory hurdles that slow down innovation. Moreover, environmental conditions such as cloud cover can disrupt data accuracy in remote sensing, while the complexity of managing and integrating vast amounts of data can overwhelm users. Addressing these limitations through targeted policies, capacity-building programs, and improved infrastructure is crucial to unlocking the full potential of these technologies for sustainable agriculture.

 

8 CONCLUSION

Sustainable agriculture is paramount for addressing the growing global demands for food while mitigating environmental impacts and ensuring long-term agricultural productivity. This review highlights the pivotal role of advanced agricultural practices, including conservation tillage, crop rotation, integrated pest management, and organic farming, in fostering sustainable farming systems. These practices not only enhance soil health and biodiversity but also contribute to the resilience of agricultural systems against climatic and resource challenges. Biotechnological interventions, such as genetic engineering and genome editing, offer promising avenues for developing stress-tolerant and high-yielding crop varieties. Precision agriculture and digital farming technologies further augment these efforts by optimizing resource use and improving crop management through data-driven insights. However, the successful implementation of these technologies requires overcoming socioeconomic barriers, ensuring equitable access to resources, and addressing ethical and regulatory concerns. Despite significant progress, several challenges persist, including the impacts of climate change, resource scarcity, and the need for supportive policies and market incentives. Interdisciplinary collaboration and innovative methodologies are essential to address these challenges and advance sustainable agriculture. Future research should focus on exploring additional layers of hormonal regulation, enhancing predictive capabilities for crop resilience, and integrating technological advancements into practical farming applications. By consolidating these efforts, we can move towards a more sustainable and resilient agricultural system that ensures food security and environmental sustainability for future generations.

 

Acknowledgements

Not applicable.

 

Conflicts of Interest

The author declared no conflicts of interest.

 

Data Availability

No additional data are available.

 

Copyright Permissions

Copyright © 2024 The Author(s). Published by Innovation Forever Publishing Group Limited. This open-access article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, sharing, adaptation, distribution, and reproduction in any medium, provided the original work is properly cited.

 

Author Contribution

Khan N was responsible for all the work on the article.

 

Abbreviation List

ABA, Abscisic acid

AMF, Arbuscular mycorrhizal fungi

AI, Artificial intelligence

Bt, Bacillus thuringiensis

ERFs, Ethylene-responsive factors

GM, Genetically modified

GS, Genomic selection

GIS, Geographic information systems

IPM, Integrated pest management

IoT, Internet of things

MAS, Marker-assisted selection

PRSV, Papaya ringspot virus

RNAi, RNA interference

TYLCV, Tomato yellow leaf curl virus

TALENs, Transcription activator-like effector nucleases

ZFNs, Zinc finger nucleases

 

References

[1] Rhodes CJ. Soil erosion, climate change and global food security: challenges and strategies. Sci Prog, 2014; 97: 97-153.[DOI]

[2] Muhie SH. Novel approaches and practices to sustainable agriculture. J Agr Food Res, 2022; 10: 100446.[DOI]

[3] Pretty J, Pervez Bharucha Z. Integrated pest management for sustainable intensification of agriculture in Asia and Africa. Insects, 2015; 6: 152-182.[DOI]

[4] Zhang K, Raboanatahiry N, Zhu B et al. Progress in genome editing technology and its application in plants. Front Plant Sci, 2017; 8: 177.[DOI]

[5] Lebedev VG, Popova AA, Shestibratov KA. Genetic engineering and genome editing for improving nitrogen use efficiency in plants. Cells, 2021; 10: 3303.[DOI]

[6] Hartung F, Schiemann J. Precise plant breeding using new genome editing techniques: opportunities, safety and regulation in the EU. Plant J, 2014; 78: 742-752.[DOI]

[7] Agapito-Tenfen SZ, Okoli AS, Bernstein MJ et al. Revisiting risk governance of GM plants: the need to consider new and emerging gene-editing techniques. Front Plant Sci, 2018; 9: 1874.[DOI]

