Investigating the growth promotion potential of biochar on pea (Pisum sativum) plants under saline conditions.

Pea, member of the plant family Leguminosae, play a pivotal role in global food security as essential legumes. However, their production faces challenges stemming from the detrimental impacts of abiotic stressors, leading to a concerning decline in output. Salinity stress is one of the major factors that limiting the growth and productivity of pea. However, biochar amendment in soil has a potential role in alleviating the oxidative damage caused by salinity stress. The purpose of the study was to evaluate the potential role of biochar amendment in soil that may mitigate the adverse effect of salinity stress on pea. The treatments of this study were, (a) Pea varieties; (i) V1 = Meteor and V2 = Green Grass, Salinity Stress, (b) Control (0 mM) and (ii) Salinity (80 mM) (c) Biochar applications; (i) Control, (ii) 8 g/kg soil (56 g) and (iii) 16 g/kg soil (112 g). Salinity stress demonstrated a considerable reduction in morphological parameters as Shoot and root length decreased by (29% and 47%), fresh weight and dry weight of shoot and root by (85, 63%) and (49, 68%), as well as area of leaf reduced by (71%) among both varieties. Photosynthetic pigments (chlorophyll a, b, and carotenoid contents decreased under 80 mM salinity up to (41, 63, 55 and 76%) in both varieties as compared to control. Exposure of pea plants to salinity stress increased the oxidative damage by enhancing hydrogen peroxide and malondialdehyde content by (79 and 89%), while amendment of biochar reduced their activities as, (56% and 59%) in both varieties. The activities of catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) were increased by biochar applications under salinity stress as, (49, 59, and 86%) as well as non-enzymatic antioxidants as, anthocyanin and flavonoids improved by (112 and 67%). Organic osmolytes such as total soluble proteins, sugars, and glycine betaine were increased up to (57, 83, and 140%) by biochar amendment. Among uptake of mineral ions, shoot and root Na+ uptake was greater (144 and 73%) in saline-stressed plants as compared to control, while shoot and root Ca2+ and K+ were greater up to (175, 119%) and (77, 146%) in biochar-treated plants. Overall findings revealed that 16 g/kg soil (112 g) biochar was found to be effective in reducing salinity toxicity by causing reduction in reactive oxygen species and root and shoot Na+ ions uptake and improving growth, physiological and anti-oxidative activities in pea plants (Fig. 1). Figure 1 A schematic diagram represents two different mechanisms of pea under salinity stress (control and 80 mM NaCl) with Biochar (8 and 16 g/kg soil).

Clean energy transition and climate vulnerabilities: A comparative analysis of European and non-European developed countries.

Currently, the world faces an existential threat of climate change, and every government across the globe is trying to come up with strategies to tackle the severity of climate change in every way possible. To this end, the use of clean energy rather than fossil fuel energy sources is critical, as it can reduce greenhouse gas emissions and pave the way for carbon neutrality. This study examines the impact of the energy cleanability gap on four different climate vulnerabilities, such as ecosystem, food, health, and housing vulnerabilities, considering 47 European and non-European high-income countries. The study considers samples from 2002 to 2019. This study precedes the empirical analysis in the context of a quadratic relationship between the energy cleanability gap and climate vulnerability. The study uses system-generalized methods of the moment as the main technique, while panel quantile regression is a robustness analysis. Fixed effect and random effect models have also been incorporated. The study finds that the energy cleanability gap and all four climate vulnerabilities demonstrate a U-shaped relationship in both European and non-European countries, implying that when the energy cleanability gap increases, climate vulnerability decreases, but after reaching a certain threshold, it starts to increase. Development expenditure is found to be negatively affecting food and health vulnerabilities in European nations, while it increases food vulnerability and decreases health vulnerability in non-European nations. Regarding industrialization's impact on climate vulnerabilities, the study finds opposite effects for the European and non-European economies. On the other hand, for both groups, trade openness decreases climate vulnerabilities. Based on these results, the study recommends speeding up the energy transition process from fossil fuel energy resources towards clean energy resources to obtain carbon neutrality in both European and non-European groups.

Assessing the environmental sustainability gap in G20 economies: The roles of economic growth, energy mix, foreign direct investment, and population.

