Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.

Food and nutrition are a steadfast essential to all living organisms. With specific reference to humans, the sufficient and efficient supply of food is a challenge as the world population continues to grow. Artificial Intelligence (AI) could be identified as a plausible technology in this 5th industrial revolution in bringing us closer to achieving zero hunger by 2030—Goal 2 of the United Nations Sustainable Development Goals (UNSDG). This goal cannot be achieved unless the digital divide among developed and underdeveloped countries is addressed. Nevertheless, developing and underdeveloped regions fall behind in economic resources; however, they harbor untapped potential to effectively address the impending demands posed by the soaring world population. Therefore, this study explores the in-depth potential of AI in the agriculture sector for developing and under-developed countries. Similarly, it aims to emphasize the proven efficiency and spin-off applications of AI in the advancement of agriculture. Currently, AI is being utilized in various spheres of agriculture, including but not limited to crop surveillance, irrigation management, disease identification, fertilization practices, task automation, image manipulation, data processing, yield forecasting, supply chain optimization, implementation of decision support system (DSS), weed control, and the enhancement of resource utilization. Whereas AI supports food safety and security by ensuring higher crop yields that are acquired by harnessing the potential of multi-temporal remote sensing (RS) techniques to accurately discern diverse crop phenotypes, monitor land cover dynamics, assess variations in soil organic matter, predict soil moisture levels, conduct plant biomass modeling, and enable comprehensive crop monitoring. The present study identifies various challenges, including financial, infrastructure, experts, data availability, customization, regulatory framework, cultural norms and attitudes, access to market, and interdisciplinary collaboration, in the adoption of AI for developing nations with their subsequent remedies. The identification of challenges and opportunities in the implementation of AI could ignite further research and actions in these regions; thereby supporting sustainable development.

Enhanced crop growth and yield are the recurring concerns in agricultural field, considering the soaring world population and climate change. Abiotic stresses are one of the major limiting factors for constraining crop production, for several economically important horticultural crops, and contribute to almost 70% of yield gap. Salt stress is one of these unsought abiotic stresses that has become a consistent problem in agriculture over the past few years. Salinity further induces ionic, osmotic, and oxidative stress that result in various metabolic perturbations (including the generation of reactive oxygen, carbonyl, and nitrogen species), reduction in water potential (ψ_w), distorted membrane potential, membrane injury, altered rates of photosynthesis, leaf senescence, and reduced nitrogen assimilation, among others); thereby provoking a drastic reduction in crop growth and yield. One of the strategies to mitigate salt stress is the use of natural plant extracts (PEs) instead of chemical fertilizers, thus limiting water, soil, and environmental pollution. PEs mainly consist of seeds, roots, shoots, fruits, flowers, and leaves concentrates employed either individually or in mixtures. Since PEs are usually rich in bioactive compounds (e.g., carotenoids, flavonoids, phenolics, etc.), therefore they are effective in regulating redox metabolism, thereby promoting plant growth and yield. However, various factors like plant growth stage, doses applied, application method, soil, and environmental conditions may greatly influence their impact on plants. PEs have been reported to enhance salt tolerance in plants primarily through modulation of signaling signatures and pathways (e.g., Na⁺, ANNA4, GIPC, SOS3, and SCaBP8 Ca²⁺ sensors, etc.), and regulation of redox machinery [e.g., superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), non-specific peroxidase (POX), glutathione peroxidase (GPX), peroxiredoxin (Prx), ascorbic acid (AsA), glutathione (GSH), α-tocopherol, etc.]. The current study highlights the role of PEs in terms of their sources, methods of preparation, and mode of action with subsequent physiological changes induced in plants against salinity. However, an explicit mode of action of PEs remains nebulous, which might be explicated utilizing transcriptomics, proteomics, metabolomics, and bioinformatics approaches. Being ecological and economical, PEs might pave the way for ensuring the food security in this challenging era of climate change.

The application of plant beneficial microorganisms is widely accepted as an efficient alternative to chemical fertilizers and pesticides. It was shown that annually, mycorrhizal fungi and nitrogen-fixing bacteria are responsible for 5 to 80% of all nitrogen, and up to 75% of P plant acquisition. However, while bacteria are the most studied soil microorganisms and most frequently reported in the scientific literature, the role of fungi is relatively understudied, although they are the primary organic matter decomposers and govern soil carbon and other elements, including P-cycling. Many fungi can solubilize insoluble phosphates or facilitate P-acquisition by plants and, therefore, form an important part of the commercial microbial products, with Aspergillus, Penicillium and Trichoderma being the most efficient. In this paper, the role of fungi in P-solubilization and plant nutrition will be presented with a special emphasis on their production and application. Although this topic has been repeatedly reviewed, some recent views questioned the efficacy of the microbial P-solubilizers in soil. Here, we will try to summarize the proven facts but also discuss further lines of research that may clarify our doubts in this field or open new perspectives on using the microbial and particularly fungal P-solubilizing potential in accordance with the principles of the sustainability and circular economy.

The current COVID-19 global pandemic has amplified the pressure on the agriculture sector, inciting the need for sustainable agriculture more than ever. Thus, in this review, a sustainable perspective of the use of remotely piloted aircraft (RPA) or drone technology in the agriculture sector is discussed. Similarly, the types of cameras (multispectral, thermal, and visible), sensors, software, and platforms frequently deployed for ensuring precision agriculture for crop monitoring, disease detection, or even yield estimation are briefly discoursed. In this regard, vegetation indices (VIs) embrace an imperative prominence as they provide vital information for crop monitoring and decision-making, thus a summary of most commonly used VIs is also furnished and serves as a guide while planning to collect specific crop data. Furthermore, the establishment of significant applications of RPAs in livestock, forestry, crop monitoring, disease surveillance, irrigation, soil analysis, fertilization, crop harvest, weed management, mechanical pollination, crop insurance and tree plantation are cited in the light of currently available literature in this domain. RPA technology efficiency, cost and limitations are also considered based on the previous studies that may help to devise policies, technology adoption, investment, and research activities in this sphere.