[8] Huang S, Weigel D, Beachy RN et al. A proposed regulatory framework for genome-edited crops. Nat Genet, 2016; 48: 109-111.[DOI]

[9] Samanta MK, Dey A, Gayen S. CRISPR/Cas9: an advanced tool for editing plant genomes. Transgenic Res, 2016; 25: 561-573.[DOI]

[10] Razzaq A, Saleem F, Kanwal M et al. Modern trends in plant genome editing: an inclusive review of the CRISPR/Cas9 toolbox. Int J Mol Sci, 2019; 20: 4045.[DOI]

[11] Gao C. The future of CRISPR technologies in agriculture. Nat Rev Mol Cell Bio, 2018; 19: 275-276.[DOI]

[12] Gohil S, Kumari A, Prakash A et al. CRISPER-Based Industrial Crop Improvements. In Industrial Crop Plants. Singap: Springer Nat Singap, 2024: 123-162.[DOI]

[13] Kapil J, Fartyal M, Mathur N. CRISPR/Cas9: an evolutionary approach towards crops amelioration, 2023; 12: 44-61.[DOI]

[14] Misra V, Mall AK, Pandey H et al. Advancements and prospects of CRISPR/Cas9 technologies for abiotic and biotic stresses in sugar beet. Front Genet, 2023; 14: 1235855.[DOI]

[15] Zeng Y, Wen J, Zhao W et al. Rational improvement of rice yield and cold tolerance by editing the three genes OsPIN5b, GS3, and OsMYB30 with the CRISPR-Cas9 system. Front Plant Sci, 2020; 10: 1663.[DOI]

[16] Oliva R, Ji C, Atienza-Grande G et al. Broad-spectrum resistance to bacterial blight in rice using genome editing. Nat Biotechnol, 2019; 37: 1344-1350.[DOI]

[17] Nonaka S, Ito M, Ezura H. Targeted modification of CmACO1 by CRISPR/Cas9 extends the shelf-life of Cucumis melo var. reticulatus melon. Front Genome Edit, 2023; 5: 1176125.[DOI]

[18] Liu S, Liu X, Zhang X et al. Co-expression of ZmVPP1 with ZmNAC111 confers robust drought resistance in maize. Genes, 2022; 14: 8.[DOI]

[19] Patel J, Mishra A. Genome editing: Advances and prospects. Plant biotechnology: progress in genomic era, 2019; 29: 147-174.[DOI]

[20] Schütte G, Eckerstorfer M, Rastelli V et al. Herbicide resistance and biodiversity: agronomic and environmental aspects of genetically modified herbicide-resistant plants. Environ Sci Eur, 2017; 29: 1-12.[DOI]

[21] Wan DY, Guo Y, Cheng Y et al. CRISPR/Cas9-mediated mutagenesis of VvMLO3 results in enhanced resistance to powdery mildew in grapevine (Vitis vinifera). Hortic Res, 2020; 7: 116.[DOI]

[22] Zhang Y, Ge X, Yang F et al. Comparison of non-canonical PAMs for CRISPR/Cas9-mediated DNA cleavage in human cells. Sci Rep, 2014; 4: 1-5.[DOI]

[23] Sedeek KE, Mahas A, Mahfouz M. Plant genome engineering for targeted improvement of crop traits. Front Plant Sci, 2019; 10: 114.[DOI]

[24] Tokel D, Genc BN, Ozyigit II. Economic impacts of Bt (Bacillus thuringiensis) cotton. J Nat Fibers, 2022; 19: 4622-4639.[DOI]

[25] Wang W, Pan Q, He F et al. Transgenerational CRISPR-Cas9 activity facilitates multiplex gene editing in allopolyploid wheat. Crispr J, 2018; 1: 65-74.[DOI]

[26] Paine JA, Shipton CA, Chaggar S et al. Improving the nutritional value of Golden Rice through increased pro-vitamin A content. Nat Biotechnol, 2005; 23: 482-487.[DOI]

