Smart-farming practices can help to overcome the impacts of soil and crop variability on crop yield. This article studies the impact of fertilization treatment on the production of a major oilseed crop, mustard (Brassica campestris L.), in an arid region of Pakistan. Soil-nutrient sampling was performed, using 20 × 20 m grids to characterize and quantify the variation of mustard yield and soil nutrients. Based on the results of a significant correlation between yield and soil nutrients, management zones (MZs) were developed that use Variable Rate Fertilization (VRF) to increase crop production and profitability while reducing environmental risk. Full article

Climate change poses a significant challenge to food security. Several traditional approaches are available to prevent food insecurity in climate change scenarios, such as modifications in crop practices, altering field management systems, and climate-smart farming measures. Recently, precision agriculture practices are becoming a more popular way of farming that might help to overcome climate risk and reduce food insecurity. Precision agriculture is a tool for monitoring the food supply chain and managing both the amount and quality of agricultural products. Thus, this work seeks to synthesize and discuss the research related to the importance of a precision agriculture system in preventing food insecurity in the context of a developing countries such as Pakistan. The study is based on the narrative literature review. Full article

Smart farming and precision agriculture rely on the different components of IoT, such as sensors, drones, and robotic devices. IoT in agriculture is the network of interconnected devices that corresponds in real time, simultaneously, to gather, analyze, and transfer the data, which, ultimately, generate a decision to be taken by the farmer. The availability of the 4G/3G does not support the precision practices in real time due to the bandwidth, connectivity, and the speed of data-transfer issues. Further, 5G technology in the agricultural sector has put its greater influence in real-time monitoring, unmanned aerial vehicles, virtual consultation and predictive maintenance, artificially intelligent robotics, and data analytics and cloud repositories. Conclusively, the speed, connectivity, scalability and processing power, and limitations can be overcome with the availability of 5G structures. Full article

The depletion of usable agricultural lands has brought up a scenario of vertical farming. This type of farming is mostly considered soil-less farming in the vertical direction. Three of the commonly used soil-less ways for vertical farming include hydroponic, aeroponic, and aquaponic. Although it is not very popular in developing countries, investment has been made by many European counties and efforts to use vertical farming as a commercial product are on the path to success. Food security issues can be addressed through this farming type as well. Full article

Long-term changes in climate variability, vulnerability, a rise in average temperature, and changes in precipitation patterns threaten crop productivity, food security, and the livelihoods of people across the globe. Lower crop yields with higher dependence on food imports, global economic shocks, and climate change exacerbate more challenges to food security, specifically in developing countries. Therefore, adaptation to climate change is necessary to promote farmers’ sustainable livelihoods and mitigate carbon emissions. The adoption of Climate-Smart Agriculture (CSA) practices can potentially help reduce greenhouse gas (GHG) emissions without compromising agricultural production. To confront the challenges regarding the adoption of CSA practices, this study reviews the relevant literature and suggests policy recommendations on how socioeconomic determinants and considerations affect sustainable agriculture development systems. It focuses on the optimization problem of a farmer as a social planner, in which a farmer seeks to maximize his welfare objectives now and in the future. Farmers’ choices of CSA adoption, as well as their adaptive capacity and adaptation constraints, are discussed. This study has implications for policymakers in terms of raising the frequency of adopters through innovations and policy design. Full article

The digital revolution is transforming agriculture by applying artificial intelligence (AI) techniques. Potato (Solanum tuberosum L.) is one of the most important food crops which is susceptible to different varieties of weeds which not only lower its yield but also affect crop quality. Artificial Intelligence and Computer Vision (CV) techniques have been proven to be state-of-the-art in terms of addressing various agricultural problems. In this study, a dataset of five different potato weeds was collected in different environments and under different climatic conditions such as sunny, cloudy, partly cloudy, and at different times of the day on a weekly basis. For weeds-detection purposes, the Tiny-YOLOv4 model was trained on the collected potato weeds dataset. The proposed model obtained 49.4% mAP value by calculating the IoU. The model trained with high prediction accuracy will later be used as part of a site-specific spraying system to apply agrochemicals for weed management in potato crops. Full article

