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Huanglongbing is a severe citrus disease that causes significant tree and crop losses worldwide. It is caused by three Candidatus liberibacter species and spread by psyllids and infected budwood. Various methods have been used to diagnose and understand HLB, including recent advances in molecular and biochemical assays that explore the pathogen's mode of action and its impact on the host plant. Characterization is essential for developing sustainable HLB management strategies. Nanotechnology, particularly nano sensors and metal nanoparticles, shows potential for precise disease diagnosis and control. Additionally, antibiotics, nanomaterials, and genetic engineering techniques like transgenesis offer promising avenues for mitigating HLB. These diverse approaches, from conventional to cutting-edge, contribute to developing integrated HLB management strategies for sustainable citrus cultivation. The review highlights the significant advancements in conventional and advanced molecular and biochemical characterization of HLB, aiding in early detection and understanding of the infection mechanism. It emphasizes the multidimensional efforts required to characterize disease and devise innovative management strategies. As the citrus industry faces unprecedented challenges, exploring new frontiers in HLB research provides hope for sustainable solutions and a resilient future for global citrus cultivation., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Land surface temperature (LST) is defined as a phenomenon which shows that microclimate of an urban system gets heated much faster than its surrounding rural climates. The expansion of buildings has a noteworthy influence on land use/land cover (LULC) due to conversion of vegetation land into commercial and residential areas and their associated infrastructure by which LST is accelerated. The objective of the research was to study the impact of changes in LULC on LST of Southern Punjab (Pakistan) through remote sensing (RS) data. Landsat images of 30-year duration (1987, 1997, 2007 and 2017) were employed for identifying vegetation indices and LST in the study region. These images also helped to work out normalized difference water index (NDWI) and normalized difference built-up index (NDBI) maps. There was an increase from 29620 (3.63 %) to 88038 ha (10.8 %) in built-up area over the 30 years. LST values were found in the range 12-42 °C, 11-44 °C, 11-45 °C and 11-47 °C in the years 1987, 1997, 2007 and 2017, respectively. Regression coefficients (R 2 ) 0.81, 0.78, 0.84 and 0.76 were observed between NDVI and LST in the corresponding years respectively. Our study showed that NDVI and NDWI were negatively correlated with less LST; however, NDBI showed positive correlation with high LST. Our study gives critical information of LULC and LST and will be a helpful tool for policy makers for developing effective policies in managing land resources., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Coronavirus disease (COVID)-19 is a viral and transferable disease caused by severe respiratory syndrome-coronavirus-2. It can spread through breathing droplets in human beings. It caused 5.32 million deaths around the world at the end of 2021. COVID-19 has caused several positive impacts as well, such as a reduction in air, water, and noise pollution. However, its negative impacts are by far critical such as increased death rate, increased release of microcontaminants (pesticides, biocides, pharmaceuticals, surfactants, polycyclic aromatic hydrocarbons (PAHs), flame retardants, and heavy metals), increased biomedical waste generation due to excessive use of safety equipment and its disposal, and municipal solid waste generation. Environmental pollution was significantly reduced due to lockdown during the COVID-19 period. Therefore, the quality of air and water improved. COVID-19 affected all sections of the population, particularly the most vulnerable members of society, and thus pushed more people into poverty. At the world level, it increased risks to food safety by increasing prices and lowering revenues, forcing households to reduce their food consumption in terms of quantity and quality. COVID-19 also upset various exercises e.g., horticulture, fisheries, domesticated animals, and agribusiness hence prohibiting the development of merchandise for poor-country ranchers. Most of the patients can self-recover from COVID-19 if they do not have any other diseases like high blood pressure, diabetes, and heart problems. Predictably, the appropriate execution of the proposed approaches (vaccination, wearing face masks, social distancing, sustainable industrialization) is helpful for worldwide environmental sustainability., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Human interventions and rapid changes in land use adversely affect the adequate distribution of water resources. A research study was conducted to quantify the gap between demand and supply for irrigation water in Multan, Pakistan, which may lead to sustainable water management. Two remotely sensed images (Landsat 8 OLI and Landsat 5 TM) were downloaded for the years 2010 and 2020, and supervised classification method was performed for the selected land use land cover (LULC) classes and basic framework. During the evaluation, the kappa coefficient was found in the ranges of 0.83-0.85, and overall accuracy was found to be more than 80% which indicated a substantial agreement between the classified maps and the ground truth data for both years and seasons. The LULC maps showed that urbanization has increased by 49% during the last decade (2010-2020). Reduction in planting areas for wheat (9%), cotton (24%), and orchards (46%) was observed. An increase in planting