[27] Amna, Qamar S, Tantray AY et al. Golden Rice: Genetic Engineering, Promises, Present Status and Future Prospects. In: Roychoudhury A. (eds) Rice Research for Quality Improvement: Genomics and Genetic Engineering. Springer, Singapore. 2020: 581-604.[DOI]

[28] Otegui ME, Riglos M, Mercau JL. Genetically modified maize hybrids and delayed sowing reduced drought effects across a rainfall gradient in temperate Argentina. J Exp Bot, 2021; 72: 5180-5188.[DOI]

[29] Yang Y, Sherwood TA, Patte CP et al. Use of Tomato yellow leaf curl virus (TYLCV) Rep gene sequences to engineer TYLCV resistance in tomato. Phytopathology, 2004; 94: 490-496.[DOI]

[30] El-Sappah AH, Qi S, A Soaud S et al. Natural resistance of tomato plants to Tomato yellow leaf curl virus. Front Plant Sci, 2022; 13: 1081549.[DOI]

[31] Hasan N, Choudhary S, Naaz N et al. Recent advancements in molecular marker-assisted selection and applications in plant breeding programmes. J Genet Eng Biotechnol, 2021; 19: 128.[DOI]

[32] He J, Zhao X, Laroche A et al. Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding. Front Plant Sci, 2014; 5: 484.[DOI]

[33] Ben-Ari G, Lavi U. Marker-assisted selection in plant breeding. In: Altmana A, Hasegawa PM.(eds) Plant Biotechnology and Agriculture (Prospects for the 21st Century). Academic Press, Elsevier. 2012: 163-184.[DOI]

[34] Crossa J, Pérez-Rodríguez P, Cuevas J et al. Genomic selection in plant breeding: methods, models, and perspectives. Trends Plant Sci, 2017; 22: 961-975.[DOI]

[35] Zhang D, Zhang Z, Unver T et al. CRISPR/Cas: A powerful tool for gene function study and crop improvement. J Adv Res, 2021; 29: 207-221.[DOI]

[36] Nadeem MA, Nawaz MA, Shahid MQ et al. DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnol Biotec Eq, 2018; 32: 261-285.[DOI]

[37] Ikram M, Ali N, Jan G et al. Isolation of endophytic fungi from halophytic plants and their identification and screening for auxin production and other plant growth promoting traits. J Plant Growth Regul, 2023; 42: 4707-4723.[DOI]

[38] Naseem H, Ahsan M, Shahid MA et al. Exopolysaccharides producing rhizobacteria and their role in plant growth and drought tolerance. J Basic Microb, 2018; 58: 1009-1022.[DOI]

[39] Sharma B, Singh BN, Dwivedi P et al. Interference of climate change on plant-microbe interaction: Present and future prospects. Front Agron, 2022; 3: 725804.[DOI]

[40] Abhilash PC, Powell JR, Singh HB et al. Plant - microbe interactions: novel applications for exploitation in multipurpose remediation technologies. Trends Biotechnol, 2012; 30: 416-420.[DOI]

[41] Khan N, Bano A. Modulation of phytoremediation and plant growth by the treatment with PGPR, Ag nanoparticle and untreated municipal wastewater. Int J Phytoremediat, 2016; 18: 1258-1269.[DOI]

[42] Kumar P, Srivastava DK. Introduction: Insight to biotechnological advances in the study of beneficial plant-microbe interaction with special reference to agrobacterium tumefaciens. In: Plant Microbe Symbiosis. Springer Publishing: Berlin, 2020; 287-302.

[43] Adeleke RA, Nunthkumar B, Roopnarain A et al. Introduction: Applications of plant - microbe interactions in agro-ecosystems. In: Microbiome in Plant Health and Disease. Springer Publishing: Berlin, 2019; 1-34.

[44] Khan N, Bano A, Rahman MA et al. Comparative physiological and metabolic analysis reveals a complex mechanism involved in drought tolerance in chickpea (Cicer arietinum L.) induced by PGPR and PGRs. Sci Rep, 2019; 9: 2097.[DOI]

[45] Parray JA, Mir MY, Shameem N. Sustainable Agriculture: Biotechniques in Plant Biology. Springer Publishing: Berlin, Germany, 2019.