Proper and uniform seed depth within the optimum range increases crop germination rate, which directly affects yield. Seed depth mainly depends on seed placement techniques. In conventional seed drill and planters, variations and fluctuations in seeding depth were recorded. This issue can be resolved by adaption of intelligent crop sowing machinery. A real-time seed depth control system was designed and developed to monitor and maintain the required seed depth. The developed system was installed on a tractor-mounted conventional seed drill. The materials used were ultrasonic sensors, a micro-controller, an RTC module, buzzers, an LCD, an SD card module, a power battery, and switch buttons. The system read height difference as a reference value. The seeding depth data was stored in the SD card. The results showed by introducing real time depth control system in existing seeders, it is possible to achieve desired plant population and homogeneous germination. The average cumulative germination rate (GR) of wheat with the seed depth control system was 126 plants/m², and with a conventional seed drill (without SDCS) 117 plants/m². The yield of wheat with the seed depth control system was 1225 kg/acre, and with the conventional seed drill (without SDCS) 1124 kg/acre in an arid region. Result shows that the crop yield could be enhanced by proper seed placement at the required seed depth by using the seed depth control system. Further field trials on different soils, regions and environmental conditions could improve the results. Full article

Water is a key component in the two biggest economic drivers of Taiwan, i.e., the semiconductor and agricultural industries. Agricultural water accounts for 70% of the total water usage of the nation. During drought situations, the allocation and utilization of agricultural water usage become an important issue where farmers pump groundwater to supply the irrigation deficit from surface water, which ultimately impacts regional groundwater levels. Thus, there is a need to find a way to address its field water consumption during droughts; one way is a smart irrigation water management system. In this study, a smart irrigation water management model coupled with a system dynamic model (VENSIM) was developed for mixed crops in Central Taiwan by reducing 50% of the planned irrigation. Results can be applied as a solution to water shortage during droughts with alternate frequent adjustment of water gates to ensure water supply to tail end users. Full article

Water is imperative for life and plays a vital role in sustaining multiple environmental services. Currently, water resources are under stress, and rainwater harvesting (RWH) is one of the solutions available to address water shortages. In this study, the potential of RWH for irrigation and recreational activities in a public park (i.e., Fatima Jinnah Park-Islamabad) is discussed. The soil conservation service-curve number (SCS-CN) method was used to estimate the runoff. Results revealed that annually 1.80 million cubic meters (MCM) runoff is generated at this park. If this runoff volume is accommodated and managed effectively, it can fulfill the requirements of irrigation and other water-related activities. Hence, the adoption of RWH technology is vital for managing water; therefore, this approach should be used to support any policy changes that lead to widespread use of RWH. Full article

Solar convective drying is a method of dehydrating food that is gaining popularity in developing regions due to its low power consumption and shorter yield times compared to direct sun drying. Exposure of food items to high temperatures towards the end of drying results in color and shape deterioration, negatively affecting the product’s market value. To alleviate this problem, we explored the impact of dehydrating potato slices using Convective Drying with reducing temperatures over the drying process. It was found that reducing the temperature in two steps during the drying process preserved 61% of the original color at the cost of a 23.8% increase in drying time, compared to constant temperature drying at 60 °C. Full article

The diagnosis and recommendation integrated system (DRIS) approach assesses plants’ nutrient status by comparing crop nutrient ratios with optimum values from a high-yielding group (DRIS norms). Furthermore, in this study, twenty-one grids were selected using GPS for soil sampling from a 1-hectare olive orchard field with a grid size of 20 × 20 m. Using standard laboratory procedures, soil samples were analyzed for macronutrients (N, P, and K ranging from 0.06–0.17%, 1.44–5.56%, and 31.94–120.32 mg kg⁻¹) and micronutrients (Fe, Cu, Mn, Zn and B ranging from 25.16–82.3, 1.09–1.8, 26.96–65.69, 0.01–4.5 and 0.48–1.06 mg kg⁻¹), respectively, and in plant samples for macronutrients (N, P and K ranging from 0.63–1.93, 0.01–0.16 and 0.75–1.37%) and micronutrients (Fe, Cu, Zn, Mn and B ranging from 152.5–621.5, 8.5–17, 18–34 and 43.5–113 mg kg⁻¹), respectively. The critical ranges were investigated in terms of their relationship to the population’s yield level. DRIS norms derived from olives were able to detect nutrient deficiency and excess. Full article