There is serious debate among researchers regarding the sustainability implications of economic prosperity and energy dependence. Energy consumption has a critical linkage with economic growth, but it also degrades environmental quality. Therefore, it is important to investigate the relationship between economic growth, the energy mix, and environmental sustainability. However, empirical literature utilizes narrow variables to capture environmental sustainability. Because of this, this research introduces a new environmental sustainability variable using entropy weighting and combining deforestation, household carbon emissions, and life expectancy. This study examines the relationship between environmental sustainability, economic growth, and other selected variables using data from 2002 to 2019 for the G20 and its high-, upper-, and low-middle-income member countries. Since shocks in one G20 country can affect another, this study uses the Augmented Mean Group (AMG) technique for empirical analysis. The results of this study indicate that Gross Domestic Product (EG) and its square term did not support the Environmental Kuznets Curve (EKC) theory. The energy mix has a positive impact on the environmental sustainability gap across all the samples except for the upper-middle-income group. Foreign direct investment positively affects this gap, while population growth has no significant impact. These findings demonstrate that policymakers should support environmentally friendly and clean energy sources to foster long-term economic growth and sustainability.

Does globalization and ecological footprint in OECD lead to national happiness.

This study examines the relationship between globalization, ecological footprint, innovation, and subjective wellbeing in the form of happiness, using a comprehensive assessment of OECD countries from 2008 to 2020. The study employs FGLS, Quantile, and Bootstrap Quantile regression estimation to investigate the quadratic effects of globalization, ecological footprint, and the moderating effect of innovation while controlling for renewable energy and population density. Happiness is a multidisciplinary subject, and this study focuses on the economic dimensions of happiness. The findings reveal a nonlinear relationship between ecological footprint and globalization, with negative effects on subjective wellbeing at high levels of ecological footprint and globalization. However, the moderating effect of innovation mitigates these adverse effects, indicating that innovation can help to offset the detrimental impacts of ecological footprint and globalization on subjective wellbeing. The study's implications are significant for policymakers promoting sustainable economic growth while enhancing subjective wellbeing. The findings highlight the importance of investing in innovation and sustainable development to promote subjective wellbeing in the face of increasing ecological footprint and globalization. Additionally, this research contributes to the multidisciplinary understanding of happiness and provides valuable insights for future research in this area.

Magnesium fertilization reduces high-temperature damages during anthesis in spring wheat (Triticum aestivum L.) by affecting pollen viability and seed weight.

Terminal heat during reproductive stages of wheat (Triticum aestivum L.) limits the productivity of the crop. Magnesium (Mg) is an essential macronutrient that is involved in many physiological and biochemical processes to affect photosynthesis and seed weight. The present study comparatively evaluated Mg applied to soil (80 kg MgSO4·7H2O ha-1) and to plant foliage (4% w/v) in improving wheat performance under terminal heat. Wheat crop was grown in two sets of treatments until the booting stage, and then one set of plants was shifted to a glasshouse (±5 °C) at the booting stage to grow until maturity in comparison to control plants kept under ambient warehouse condition. Heat stress reduced the pollen viability while foliar- and soil-applied Mg improved it by 3% and 6% under heat stress, respectively, compared to the control without Mg treatment. The 100-seed weight, spike length, and biological yield reduced by 39%, 19%, and 50% under heat stress; however, foliar and soil application increased 100-seed weight by 45% and 40%, spike length by 8% and 5%, and biological yield by 35% and 25% under heat stress, respectively. Soil Mg showed maximum SPAD chlorophyll values; however, response was statistically similar to that of foliar Mg as compared to the control without Mg supply. Membrane stability decreased (4%) due to heat stress while foliar and soil treatments improved membrane stability by 8% and 5% compared to that of the control, respectively. Thus, Mg application through soil or plant foliage can be an effective way to reduce negative impacts of terminal heat in wheat by improving pollen viability at anthesis and 100-seed weight that was attributed to increased chlorophyll contents during anthesis.

Stretchable, Strong, Recyclable Helicide Elastomer Based on Dynamic Covalent Interactions.

Current methods for making and disposing synthetic polymers have been widely pursued and are largely unsustainable. As a part of the solution, the reversible nature of dynamic covalent bonds emerges as an extraordinarily diverse and valuable feature in the development of exotic molecules and extended structures. With these bonds, it should be possible to construct recyclable and mechanically interlocked molecular structures using relatively simple precursors with preorganized geometries. A new helicide-based elastomer network is developed here with self-healing, recycling, and degradation features using a similar concept. The best self-healing performance (100%) was noted over 10-20 min, with various H2O, HCl, and NaOH solutions that delivered mechanical properties in the 1-1.4 MPa range. For hydrolytic degradation, the parameters are defined based on the type of binding, the pH of the solutions, and the copolymer network, which endowed a degradation time of approximately 4-11 h for each prepared sample. However, due to the reversible nature of the dynamic bonds, the material showed good recyclable mechanical properties compared to the pristine samples after five consecutive cycles, which meet the requirements of recyclable materials and recyclable packaging.