[46] Lyson TA. Advanced agricultural biotechnologies and sustainable agriculture. Trends Biotechnol, 2002; 20: 193-196.[DOI]

[47] Koch MS, Ward JM, Levine SL et al. The food and environmental safety of Bt crops. Front Plant Sci, 2015; 6: 283.[DOI]

[48] Pohare MB, Wagh SG, Udayasuriyan V. Introduction: Bacillus thuringiensis as potential biocontrol agent for sustainable agriculture. In: Current trends in microbial biotechnology for sustainable agriculture. Springer Publishing: Berlin, 2021; 439-468.

[49] Adomako J, Yeboah S, Larbi-Koranteng S et al. Introduction: Transgenic plants and its role in insect control. In: New and Future Development in Biopesticide Research: Biotechnological Exploration. Springer Publishing: Berlin, 2022; 203-222.

[50] Romeis J, Naranjo SE, Meissle M et al. Genetically engineered crops help support conservation biological control. Biol Control, 2019; 130: 136-154.[DOI]

[51] Luttrell RG, Jackson RE. Helicoverpa zea and Bt cotton in the United States. Gm Crops Food, 2012; 3: 213-227.[DOI]

[52] Dhurua S, Gujar GT. Field‐evolved resistance to Bt toxin Cry1Ac in the pink bollworm, Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae), from India. Pest Manag Sci, 2011; 67: 898-903.[DOI]

[53] Li X, Liu X, Lu W et al. Application progress of plant-mediated RNAi in pest control. Front Bioeng Biotech, 2022; 10: 963026.[DOI]

[54] Halder K, Chaudhuri A, Abdin MZ et al. RNA interference for improving disease resistance in plants and its relevance in this clustered regularly interspaced short palindromic repeats-dominated era in terms of dsrna-based biopesticides. Front Plant Sci, 2022; 13: 885128.[DOI]

[55] Das PR, Sherif SM. Application of exogenous dsRNAs-induced RNAi in agriculture: challenges and triumphs. Front Plant Sci, 2020; 11: 946.[DOI]

[56] Nitnavare RB, Bhattacharya J, Singh S et al. Next generation dsRNA-based insect control: Success so far and challenges. Front Plant Sci, 2021; 12: 673576.[DOI]

[57] Christiaens O, Whyard S, Vélez AM et al. Double-stranded RNA technology to control insect pests: current status and challenges. Front Plant Sci, 2020; 11: 451.[DOI]

[58] Yan S, Ren B, Zeng B et al. Improving RNAi efficiency for pest control in crop species. BioTechniques, 2020; 68: 283-290.[DOI]

[59] Saeed F, Hashmi MH, Hossain MJ et al. Introduction: Transgenic technologies for efficient insect pest management in crop plants. In: Transgenic technology based value addition in plant biotechnology. Academic Press: Cambridge, 2020; 123-156.

[60] Trewavas A. Plant Behaviour and Intelligence. Oxford University Press: London, UK, 2017.

[61] Zhu JK. Abiotic Stress Signaling and Responses in Plants. Cell, 2016; 167: 313-324.[DOI]

[62] Pieterse CMJ, Van der Does D, Zamioudis C et al. Hormonal Modulation of Plant Immunity. Annu Rev Cell Dev Bi, 2012; 28: 489-521.[DOI]

[63] Finkelstein R. Abscisic Acid synthesis and response. Arabidopsis Book, 2013; 11: e0166.[DOI]

[64] Yoshida T, Mogami J. ABA-dependent and ABA-independent signaling in response to osmotic stress in plants. Curr Opin Plant Biol, 2014; 21: 133-139.[DOI]

[65] Licausi F, Ohme-Takagi M, Perata P. APETALA2/Ethylene Responsive Factor (AP2/ERF) transcription factors: mediators of stress responses and developmental programs New Phytol, 2013; 199: 639-649.[DOI]

[66] Wang F, Zhu D, Huang X et al. Genetic Engineering and Genome Editing for Crop Improvement in China. Front Plant Sci, 2020; 11: 114.