The precise monitoring of nitrogen (N) is an effective strategy for enhancing the crop yield per unit of land, but it involves field-level soil and crop data. The two years of experimental study were conducted during the cotton growing seasons of 2018 and 2019 at the Agriculture Research Farm of the Department of Agricultural Engineering, Bahauddin Zakariya University, Multan. The Nitrogen Fertilizer Optimization Algorithm (NFOA) was formulated based on the observed data for cotton lint yield (CLY) and GreenSeeker Normalized Difference Vegetation Index (GSNDVI) during the growing stages of cotton. The precision nitrogen application rate-based green seeker (PNAR) G.S for cotton was identified as 150-165 kg/ha. A linear relationship was observed between CLY (R2 = 0.80) for cotton with the GSNDVI. The average nitrogen requirement (N_req) using (PNAR) G.S was determined through the nitrogen fertilizer optimization algorithm (NFOA). The N_req was found to be 0.013 kg/kg for cotton. Precision N management originating from handheld crop sensors (GreenSeeker) may be helpful in decision-making for site-specific in-season N fertilizer management to enhance crop yield. Full article

This research presents the new techniques and practical experiences of using unmanned aerial vehicles (UAVs) precision agriculture mapping. UAV-based remote sensing systems should be cost-effective, fast-producing, have high geometric accuracy, and be simple to operate by local staff. This work aims to: (1) precisely use high-resolution UAV thermal multi-spectral sensors and machine learning approaches to reliably assess crop water status on a field scale; (2) capture on-field images for quantitative study from the multi-spectral sensors; (3) establish workflows for digital agriculture applications; (4) interpret the intelligent irrigation decision model using UAV indices, maps, and multi-source heterogeneous data integration. This research gives us new methods to set an intelligent method for precision agriculture, which greatly improves the level of agricultural intelligence. Full article

Oat is an essential Rabi crop commonly used as green fodder. The nutritional requirements of oats are higher than those of other Rabi fodder crops. Higher doses of inorganic fertilizers are required to meet this demand, which is not economical for fodder production. This study evaluates the best economical dose of integrated nutrient management for attaining higher yield and better nutritional quality of oat. The experiment was conducted on the Agronomy Research Farm, University of Agriculture, Faisalabad, Punjab, Pakistan. The seed varieties used in this experiment were Oat-2011 Sargodha and Oat-F-411 (2021) Faisalabad. The experimental treatments were organized in factorial Randomized Complete Block Design (RCBD) arrangements, with each treatment replicated three times. The results revealed that treatment (T4) 50% RDF + 5 t/ha. Farmyard Manure + seed inoculation azotobacter was found to be the most appropriate than all other treatments. Full article

The agriculture sector in Pakistan has a significant amount of potential in terms of solar, wind, geothermal, and biomass energy production and consumption. Most of the farm machinery on agriculture farms runs on high-cost fossil fuels and is also our source of greenhouse gas emissions (GHG). Utilizing renewable energy (RE) technology in the agriculture sector will reduce the cost of agricultural farming and will lower GHG emissions. The objective of this study is to determine and compare the solar and wind energy potential for the different districts in the Potohar region of Pakistan. The solar and wind energy data are obtained from HOMER Pro, RETScreen, and the weather station of the National Center of Industrial Biotechnology (NCIB), PMAS-Arid Agriculture University Rawalpindi. The results obtained are analyzed and compared which depicts that the Potohar region of Punjab, Pakistan has a significant amount of solar potential for its application in agriculture. This article gives an overview of renewable solar and wind energy potential and its applications for farmers and ranchers to make RE a rising source of energy and rural income in Pakistan. Full article

Precision agriculture (PA) is a cutting-edge, comprehensive, and globally recognized method. PA entails the application of agronomic ideas and modern technologies to improve sustainability, agricultural output, and environmental quality. This article is mostly concerned with sensing techniques. Remote sensing is a useful technique in PA for spotting, predicting, and predetermining the levels of infestations, and for controlling pests and diseases on a variety of fruits and crops. Sensors also transform traditional farming methods into precision farming methods, which helps to cut back on unnecessary input costs and raises agricultural productivity. By using these techniques, the application of pesticides can be quickly and locally administered. Full article

Nanotechnology is an interdisciplinary study field that attempts to boost agricultural output through substantial nanotechnology. This study has been conducted because of the reckless use of pesticides and synthetic fertilizers brought on by the green revolution, which has diminished soil biodiversity and increased disease and insect resistance. Only nanoparticles or nano chips can produce sophisticated biosensors for precision farming and deliver ingredients to plants in a nanoparticle-mediated manner. The precise distribution of nutrients and agrochemicals to plants is made possible by nano-encapsulated versions of conventional fertilizers, insecticides, and herbicides. Nanotechnology-based tests for detecting plant viral diseases are also gaining popularity and are useful for making a rapid and accurate diagnosis of viral disorders. The advantages and future uses of nanotechnology in precision agriculture are covered in this article. Modern technologies and methods based on nanotechnology can solve many issues in traditional agriculture and could revolutionize this industry. Full article