areas for rice (92%) and sugarcane (63%) was observed. The changing LULC pattern may be related to variation in water demand and supply for irrigation. The irrigation water demand has decreased by 370.2 Mm 3 from 2010 to 2020, due to the reduction in agricultural land and an increase in urbanization. Available irrigation water supply (canals/rainfall) was estimated as 2432 Mm 3 for the year 2020 which was 26% less than that of total irrigation water demand (3281 Mm 3 ). The findings also provide the database for sustainable water management and equitable distribution of water in the region., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Corporate social responsibility turned into a global sensation from the inception of the twenty-first century in the corporate world and grabbed immense engrossment from all stakeholders in their decision-making process. Capital structure and corporate governance practices are the well-mellowed facets of corporate finance literature. In this study, the moderating role of corporate social responsibility (CSR) between corporate governance and leverage of the US and Chinese listed firms has been established, with a further extension of analyzing the moderating role of CSR between corporate governance and leverage in high vs low leveraged firms and high CSR vs low CSR firms as the novelty of this study and has never been examined in both economies and globally. The data of 1989 Chinese-listed firms from 28 sectors of the economy and 6640 US-listed firms from 27 sectors of the economy has been taken from 2001 to 2019 and analyzed through fixed effect regression and system generalized method of moment (GMM). Results of the study reveal that CSR and corporate governance are negatively associated with the leverage of both Chinese and US firms. Moreover, the moderating role of CSR has established between corporate governance and leverage negative relationship. The moderating role of CSR in the relationship of leverage and corporate governance is established only in low-leveraged firms whereas it is insignificant in high-leveraged firms. System GMM confirms the signs and significance of the regression results; that is why regression results are robust and reliable, and there is no endogeneity problem in our model. The study also gives an insight for future research on high- and low-leveraged firms and firms with more CSR score than less CSR score with other dimensions such as firm performance and firm value variables., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the worldwide pandemic coronavirus 2019 (COVID-19). The aim of this study was to evaluate the effects of COVID-19 on food supply chain and agriculture in Punjab, Pakistan, by using space-time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province. The STSS detected "active" and emerging clusters that are current at the end of our study area-particularly, 17 clusters were formed while adding the updated case data. Software ArcGIS 10.3 was used to find relative risk (RR) values; the maximum RR value was found to be 42.19 and maximum observed cases 53,265 during June 15-July 1, 2020. It was not always necessary that if the number of active cases in Punjab increased, there should be higher relative risk for more number of districts and vice versa. Due to the highest number of cases of COVID-19 and RR values during July, mostly farmers faced many difficulties during the cultivation of cotton and rice. Mostly farmers (72%) observed increase in prices of inputs (fertilizers and pesticides) during lockdown. If the supply chain of agriculture related inputs is disturbed, farmers may find it quite difficult to access markets, which could result in a decline in production and sales of crops and livestock in study area. It is suggested that to protect the food security and to decrease the effect of the lockdown, Punjab government needs to review food policy and analyse how market forces will respond to the imbalanced storage facilities and capacity, supply and demand and price control of products. The findings of this study can also help policy-makers to formulate an effective food security and agriculture adaptation strategy., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Plant diseases significantly impact the global economy, and plant pathogenic microorganisms such as nematodes, viruses, bacteria, fungi, and viroids may be the etiology for most infectious diseases. In agriculture, the development of disease-free plants is an important strategy for the determination of the survival and productivity of plants in the field. This article reviews biosensor methods of disease detection that have been used effectively in other fields, and these methods could possibly transform the production methods of the agricultural industry. The precise identification of plant pathogens assists in the assessment of effective management steps for minimization of production loss. The new plant pathogen detection methods include evaluation of signs of disease, detection of cultured organisms, or direct examination of contaminated tissues through molecular and serological techniques. Laboratory-based approaches are costly and time-consuming and require specialized skills. The conclusions of this review also indicate that there is an urgent need for the establishment of a reliable, fast, accurate, responsive, and cost-effective testing method for the detection of field plants at early stages of growth. We also summarized new emerging biosensor technologies, including isothermal amplification, detection of nanomaterials, paper-based techniques, robotics, and lab-on-a-chip analytical devices. However, these constitute novelty in the research and development of approaches for the early diagnosis of pathogens in sustainable agriculture.