[67] Kingra PK, Majumder D, Singh SP. Application of remote sensing and GIS in agriculture and natural resource management under changing climatic conditions. Agr Res J, 2016; 53: 295-302.[DOI]

[68] AbdelRahman MA, Hegab RH, Yossif TM. Soil fertility assessment for optimal agricultural use using remote sensing and GIS technologies. Appl Geomat, 2021; 13: 605-618.[DOI]

[69] Mani JK, Varghese AO. Introduction: Remote sensing and GIS in agriculture and forest resource monitoring. In: Geospatial technologies in land resources mapping, monitoring and management. Springer International Publishing: Berlin, 2018; 377-400.

[70] Lu B, Dao PD, Liu J et al. Recent advances of hyperspectral imaging technology and applications in agriculture. Remote Sens, 2020; 12: 2659.[DOI]

[71] Ortega S, Fabelo H, Iakovidis DK et al. Use of hyperspectral/multispectral imaging in gastroenterology. Shedding some-different-light into the dark. J Clin Med, 2019; 8: 36.[DOI]

[72] Erunova MG, Yakubailik OE. GIS technologies for agricultural monitoring in the regional agriculture system of the Krasnoyarsk territory. Int Multidiscip Sci GeoConf: SGEM, 2019; 19: 863-869.[DOI]

[73] Ghosh P, Kumpatla SP. Chapter 5: GIS applications in agriculture. In: Zhang Y, Cheng Q, Geographic Information Systems and Applications in Coastal Studies. IntechOpen Publishing: London, 2022.

[74] Doshi J, Patel T, kumar Bharti S. Smart Farming using IoT, a solution for optimally monitoring farming conditions. Procedia Comput Sci, 2019; 160: 746-751.[DOI]

[75] Dagar R, Som S, Khatri SK. Smart farming-IoT in agriculture: Proceedings of the 2018 International Conference on Inventive Research in Computing Applications (ICIRCA). Coimbatore, India, 11-12 July 2018.[DOI]

[76] Dhanaraju M, Chenniappan P, Ramalingam K et al. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture, 2022; 12: 1745.[DOI]

[77] Sabir RM, Mehmood K, Sarwar A et al. Chapter 5: Remote Sensing and Precision Agriculture: A Sustainable Future. In: Transforming Agricultural Management for a Sustainable Future: Climate Change and Machine Learning Perspectives. Springer Nature: Switzerland, 2024; 75-103.

[78] Dhanaraju M, Chenniappan P, Ramalingam K et al. Smart farming: Internet of Things (IoT)-based sustainable agriculture. Agriculture, 2022; 12: 1745.[DOI]

[79] Misra NN, Dixit Y, Al-Mallahi A et al. IoT, big data, and artificial intelligence in agriculture and food industry. IEEE Internet Things J, 2020; 9: 6305-6324.[DOI]

[80] Joshi A, Kaushik V. Introduction: Big Data and Its Analytics in Agriculture. In: Bioinformatics for agriculture: High-throughput approaches. Springer Publishing: Berlin, 2021; 71-83.

[81] Kumar P, Singh A, Rajput VD et al. Introduction: Role of artificial intelligence, sensor technology, big data in agriculture: next-generation farming. In: Bioinformatics in agriculture. Academic Press: Cambridge, 2022; 625-639.