Reliable precipitation data at appropriate resolutions are essential for crop irrigation scheduling, climate change assessments, and mitigating floods and droughts. However, information on precipitation at acceptable spatial and temporal scales is lacking in Pakistan, particularly in undulating areas such as the Potohar region. Therefore, an investigation was conducted to check the accuracies of two satellite-based precipitation products (SPPs), PERSIANN-CDR and TRMM, concerning the gauge-based data obtained from the Pakistan Metrological Department (PMD). At the pixel and regional scales, the uncertainty in satellite-based daily, monthly, and annual precipitation estimates was investigated. Statistical indices were used for the spatio-temporal assessment of SPPs. The results reveal that both SPPs performed better on the monthly and daily scales. The TRMM precipitation product was in better agreement with in situ gauge-based data (with CC > 0.7). Therefore, we recommend using TRMM data for hydro-climatic applications in the Potohar region of Pakistan. Full article

Horticultural crops have a special impact on a nation’s economy due to their significance in raising the living standards of farmers. The traditional method for crop protection is becoming ineffective with an increase in climate change effects. Precision Agriculture (PA) presents a solution to this issue through the precise monitoring and forecasting of pests, which improves productivity and guarantees environmental sustainability. The productivity of the existing plant production system can be increased by using precision agriculture techniques. Various PA technologies that enable farmers to monitor the pest include remote sensing, the Internet of Things, geographical information systems, and artificial intelligence. The PA technique assists with pest forecasting and the management of pests and diseases in plants. The content of this article was gathered through a literature review of recent research. The approaches used in PA for pest forecasting, monitoring, and management are the main topic of this study. In the long term, this study will help farmers to manage insect pests in a way that is both affordable and environmentally beneficial. Full article

Irrigated agriculture is highly dependent on groundwater resources in Pakistan. Due to the fiber and food requirements, the reliance on groundwater has been increasing during the past two decades. This research work was conducted at the canal command area of the Dera Ghazi Khan (D.G Khan) canal for years 2017–2019. There were two products of the satellite i.e., AQUA (EOS PM) and TERRA (EOS AM), which were used in this research for determining groundwater demand in the area. For Rabi seasons 2017–2018 and 2018–2019, cropping areas of the major crops i.e., wheat and sugarcane, were 98,712.5 and 131,856.2 ha, and 100,568.7 and 132,743.7 ha, respectively. For the Kharif seasons of 2018 and 2019, cropping areas of major crops i.e., rice, cotton, and sugarcane, were 82,093.7, 74,150, and 98,712.5 ha, and 75,687.5, 79,275, and 132,743.7 ha, respectively. Full article

Shortly, the demand for food production will increase, and the challenges to agriculture, including climate change, land degradation, farmable land availability and labor effort, will be resolved by applying precision agriculture techniques. In modern precision agriculture, variable rate (VR) technology is one of the key research areas. This technology provides an improved adjustment of agrochemical dosage to the trees by applying pesticide spraying to only areas where trees are detected based on their heights. This paper presents the testing results of an indigenously developed spot-specific sprayer for orchards based on tree detection through ultrasonic sensors. Lab Results show that spot-specific spraying provides 40% of agrochemical savings for an area of 100 acres compared with traditional spraying for the citrus orchard. Such technology can facilitate the farmers by automatic pesticide sprayers and economically protect the plants. Full article

A real-time approach based on IoT sensors to detect and measure the canopy size of trees in orchards for plant data collection has been proposed. This work discusses the issues related to sensors, particularly ultrasonic sensors for canopy size measurement. Other core issues related to sound cone measurement, angle error, crosstalk error, and measurement accuracy have also been investigated in depth. Keeping these aspects in mind, this work focused on the usability of these sensors while providing information about environmental structures. The feasibility of this research was tested in a laboratory. The results showed that for large sensor spacings, the interference errors are minimal, and the sensors’ field distance measurements are accurate. Full article