Nanobiotechnology in crop stress management: an overview of novel applications.

Agricultural crops are subject to a variety of biotic and abiotic stresses that adversely affect growth and reduce the yield of crop plantss. Traditional crop stress management approaches are not capable of fulfilling the food demand of the human population which is projected to reach 10 billion by 2050. Nanobiotechnology is the application of nanotechnology in biological fields and has emerged as a sustainable approach to enhancing agricultural productivity by alleviating various plant stresses. This article reviews innovations in nanobiotechnology and its role in promoting plant growth and enhancing plant resistance/tolerance against biotic and abiotic stresses and the underlying mechanisms. Nanoparticles, synthesized through various approaches (physical, chemical and biological), induce plant resistance against these stresses by strengthening the physical barriers, improving plant photosynthesis and activating plant defense mechanisms. The nanoparticles can also upregulate the expression of stress-related genes by increasing anti-stress compounds and activating the expression of defense-related genes. The unique physico-chemical characteristics of nanoparticles enhance biochemical activity and effectiveness to cause diverse impacts on plants. Molecular mechanisms of nanobiotechnology-induced tolerance to abiotic and biotic stresses have also been highlighted. Further research is needed on efficient synthesis methods, optimization of nanoparticle dosages, application techniques and integration with other technologies, and a better understanding of their fate in agricultural systems.

High-throughput vibrational spectroscopy methods for determination of degree of acetylation for chitin and chitosan.

The rising demand for chitin and chitosan in chemical, agro-food, and healthcare industries is creating a need for rapid and high-throughput analysis. The physicochemical properties of these biopolymers are greatly dependent on the degree of acetylation (DA). Conventional methods for DA determination, such as LC-MS and 1H NMR, are time-consuming when performed on many samples, and therefore efficient methods are needed. Here, high-throughput microplate-based FTIR and FT-Raman methods were compared with their manual counterparts. Partial least squares regression models were based on 30 samples of chitin and chitosan with reference DA values obtained by LC-MS and 1H NMR, and the models were validated on an independent test set of 16 samples. The overall predictive accuracy of the high-throughput methods was at the same level as the manual methods and the well-established LC-MS and 1H NMR methods. Therefore, high-throughput FTIR and FT-Raman DA determination methods have great potential to serve as fast and economical substitutes for traditional methods.

Analyzing the impact of access to electricity and biomass energy consumption on infant mortality rate: a global perspective.

Conserving the lives of newborns has been a long-standing issue around the world, where 2.4 million babies die in the first month of the life. The literature indicates that the important challenges of social development goals around the globe include affordable and easy access to electricity, promotion of sustainable economic development, and provision of better social services and creation of job opportunities which help in reducing infant mortality rate. This calls for the need to probe into this matter minutely and brings up the ways for reducing the infant mortality rate. The present study is an attempt to analyze the impact of rural and urban electrification and biomass energy consumption on infant mortality rate for the period 1990-2020 using the Panel Quantile Regression (PQR) approach. The results of the study show that in both developed and developing countries, biomass energy consumption has positive impact on infant mortality rate, while rural and urban electrification has proposed the inverted U-shaped relationship with infant mortality in different quantile groups. It is also concluded that few developing countries are failed to achieve the maturity of the inverted U-shaped curve while all developed countries have achieved at the maturity stage. This study recommended that for reducing the infant mortality rate, the world should discourage the use of biomass energy and promote the affordable and easy access to electricity on priority basis.

Exploring the moderating effect of globalization, financial development and environmental degradation nexus: a roadmap to sustainable development.

Financial development is a multidimensional process that contributes to economic growth but sometimes it has a devastating effect on climate change. No country can achieve sustainable development goals without caring the environmental quality. The present study investigates the moderating role of globalization (KOF) in determining the financial development (FD) on environmental degradation in the SAARC countries from 1990 to 2020. The long-run coefficients are estimated using the panel quantile regression (PQR) approach at lower, middle and upper quantile groups. The study shows the U-shaped relationship across three quantile groups based on financial development and carbon emissions. The moderator globalization (KOF) brings up the change in the turning point and flattens before the maturity of the U-shaped curve at the middle quantile while flattens after the maturity of the U-shaped curve at the upper quantile. The study recommends that by using energy-efficient technologies, better financial sector interaction with globalization enhances the environmental quality in SAARC countries.

Gene Ontology Capsule GAN: an improved architecture for protein function prediction.