Climate change is occurring and is influencing biological systems through augmented temperatures, more inconstant precipitation, and rising CO 2 in the atmosphere. For sustainable landscaping, it was essential to assess the diversity of native/wild grasses and their suitability for turf and to combat the salinity problem in the region. For this purpose, a native halophytic grass, Aeluropus lagopoides, was investigated by conducting mowing tests on its ecotypes during the year 2014-2016 under desert climatic conditions. The research was carried out in two phases, i.e. Phase-I was for collection and establishment of ecotypes from various parts of UAE, while in Phase-II, mowing tests were conducted. During mowing tests, 50 ecotypes of A. lagopoides were given various mowing treatments (i.e. they were cut back at 1-, 2-, 3-, 4- and 5-cm heights) in field conditions. Significant differences were found among various ecotypes for different agronomic parameters such as ground cover, canopy stiffness, leaf number, clippings fresh and dry weights and internode length. Overall, the grass exhibited better performance at mowing heights of 3 and 4 cm, which are the standard mowing heights for turfgrasses. Ecotypes FA5, RA3, RUDA2, RUDA7 and RUADA1 of A. lagopoides showed the best performance against mowing shock and became the candidates for the turfgrass varieties from the native Arabian flora.

Land use/land cover (LULC) change has serious implications for environment as LULC is directly related to land degradation over a period of time and results in many changes in the environment. Monitoring the locations and distributions of LULC changes is important for establishing links between regulatory actions, policy decisions, and subsequent LULC activities. The normalized difference vegetation index (NDVI) has the potential ability to identify the vegetation features of various eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. Similarly, the normalized difference built-up index (NDBI) may be used for quoting built-up land. This study aims to detect the pattern of LULC, NDBI, and NDVI change in Lodhran district, Pakistan, from the Landsat images taken over 40 years, considering four major LULC types as follows: water bodies, built-up area, bare soil, and vegetation. Supervised classification was applied to detect LULC changes observed over Lodhran district as it explains the maximum likelihood algorithm in software ERDAS imagine 15. Most farmers (46.6%) perceived that there have been extreme changes of onset of temperature, planting season, and less precipitation amount in Lodhran district in the last few years. In 2017, building areas increased (4.3%) as compared to 1977. NDVI values for Lodhran district were highest in 1977 (up to + 0.86) and lowest in 1997 (up to - 0.33). Overall accuracy for classification was 86% for 1977, 85% for 1987, 86% for 1997, 88% for 2007, and 95% for 2017. LULC change with soil types, temperature, and NDVI, NDBI, and slope classes was common in the study area, and the conversions of bare soil into vegetation area and built-up area were major changes in the past 40 years in Lodhran district. Lodhran district faces rising temperatures, less irrigation water, and low rainfall. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support from government.