Khyber Pakhtunkhwa launched the Billion Tree Afforestation Project (BTAP) in 2014. Pakistan also initiated a “10 billion trees in five years” project in 2018. The soil and water assessment tool (SWAT) model was used to forecast the impacts of LULC changes on water yield under three scenarios: before planting, after 1 billion trees planted, and after 10 billion trees planted. Model calibration and validation were undertaken at the Bisham Qila gauging station from 1984 to 2000 and 2001 to 2010. The Tarbela reservoir’s mean annual runoff declined from 53.70 mm to 45.40 mm after 1 billion trees planted, while under the third scenario it approximated 35.05 mm. Full article

Due to Pakistan’s complex hydro-climatic and topographical features, drought is a severe problem. It is necessary to regionalize various topographical and hydrometeorological occurrences into uniform zones. The regionalization of clusters across Pakistan has been examined and analyzed using the hierarchical classification of principal components (HCPC). Five statistically homogenous zones were made, which were validated through the cluster validation indices. Univariate discordancy tests were run using the drought’s severity and duration as inputs. Over 12 months, drought was regionalized for SPEI time scales, indicating regional discordancy in cluster 4, while cluster 2 had a smaller number of stations, which were further adjusted to ensure homogeneity. The results of this research might be utilized to offer the fundamental information needed to develop a regional drought mitigation plan. Full article

The application of water-retention polymers with improved fertilizers is a better crop-growing technique, especially in soils where the water-retention capacity is low. In Pakistan, different types of fertilizers, such as urea, DAP, MOP or SOP, are used from sowing to harvesting of crops. The use of water-retention polymers in low water-retaining soils is very important to increase its retention time. The experiment was conducted on half an acre of land in FFC Research Center located in Dyyalgarh, Millat Rd., near Deputy Wala interchange M4, Faisalabad, Punjab, Pakistan. The seed variety used in this experiment is zincole and the seed rate is 50 kg/acre. This experiment contains four different treatments, and each treatment contains three replicates. In T1, no water-retention polymers were used, while T2 was treated with standard and neem-coated urea under no water-retention polymer application. While in T3 and T4 recommended doses of polymers were used with standard and neem-coated urea. Irrigation scheduling was determined using tensiometers.. The research is aimed to keep moisture available in the root zone for better growth. For proper moisture monitoring tensiometers were installed. Full article

The energy crisis in Pakistan has amplified the need for solar photovoltaic (PV) technologies in the agriculture sector. Currently, solar PV systems in Pakistan are primarily used for water-pumping irrigation. This article presents an investigation of the cost–benefit analysis of solar photovoltaic energy systems in the agriculture sector in the Baluchistan province of Pakistan. The findings of the study reveal that solar PV systems are relatively economical, as a benefit-to-cost ratio for the solar system is calculated to be 9.3 as compared to grid electricity which is calculated to be 8.4. Furthermore, solar photovoltaics can increase agricultural productivity substantially by providing a continuous power supply for water-pumping irrigation. However, the high initial cost and weather dependency of solar systems are the main obstacles to adopting PV technologies in the agriculture sector. Nevertheless, inconsistent grid power supply and sky-rocketing energy costs in Pakistan cause the local farmers to shift to solar PV systems for water-pumping irrigation to boost their agricultural productivity. Full article

Conventional agricultural practices and a rapidly growing population have both contributed to an increase in interest in cutting-edge research on environmental friendly farming methods. A field experiment to investigate the potential of soil probiotics on soil and plant health is under process at IOT Smart Research Farm, PMAS-Arid Agriculture University Rawalpindi from 22 June till mid October 2022. The plots contain four different treatments (Control, Full dose NPK, Probiotics only and ½ NPK+ Probiotics) on peanut crop. Probiotics (Actinomycetes sp. & Mycobacterium neoaurum) were applied through seed coating. Treatments were triplicated in a randomized complete block design. Different plant physiological characteristics (height, canopy, no of leaves, leaf area index, chlorophyll content, and normalized difference vegetation index) and soil properties (pH, Ec, moisture, nitrogen, phosphorous, and potassium) are under investigation. For different plant parameters different novel devices are being used, such as leaf area index meters to find the index area, and chlorophyll meters for chlorophyll content, whereas for soil parameters proximal sensors are being used. The findings of the trial up till now show the best results in ½ NPK+ probiotics followed by probiotics, full-dose NPK and control which are encouraging, indicating enhanced crop productivity and improved soil health. This study will provide a way out for increased peanut production in an environmental friendly manner for farmers. Full article