Proteins are the core of all functions pertaining to living things. They consist of an extended amino acid chain folding into a three-dimensional shape that dictates their behavior. Currently, convolutional neural networks (CNNs) have been pivotal in predicting protein functions based on protein sequences. While it is a technology crucial to the niche, the computation cost and translational invariance associated with CNN make it impossible to detect spatial hierarchies between complex and simpler objects. Therefore, this research utilizes capsule networks to capture spatial information as opposed to CNNs. Since capsule networks focus on hierarchical links, they have a lot of potential for solving structural biology challenges. In comparison to the standard CNNs, our results exhibit an improvement in accuracy. Gene Ontology Capsule GAN (GOCAPGAN) achieved an F1 score of 82.6%, a precision score of 90.4% and recall score of 76.1%.

Revisiting the environmental impact of financial development on economic growth and carbon emissions: evidence from South Asian economies.

It is a global challenge to achieve sustainable economic growth by improving the environment. The present study discussed the role of the financial development sector in achieving sustainable economic growth and environmental quality in South Asian countries from 1990 to 2020 by controlling labour force participation, globalization, industrialization, and the education sector. A feasible generalized least squares (FGLS) panel data econometric technique has been used to check the relationship among the variables. The results show that financial development has a U-shaped relationship with carbon emissions and economic growth. Furthermore, labour force participation, industrialization, globalization, and educational school enrolment significantly increase CO2 and economic growth. This study suggests that the governments of South Asian countries should take steps to increase economic growth. For this purpose, effective supervisory mechanisms of financial development through financial innovation, improving financial efficiency, maintaining financial stability, and reducing the environmental pollution.

Trends and Limits for Quinoa Production and Promotion in Pakistan.

Quinoa is known as a super food due to its extraordinary nutritional qualities and has the potential to ensure future global food and nutritional security. As a model plant with halophytic behavior, quinoa has potential to meet the challenges of climate change and salinization due to its capabilities for survival in harsh climatic conditions. The quinoa crop has received worldwide attention due to its adoption and production expanded in countries out of the native Andean region. Quinoa was introduced to Pakistan in 2009 and it is still a new crop in Pakistan. The first quinoa variety was registered in 2019, then afterward, its cultivation started on a larger scale. Weed pressure, terminal heat stress, stem lodging, bold grain size, and an unstructured market are the major challenges in the production and promotion of the crop. The potential of superior features of quinoa has not been fully explored and utilized. Hence, there is a need to acquire more diverse quinoa germplasm and to establish a strong breeding program to develop new lines with higher productivity and improved crop features for the Pakistan market. Mechanized production, processing practices, and a structured market are needed for further scaling of quinoa production in Pakistan. To achieve these objectives, there is a dire need to create an enabling environment for quinoa production and promotion through the involvement of policymakers, research institutions, farmers associations, and the private sector.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach.

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.

Transportation moderation in agricultural sector sustainability - a robust global perspective.

The agriculture sector creates nearly a quarter of the total GHG emissions globally as production and transportation activities in the agriculture sector mostly use fossil fuels, creating carbon emissions. In this regard, it is highly important to study the environmental sustainability of agriculture sector growth by using the theory of environmental Kuznets curve (EKC). Furthermore, this research study is aimed to assess the moderation role of transportation competitiveness in determining the carbon emissions of transportation sector by using agriculture sector value addition. The study uses panel quantile regression technique for data analysis of 121 countries by covering time period from 2008 to 2018. The study results validated the agricultural EKC across four different quantile groups based on carbon emissions of transport sector. The moderation of transportation competitiveness is observed in changing the turning point and flattening of agricultural EKC indicating the early achievement of maturity. The quality of institutions and planned increase of population can help reduce carbon emissions of transportation sector. The moderation of transportation competitiveness implicates the importance of planning and efficiently operating the transportation sector to mitigate carbon emissions.

m6A-Finder: Detecting m6A methylation sites from RNA transcriptomes using physical and statistical properties based features.