The use of sewage water as an irrigation source can be beneficial in agricultural practices, however, it may result in human health risks due to the consumption of heavy metal(loid)-contaminated food. This study evaluated the suitability of using sewage water (SW), freshwater (FW), and groundwater (GW) for vegetable irrigation in District Vehari. Spinach (Spinacia oleracea) plants were grown in pots irrigated with FW, GW, and SW in different proportions and combinations. The results indicated the substantial lesser buildup of heavy metal(loid)s (As (- 0.8%), Cd (- 38%), Cr (- 6.2%), Cu (- 20%), Fe (- 9.2%), Mn (- 13%), Ni (- 16%), Pb (- 19%), and Zn (-15%)) in soil after S. oleracea cultivation compared to unirrigated soil possibly due to high metal(loid) uptake by S. oleracea. Irrigation with all types of waters resulted in metal(loid) accumulation in S. oleracea predominantly in roots. The combinations of FW, GW, and SW resulted in high metal(loid) accumulation (As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) in the edible S. oleracea leaves than their alone application. Owing to high metal(loid) buildup, plants showed a linear trend in physiological imbalance in terms of reduced pigment content, induction of peroxidation, and oxidation of lipids. The severe oxidative stress was observed in S. oleracea plants under FW and GW irrigation due to high metal(loid) accumulation. The risk indices showed possible carcinogenic risk (CR > 0.0001) and non-carcinogenic risk (HI > 1) from the consumption of metal(loid)-contaminated S. oleracea leaves. Results revealed unsuitability of all waters and their combinations for S. oleracea irrigation. Moreover, this study does not encourage the use of mixed water for vegetable irrigation in Vehari District. Therefore, it is of utmost importance to monitor the quality of irrigation waters to ensure food safety and prevent chronic health risks to the exposed population.

Water and land both are limited resources. Current management strategies are facing multiple challenges to meet food security of an increasing population in numerous South Asian countries, including Pakistan. The study of land cover/land use changes (LCLUC) and land surface temperature (LST) is important as both provide critical information for policymaking of natural resources. We spatially examined LCLU and LST changes in district Multan, Pakistan, and its impacts on vegetation cover and water during 1988 to 2017. The LCLUC indicate that rice and sugarcane had less volatility of change in comparison with both cotton and wheat. Producer's accuracy (PA) is the map accuracy (the producer of map), but user's accuracy (UA) is the accuracy from the point of view of a map user, not the map maker. Average overall producer's and user's accuracy for the region was 85.7% and 87.7% for Rabi (winter) and Kharif (summer) seasons, respectively. The results of this study showed that 'built-up area' increased with 7.2% of all the classes during 1988 to 2017 in the Multan district. Anthropogenic activities decreased the vegetation, leading to an increase in LST in study area. Changes on LCLU and LST during the last 30 years have shown that vegetation pattern has changed and temperature has increased in the Multan district.

Electronic waste (e-waste) is used for all electronic/electrical devices which are no more used. Conventionally, waste management policies are desfighandle the traditional waste. Although e-waste contains toxic materials, however, its management is rarely focused by policy makers; therefore, its negative impact on the global environment, ecosystem, and human health is aggravated. The review outlines the categories of e-waste materials, major pollutants including ferrous/non-ferrous metals, plastics, glass, printed circuit boards, cement, ceramic, and rubber beside, some valuable metals (such as copper, silver, gold, platinum). Toxic elements from e-waste materials, released in the air, water, and soil, include arsenic, cadmium, chromium, mercury, and lead, causing pollution. Although their roles in biological systems are poorly identified, however, they possess significant toxic and carcinogenic potential. It is therefore critical to monitor footprint and device strategies to address e-waste-linked issues from manufacturing, exportation, to ultimate dumping, including technology transmissions for its recycling. This review traces a plausible link among e-waste condition at a worldwide dimension, as far as settlement procedures to keep it secure and carefully monitored when traded. Their fate in the three spheres of the earth, i.e., water, soil, and air, impacts human health. The strategies and regulation to handle e-waste generation at the global level have been discussed. Graphical abstract .