Promising Land and Water Conservation Practices (LWCPs) play a vital role in restraining floods and keeping the land productive. Floods are usually destructive and increase the risk of drowning, waterborne diseases, malnutrition, and multiple long-term knock-on effects. Similarly, the 2022 monsoon season has prompted the most severe flood in Pakistan. The main objective of this review is to highlight the importance of LWCPs as an adaptation strategy for flood mitigation. Moreover, different LWCPs are discussed concerning studies carried out in different regions and published in scientific journals, technical reports, and notes from experts. It was observed that both the in situ and ex situ LWCPs have a significant effect on reducing land degradation and flood control. Additionally, most of the reviewed studies showed a positive impact of LWCPs on agricultural productivity, primarily due to the retention of nutrients and moisture. Hence, land conservation practices including biological and agronomic measures (i.e., contour farming, conservation tillage, strip cropping, vegetation, etc.), and mechanical or engineering methods (i.e., check dams, bunding, ponds/reservoirs, etc.) are aimed at reducing the run-off velocity and mitigating the floods. The results of this study will encourage the stakeholders to adopt LWCPs to lessen flood hazards and uplift agricultural production by limiting the land degradation processes. Full article

Due to the intense seasonality, high labor intensity, and high cost, picking fruit and vegetables typically requires a significant amount of personnel, material resources, and time. The fruit and vegetable picking is a critical role in the agricultural production chain. At the same time, the world is facing the challenge of an aging population. As a result, the requirements of current agricultural output cannot be addressed by using the traditional ways of picking. The robots picking have been widely utilized in the domains of fruit and vegetable production due to increases in labor productivity, picking efficiency, cost, and other aspects related to the industry. Therefore, the structural characteristics and target recognition methods for the end-effectors of picking robots will be thoroughly summarized. This study will ensure that the future direction of structural development and recognition methods that are matched with fruit and vegetable picking are more visible. Full article

Irrigation for high Andean agriculture is traditionally performed with rainwater and without the use of technology, where the influence of changes in water volumes and/or water losses is not considered. Likewise, the limited information on high Andean crops generates a lag in the use of irrigation technology. Improving the efficiency of irrigation in crops contributes substantially to the sustainable use of water. One way to perform this is by applying control strategies to irrigation processes that consider implementing a feedback logic of the water necessary for irrigation, thus satisfying the water demand of plants and minimizing waste. The article proposes a control strategy applying a model predictive control (MPC) that calculates the optimal amount of water for daily irrigation. The most important attraction of the model is the prediction and future behavior of the controlled variables as a function of the changes in the manipulated variables. The objective is to improve the productivity of the crop at minimum water consumption. For this, it will be necessary to use models that link with the Aquacrop software and which are allowed to be a source of data, as well as being used for the prediction of future values. The predictive model is evaluated in the Quinoa crop (Chenopodium Quinoa Willdenow), and the information is validated against the traditional irrigation data existing in the literature. Preliminary results indicate that the predictive model can achieve greater crop efficiency and reduce significant irrigation water supplies. Full article

The ever-increasing world’s population, the consequent heavy demand for food supply, and the lack of rain-fed agriculture to meet such demands have increased the role of irrigation in agricultural production. Water management in the irrigation system is the biggest problem, particularly in regions where the effects of climate change are noticeable. The amount and timing of the crop’s water requirements are under debate. Information about crops, weather, and/or soil is needed for this purpose. Unfortunately, getting such information is difficult, especially when working with enormous tracts of property. Scientists have been working to find the answers to these issues for many years. The use of remote sensing to gather the necessary data is one area that has attracted interest. The advantage of remote sensing is that data collection over vast distances becomes simple and efficient. For the purpose of enhancing sustainability, crop yield, and environmental quality, precision agriculture involves the use of agronomic concepts and innovative technology to control the geographical and temporal variance related to every aspect of agricultural output. Crop water status is monitored in agricultural areas using a variety of remote sensing techniques. It mainly includes remote sensing, crop monitoring in terms of water management, the use of drones, and modern irrigation techniques for the purpose of saving water and increasing water use efficiency in crops. This review is focused on remote sensing technologies for precision irrigation used to calculate evapotranspiration, infrared thermography, crop water status, and crop attributes. The framework for achieving this goal has included precision agriculture as a valuable element. By using these techniques, we can overcome the problem of water shortage, which is crucial for agriculture. Full article