[82] Nath S. A vision of precision agriculture: Balance between agricultural sustainability and environmental stewardship. Agron J, 2024; 116: 1126-1143.[DOI]

[83] Adhikari P, Araya H, Aruna G et al. System of crop intensification for more productive, resource-conserving, climate-resilient, and sustainable agriculture: Experience with diverse crops in varying agroecologies. Int J Agr Sustain, 2018; 16: 1-28.[DOI]

[84] Bista B, Dahal S. Cementing the organic farming by green manures. Int J Appl Sci Biotechnol, 2018; 6: 87-96.[DOI]

[85] Fuentes-Peñailillo F, Gutter K, Vega R et al. Transformative technologies in digital agriculture: Leveraging Internet of Things, remote sensing, and artificial intelligence for smart crop management. J Sens Actuat Netw, 2024; 13: 39.[DOI]

[86] Łuczka W, Kalinowski S. Barriers to the development of organic farming: A polish case study. Agriculture, 2020; 10: 536.[DOI]

[87] Kumar D, Yadav A, Ahmad R et al. CRISPR-based genome editing for nutrient enrichment in crops: a promising approach toward global food security. Front Genet, 2022; 13: 932859.[DOI]

[88] Lisowski O. International Food Regulations and Their Unintended Consequences: Why the EUʼs Farm to Fork Strategy Would Hurt Europeans. Wisc Int Law J, 2022; 39: 206-231.

[89] Stenberg JA. A conceptual framework for integrated pest management. Trends Plant Sci, 2017; 22: 759-769.[DOI]

[90] Shi B, Feng C, Qiu M et al. Innovation suppression and migration effect: The unintentional consequences of environmental regulation. China Econ Rev, 2018; 49: 1-23.[DOI]

[91] Qayyum M, Zhang Y, Wang M et al. Advancements in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils. J Environ Manag, 2023; 347: 119147.[DOI]

[92] Weisberger D, Nichols V, Liebman M. Does diversifying crop rotations suppress weeds? A meta-analysis. PLoS One, 2019; 14: e0219847.[DOI]

[93] Tamburini G, Bommarco R, Wanger TC et al. Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci Adv, 2020; 6: eaba1715.[DOI]

[94] Jensen JL, Beucher AM, Eriksen J. Soil organic C and N stock changes in grass-clover leys: Effect of grassland proportion and organic fertilizer. Geoderma, 2022; 424: 116022.[DOI]

[95] Dainese M, Martin EA, Aizen MA et al. A global synthesis reveals biodiversity-mediated benefits for crop production. Sci Adv, 2019; 5: eaax0121.[DOI]

[96] Bowles TM, Mooshammer M, Socolar Y et al. Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth, 2020; 2: 284-293.[DOI]

[97] Schut MC, Dongelmans DA, De Lange DW et al. Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges. Bmc Med Inform Decis, 2024; 24: 7.[DOI]

[98] Dara SK. The new integrated pest management paradigm for the modern age. J Integr Pest Manag, 2019; 10: 12.[DOI]

[99] Nasrullah, Ali S, Umar M et al. Flooding tolerance in plants: from physiological and molecular perspectives. Braz J Bot, 2022; 45: 1161-1176.[DOI]

[100] Zaman A, Zaman P, Maitra S. Water resource development and management for agricultural sustainability. J Appl Adv Res, 2017; 2: 73-77.[DOI]

[101] Gaddikeri V, Jatav MS, Pasha MM et al. Chapter 8: Role of Water Harvesting and Supplemental Irrigation in Enhancing Agriculture Productivity of Dryland under Climate Change. In: Enhancing Resilience of Dryland Agriculture Under Changing Climate: Interdisciplinary and Convergence Approaches. Springer Nature Singapore: Berlin, 2023; 123-143.[DOI]

[102] Bista B, Dahal S. Cementing the organic farming by green manures. Int J Appl Sci Biotechnol, 2018; 6: 87-96.[DOI]

[103] Ray S, Majumder S. Chapter 10: Water management in agriculture: Innovations for efficient irrigation. In: Sil P, Chhetri P, Majumder S et al. Modern Agronomy. International Books and Periodical Supply Service Publishing: New Delhi, 2024; 169-185.

[104] Mandal S, Vema VK, Kurian C et al. Improving the crop productivity in rainfed areas with water harvesting structures and deficit irrigation strategies. J Hydrol, 2020; 586: 124818.[DOI]

[105] Altieri MA, Ponti L, Nicholls CI. Introduction: Soil fertility, biodiversity and pest management. In: Biodiversity and insect pests: key issues for sustainable management. Morgan & Claypool Publishing: California, 2012; 72-84.