Road traffic accidents (RTAs) are among the life-threatening issues facing rural as well as sub-/urban communities. Several factors contribute to RTAs ranging from human to technical and natural/environmental impacts. Anthropogenic air pollution and corresponding environmental factors also increase the probability of RTAs. Current study reports the relationship of the weather conditions to RTAs. The study establishes the relevancy of different weather conditions like rainfall, temperature, fog, and wind storm with the incidences of RTAs in rural and urban settings of Vehari, Punjab-Pakistan. The results of the study showed that rainfall, severe coldness, fog, and heat conditions were directly related with the occurrence of RTAs. The percentage of RTAs which occurred due to fog, rainfall, temperature, and other weather-related factors was 34, 25, 21, and 20%, respectively. The age of the driver significantly correlated (R 2  = 0.60) with RTAs; the drivers in the age group 40-60 years caused the least RTAs during their drive. Since the smaller vehicles were involved in maximum RTAs, it relates negatively (R 2  = 0.82) to vehicles power. Among different vehicles motor bikes were involved in most (42%) of the reported RTAs. Therefore, during severe weather conditions, vehicles with smaller size and young drivers must be dealt with carefully while interacting (crossing, overtaking, and maneuvering) on the roads regardless of rural or urban conditions. Factors including civic sense, traffic education, vehicle size, drivers' maturity, road conditions, and environmental impacts may be considered while designing traffic rules and traffic aware campaigns specific for developing countries such as Pakistan.

Growth, development, and economic yield of agricultural crops rely on moisture, temperature, light, and carbon dioxide concentration. However, the amount of these parameters is varying with time due to climate change. Climate change is factual and ongoing so, first principle of agronomy should be to identify climate change potential impacts and adaptation measures to manage the susceptibilities of agricultural sector. Crop models have ability to predict the crop's yield under changing climatic conditions. We used OILCROP-SUN model to simulate the influence of elevated temperature and CO 2 on crop growth duration, maximum leaf area index (LAI), total dry matter (TDM), and achene yield of sunflower under semi-arid conditions of Pakistan (Faisalabad, Punjab). The model was calibrated and validated with the experimental data of 2012 and 2013, respectively. The simulation results showed that phenological events of sunflower were not changed at higher concentration of CO 2 (430 and 550 ppm). However LAI, achene yield, and TDM increased by 0.24, 2.41, and 4.67% at 430 ppm and by 0.48, 3.09, and 9.87% at 550 ppm, respectively. Increased temperature (1 and 2 °C) reduced the sunflower duration to remain green that finally led to less LAI, achene yield, and TDM as compared to present conditions. However, the drastic effects of increased temperature on sunflower were reduced to some extent at 550 ppm CO 2 concentration. Evaluation of different adaptation options revealed that 21 days earlier (as compared to current sowing date) planting of sunflower crop with increased plant population (83,333 plants ha -1 ) could reduce the yield losses due to climate change. Flowering is the most critical stage of sunflower to water scarcity. We recommended skipping second irrigation or 10% (337.5 mm) less irrigation water application to conserve moisture under possible water scarce conditions of 2025 and 2050.