Agricultural sustainability and food security are adversely affected by nutrient deficiency in the soil that in turn reduces crop yield. To restore soil fertility, precision agriculture (PA) techniques are highly encouraged. The PA techniques include the use of integrated sensors, information systems, better-quality machinery, and informed management to improve productivity. The quality and quantity of agricultural products can be improved by precision farming. The use of remote sensing is a nondestructive technique that facilitates the application of PA. The nutrient use efficiency of crops can be improved by using PA technology. In this regard, various remote sensing techniques including hyperspectral remote sensing, visible light remote sensing, and the back-propagation neural network (BPNN) model combined with ordinary kriging (OK) known as BPNKOK are currently being employed to improve soil nutrients management. These techniques assist in non-destructive monitoring of plant growth and hence aid in sustaining crop yields. Full article

Technology integration between the farm and the consumer is at the heart of digital agriculture. New technologies for developing countries, such as vertical indoor farming that uses automation and robots, might speed up the elimination of rural poverty and hunger worldwide. Significant technical developments include state-of-the-art greenhouse techniques, laser-guided precision farming, AI, and blockchain. Connected farm machinery collects data that may then be used to research the soil and climate of a given area, allowing experts to offer advice on seed selection and the optimal timing for applying pesticides and fertilizers. One of the most widely used innovations of the previous century was the mobile phone. The use of digital technology will improve communication between consumers and farmers. The public now has more accessible access to information on farming because of the wealth of data collected on crops and livestock. Smart farming’s impact on crop yields will be seen in the long term. Full article

Precision agriculture (PA) has the potential to radically transform agronomic systems. It is an effective approach for viable zone management in the agriculture field. In today's era of finite resources and drastic consequences of climate change, an approach to PA which is an integration of below-the-ground sensors, multispectral satellite imagery, and weather monitoring system is reshaping agriculture from static to smart. In this paper, a real-time case study at a lemon orchard in Gadap, Sindh, Pakistan is presented where PA practices are being implemented successfully. At the farm locally developed innovative agri-tech devices are deployed which are embedded with electrical conductivity, soil temperature, soil moisture sensor, and nitrogen, phosphorus, and potassium sensor to monitor real-time conditions of the soil for precision irrigation and fertilizer application. Along with device data, incorporation of weather data, agronomist advisory and use of satellite imagery offer a full-functioning monitoring system for viable decisions. This system also favors tracking variations in crop health & pest attack for precise pesticide spray. The data output is observed through a web application. Using these drivers for PA there was increased flowering in the orchard as compared to other farms in the vicinity. Hence, a promising surplus yield and least toxic better fruit quality are being obtained, along with the preservation of biodiversity and environment sustainability the output yield of lemons was quite better than the conventional agriculture practices. PA is an extraordinary approach to leap closer to food security. Full article

Agriculture is extremely vulnerable to climate change, creating more difficult challenges. Presently, the agricultural sector contributes to between 19 and 29% of all global greenhouse Gas (GHG) emissions. Methane (CH₄), nitrous oxide (N₂O), and carbon dioxide (CO₂) are the main types of greenhouse gases generated by the agricultural industry. Energy use before and after farms, as well as shifting ground carbon stocks above and below as a result of changes in land use, are major sources of CO₂ emissions. There has been a trend in recent years toward lowering GHG emissions in the agriculture sector. Precision agriculture Technologies (PAT) address the field’s temporal and spatial variability to maximize the usage of agricultural inputs (i.e., irrigation, fuel, and fertilizers). The PAT can keep or increase productivity while lowering GHG emissions from agricultural activities, whereas the variable rate irrigation (VRI) approach is helpful in this scenario. Recent research shows that VRI has a significant potential to mitigate GHG. The present study reviews research related to VRI that address the reduction in GHG emissions. Full article