[106] Akenroye TO, Dora M, Kumar M et al. A taxonomy of barriers to the adoption of sustainable practices in the coffee farming process. J Clean Prod, 2021; 312: 127818.[DOI]

[107] Villalobos-López MA, Arroyo-Becerra A, Quintero-Jiménez A et al. Biotechnological advances to improve abiotic stress tolerance in crops. Int J Mol Sci, 2022; 23: 12053.[DOI]

[108] Kovács GP, Simon B, Balla I et al. Conservation tillage improves soil quality and crop yield in Hungary. Agronomy, 2023; 13: 894.[DOI]

[109] Reicosky D. Conservation agriculture systems: Soil health and landscape management. In Advances in Conservation Agriculture. Burleigh Dodds Science Publishing: Sawston, 2020; 87-154.

[110] Kovács GP, Simon B, Balla I et al. Conservation tillage improves soil quality and crop yield in Hungary. Agronomy, 2023; 13: 894.[DOI]

[111] Nadeem F, Nawaz A, Farooq M. Chapter: Crop rotations, fallowing, and associated environmental benefits. In: Oxford Research Encyclopedia of Environmental Science. Oxford University Press: London, 2019.

[112] Sanogo K, Touré I, Arinloye DAA et al. Factors affecting the adoption of climate-smart agriculture technologies in rice farming systems in Mali, West Africa. Smart Agr Technol, 2023; 5: 100283.[DOI]

[113] Boincean B, Dent D, Boincean B et al. Chapter: Crop rotation. In: Farming the Black Earth: Sustainable and Climate-Smart Management of Chernozem Soils. Springer Publishing: Berlin, 2019; 89-124.

[114] Yadav RK, Tripathi MK, Tiwari S et al. Genome editing and improvement of abiotic stress tolerance in crop plants. Life, 2023; 13: 1456.[DOI]

[115] Kumar D, Yadav A, Ahmad R et al. CRISPR-based genome editing for nutrient enrichment in crops: a promising approach toward global food security. Front Genet, 2022; 13: 932859.[DOI]

[116] Liu C, Plaza-Bonilla D, Coulter JA et al. Diversifying crop rotations enhances agroecosystem services and resilience. Adv Agron, 2022; 173: 299-335.[DOI]

[117] Karuppuchamy P, Venugopal S. Integrated pest management. In Ecofriendly pest management for food security. Academic Press: London, 2016; 651-684.

[118] Pretty J, Pervez Bharucha Z. Integrated pest management for sustainable intensification of agriculture in Asia and Africa. Insects, 2015; 6: 152-182.[DOI]

[119] Jasrotia P, Kumari P, Malik K et al. Conservation agriculture based crop management practices impact diversity and population dynamics of the insect-pests and their natural enemies in agroecosystems. Front Sustain Food S, 2023; 7: 1173048.[DOI]

[120] Singh VK, Malhi GS, Kaur M et al. Chapter: Use of organic soil amendments for improving soil ecosystem health and crop productivity. In: Ecosystem Services. Nova Science Publishing: Hauppauge, 2022; 259-278.

[121] Gamage A, Gangahagedara R, Gamage J et al. Role of organic farming for achieving sustainability in agriculture. Farming Syst, 2023; 1: 100005.[DOI]

[122] Shennan C, Krupnik TJ, Baird G et al. Organic and conventional agriculture: a useful framing? Annu Rev Environ Resour, 2017; 42: 317-346.[DOI]

 

Brief of Corresponding Author(s)

Naeem Khan He is a dedicated crop physiologist and agronomist in Plant Sciences, driven by a passion for understanding and improving plant resilience against environmental challenges. Currently, he serve as a senior scientist in the Agronomy Department at the University of Florida. His scientific interests encompass plant metabolites, plant-microbe interactions, phytohormones, breeding, and genetics, with a particular focus on how crops respond to abiotic stresses, especially drought. He has over 110 publications and with an h index of 40.