The combination of nitrogen and plant population expresses the spatial distribution of crop plants. The spatial distribution influences canopy structure and development, radiation capture, accumulated intercepted radiation (Sa), radiation use efficiency (RUE), and subsequently dry matter production. We hypothesized that the sunflower crop at higher plant populations and nitrogen (N) rates would achieve early canopy cover, capture more radiant energy, utilize radiation energy more efficiently, and ultimately increase economic yield. To investigate the above hypothesis, we examined the influences of leaf area index (LAI) at different plant populations (83,333, 66,666, and 55,555 plants ha -1 ) and N rates (90, 120, and 150 kg ha -1 ) on radiation interception (Fi), photosynthetically active radiation (PAR) accumulation (Sa), total dry matter (TDM), achene yield (AY), and RUE of sunflower. The experimental work was conducted during 2012 and 2013 on sandy loam soil in Punjab, Pakistan. The sunflower crop captured more than 96% of incident radiant energy (mean of all treatments), 98% with a higher plant population (83,333 plants ha -1 ), and 97% with higher N application (150 kg ha -1 ) at the fifth harvest (60 days after sowing) during both study years. The plant population of 83,333 plants ha -1 with 150 kg N ha -1 ominously promoted crop, RUE, and finally productivity of sunflower (AY and TDM). Sunflower canopy (LAI) showed a very close and strong association with Fi (R 2  = 0.99 in both years), PAR (R 2  = 0.74 and 0.79 in 2012 and 2013, respectively), TDM (R 2  = 0.97 in 2012 and 0.91 in 2013), AY (R 2  = 0.95 in both years), RUE for TDM (RUE TDM ) (R 2  = 0.63 and 0.71 in 2012 and 2013, respectively), and RUE for AY (RUE AY ) (R 2  = 0.88 and 0.87 in 2012 and 2013, respectively). Similarly, AY (R 2  = 0.73 in 2012 and 0.79 in 2013) and TDM (R 2  = 0.75 in 2012 and 0.84 in 2013) indicated significant dependence on PAR accumulation of sunflower. High temperature during the flowering stage in 2013 shortened the crop maturity duration, which reduced the LAI, leaf area duration (LAD), crop growth rate (CGR), TDM, AY, Fi, Sa, and RUE of sunflower. Our results clearly revealed that RUE was enhanced as plant population and N application rates were increased and biomass assimilation in semi-arid environments varied with radiation capture capacity of sunflower.

Crop nutrient management is an essential component of any cropping system. With increasing concerns over environmental protection, improvement in fertilizer use efficiencies has become a prime goal in global agriculture system. Phosphorus (P) is one of the most important nutrients, and strategies are required to optimize its use in important arable crops like cotton (Gossypium hirsutum L.) that has great significance. Sustainable P use in crop production could significantly avoid environmental hazards resulting from over-P fertilization. Crop growth modeling has emerged as an effective tool to assess and predict the optimal nutrient requirements for different crops. In present study, Decision Support System for Agro-technology Transfer (DSSAT) sub-model CSM-CROPGRO-Cotton-P was evaluated to estimate the observed and simulated P use in two cotton cultivars grown at three P application rates under the semi-arid climate of southern Punjab, Pakistan. The results revealed that both the cultivars performed best at medium rate of P application (57 kg ha -1 ) in terms of days to anthesis, days to maturity, seed cotton yield, total dry matter production, and harvest index during 2013 and 2014. Cultivar FH-142 performed better than MNH-886 in terms of different yield components. There was a good agreement between observed and simulated days to anthesis (0 to 1 day), days to maturity (0 to 2 days), seed cotton yield, total dry matter, and harvest index with an error of -4.4 to 15%, 12-7.5%, and 13-9.5% in MNH-886 and for FH-142, 4-16%, 19-11%, and 16-8.3% for growing years 2013 and 2014, respectively. CROPGRO-Cotton-P would be a useful tool to forecast cotton yield under different levels of P in cotton production system of the semi-arid climate of Southern Punjab.

Nitrogen (N) fertilizer is an important yield limiting factor for sunflower production. The correlation between yield components and growth parameters of three sunflower hybrids (Hysun-33, Hysun-38, Pioneer-64A93) were studied with five N rates (0, 60, 120, 180, 240 kg ha(-1)) at three different experimental sites during the two consecutive growing seasons 2008 and 2009. The results revealed that total dry matter (TDM) production and grain yield were positively and linearly associated with leaf area index (LAI), leaf area duration (LAD), and crop growth rate (CGR) at all three sites of the experiments. The significant association of yield with growth components indicated that the humid climate was most suitable for sunflower production. Furthermore, the association of these components can be successfully used to predict the grain yield under diverse climatic conditions. The application of N at increased rate of 180 kg ha(-1) resulted in maximum yield as compared to standard rate (120 kg ha(-1)) at all the experimental sites. In this way, N application rate was significantly correlated with growth and development of sunflower under a variety of climatic conditions. Keeping in view such relationship, the N dose can be optimized for sunflower crop in a particular region to maximize the productivity. Multilocation trails help to predict the input rates precisely while taking climatic variations into account also. In the long run, results of this study provides basis for sustainable sunflower production under changing climate.