Crop growth and yield are influenced by the genetic potential of the cultivar, soil, weather, and cultivation practices, i.e., sowing date, irrigation and fertilizer amount, and biotic stresses. Temporal variation in yield and growth has been largely forecasted using climate as a predictor, which can be achieved by using either an empirical or crop simulation approach for a given location. Climate and soil data collected over agricultural land regularly aid in crop growth monitoring, as well as crop vitality assessment. Crop simulation models (CSM) that have been successful in field-scale applications are now being implemented in GIS framework to simulate and monitor crop growth with remote sensing inputs, allowing for sensitive evaluations of seasonal weather conditions, local variability, and crop management signals. This research was designed to monitor the growth of three varieties of kiwifruit, i.e., Hayward grafted, Green-flesh, and Hayward, in four different localities: Hazaro (Attock), Simli Dam (Pind Begwal), GPU (germ plasm unit) Arid Agriculture University Rawalpindi and ZTBL (Zarai Taraqiati Bank Limited) Farm Islamabad, each of which has different soil and weather conditions. Soil proximal sensors were used to measure soil characteristics, and data loggers were installed in each field to monitor the weather parameters to collect data that influences crops. In this study, we used a quantitative method and GIS-integrated data to assess the impact of soil and climate on kiwifruit growth. It can help policy makers and researchers to identify new agro-climatic zones in Pakistan’s semi-arid regions for kiwifruit farming based on this data. In this study, we found that kiwi is very susceptible to temperatures above 40 °C, which cause mortality in kiwifruits plants. Morphological data with respect to soil and climate results showed that green-fleshed and Hayward varieties performed slightly better than Hayward grafted, which was most susceptible to diseases and heat damage. Full article

All tropical and subtropical areas of the world are suitable for citrus cultivation. In managing fertilizer application efficiency in orchards, variable-rate technology (VRT) has been demonstrated to be an important element. This article aims to study the significance of variable-rate fertilization for citrus in the arid region of Pakistan. The NPK was calculated before the application of the variable-rate fertilizer. The plant height and stem girth were determined before and after fertilizer application. The preliminary results revealed that the stem girth performed significantly better than the plant height after applying fertilizer by VRT. The preliminary results showed a significant difference in the fruit yield between the VRT and uniform-rate fertilizer application. Full article

Soil moisture sensors and hydraulic modeling play a vital role in managing surface irrigation systems. Crop water productivity can be improved by managing the inflow cut-off time and optimizing the other field scale measurements. As such, hydraulic modelling and field experiments were carried out at the University of Agriculture Faisalabad-Pakistan. The soil moisture sensor (SEN-13322) and the WinSRFR model were used for this purpose. In total, nineteen treatments including eighteen simulated treatments and one conventional treatment were designed at two levels of discharge (Q₁:0.0025 and Q₂:0.0035 m³s⁻¹), at three sensor positions (S₁:55%, S₂:65%, and S₃:75%) across the field length, as well as with three different border widths (B₁:6.4m, B₂:8.5m, and B₃:10.7m) after successful sensor and model calibration during the two growing seasons of 2016–2017 and 2017–2018. The results revealed a significant difference between the means and the treatment T₁₀ i.e., Q₂S₁B₁ that were found to be highly efficient and uniform. Full article

Precision agriculture is getting immense attention from researchers and farmers across the world due to the threatening situation of the demand and production gap. Evolution in the electromechanical system and the emergence of intelligent monitoring and conditioning systems have enabled closing the gap to make agronomy quicker, lesser prone to infestations, and still profitable at the same time. Whereas the Internet of Things (IoT) has enabled access to relevant data remotely and automates essential response systems to any threat or requirement by a plant in a particular environment. This study concentrates on gathering such advanced mechatronic techniques in the agricultural sector and analyses of the benefits and disadvantages of the modern method. Full article

Rainfall is a key factor in hydrological, meteorological, and water management applications in restricted regions or basins, but its measurement remains difficult in mountainous or otherwise remote places due to a lack of readily available rain gauges. While satellite rainfall data offer a better temporal resolution than other sources, the majority of this data are only available at a coarse geographic resolution, which distorts the true picture of precipitation. Thus, researchers at the University of Agriculture in Faisalabad used the normalized difference vegetation index (NDVI) monthly data and 1 km topography data for the whole Indus Basin from 2002 to 2011 to reduce the TRMM’s spatial resolution from 25 km to 1 km. An approach to downscaling based on a regression model with residual correction was established in this study. First, we resampled the NDVI and TRMM datasets to a 25 km resolution and established a regression model connecting the two datasets. Precipitation was forecasted at a distance of 25 km. The TRMM 3B43 product was then adjusted downward by the projected precipitation to achieve the residual value. The IDW method was used to reduce the resolution of the residual image from 25 km to 1 km. Rainfall was predicted using a regression model applied to NDVI at a 1 km spatial resolution. The final downscaled precipitation was created by combining the modeled precipitation at 1 km resolution with the residual image. The result was double-checked by the post-processing steps of validation and calibration. Full article