N6-methyladenosine (m6A) is one of the abundant post-transcription modification in cellular RNA. It regulates different biological processes, such as, protein synthesis, X-chromosome inactivation, cell stability, cell-reprogramming and miRNA regulation etc. Most recently, various studies claimed that mutations in m6A sites are linked with various diseases, such as, brain-tumor, heart attack, obesity and cancer. The correct identification of m6A sites is essential to overcome these diseases. However, the state-of-the-art predictors face many challenges for precise detection of m6A sites. Even for model organisms, such as Saccharomyces cerevisiae, the detection of m6A sites is difficult due to complex patterns surrounding the m6A sites. These patterns are not widely understood and lead to non-discriminative features for detecting m6A sites. To overcome this problem, we propose a novel predictor called m6A-Finder that creates features based on global and local sequence order. The global sequence order is captured by physical properties based features, while the local sequence order is captured by the statistical features. The fusion of these features results in high dimensional vector which lead to over-fitting, to solve this problem, we use mRMR algorithm to remove redundant features. The proposed technique is evaluated on the most widely used Saccharomyces cerevisiae species dataset. Overall, the m6A-Finder achieved an accuracy of 82.02%, the sensitivity of 82.10%, specificity of 81.94% and a Matthew correlation coefficient value of +0.64.

Enriching Urea with Nitrogen Inhibitors Improves Growth, N Uptake and Seed Yield in Quinoa (Chenopodium quinoa Willd) Affecting Photochemical Efficiency and Nitrate Reductase Activity.

Quinoa is a climate resilience potential crop for food security due to high nutritive value. However, crop variable response to nitrogen (N) use efficiency may lead to affect grain quality and yield. This study compared the performance of contrasting quinoa genotypes (UAF Q-7, EMS-line and JQH1) to fertilizer urea enriched with urease and nitrification inhibitors (NIs; 1% (w/w) thiourea + boric acid + sodium thiosulphate), ordinary urea and with no N as control. Application of NIs-enriched urea improved plant growth, N uptake and chlorophyll values in quinoa genotype UAF-Q7 and JHQ1, however, highest nitrate reductase (NR) activity was observed in EMS-line. Quinoa plants supplied with NIs-enriched urea also completed true and multiple leaf stage, bud formation, flowering, and maturity stages earlier than ordinary urea and control, nevertheless, all quinoa genotypes reached true and multiple leaf stage, flowering and maturity stages at same time. Among photosynthetic efficiency traits, application of NIs-enriched urea expressed highest photosynthetic active radiations (PAR), electron transport rate (ETR), current fluorescence (Ft) and reduced quantum yield (Y) in EMS line. Nitrogen treatments had no significant difference for panicle length, however, among genotypes, UAF-Q7 showed highest length of panicle followed by others. Among yield attributes, NIs-enriched urea expressed maximum 1000-seed weight and seed yield per plant in JQH-1 hybrid and EMS-line. Likely, an increase in quinoa grain protein contents was observed in JQH-1 hybrid for NIs-enriched urea. In conclusion, NIs-enriched urea with urease and nitrification inhibitors simultaneously can be used to improve the N uptake, seed yield and grain protein contents in quinoa, however, better crop response was attributed to enhanced plant growth and photosynthetic efficiency.

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC). The optimal preprocessing was selected based on the quality of classification models established by partial least squares discriminant analysis for discriminating healthy and damaged cartilage samples. The best results for the sparse data were obtained by preprocessing using a baseline offset correction at 1800 cm-1, followed by peak normalization at 850 cm-1 and preprocessing by MSC.

Moderation of Services' EKC through Transportation Competitiveness: PQR Model in Global Prospective.

The continuously increasing GHG emissions have created environmental pollution and several challenges to ecosystems and biodiversity. The challenges of climate change are multipronged, resulting in melting glaciers, flash floods, and severe heat waves. In this regard, the adaptive and mitigation strategies to manage the consequences of climate change are highly important. The transport sector creates a quarter of carbon emissions, and this share is continuously increasing. Accordingly, this research study uses transport competitiveness to determine carbon emissions of the transport sector for 121 countries covering the time period from 2008 to 2018. The Panel Quantile Regression (PQR) technique is engaged to analyze the study results. The findings highlight that transport competitiveness tends to increase carbon emissions of the transport sector across quantile groups 1 and 3, while it reduces carbon emissions in quantile group 2. The U-shaped services' EKC is validated in quantile groups 2 and 4. The moderation engaged, i.e., transportation competitiveness, changes the turning point of the services' EKC across quantile groups 2 and 4. However, in the high-CO2 quantile group, the moderation impact of transport competitiveness is strongest as it reduces the sensitivity by flattening the services' EKC. Furthermore, the planned expansion of the population and improved institutional quality tend to mitigate carbon emissions across different quantile groups. The policy relevance/implications that are based on the study results/findings are made part of the research paper.

The Influence of Different Crop Mulches on Weed Infestation, Soil Properties and Productivity of Wheat under Conventional and Conservation Production Systems.

Pakistan and other South Asian countries rely on wheat for human nutrition. However, wheat yield is declining in the region due to several biotic and abiotic constraints. Weeds are among the major factors responsible for yield decrease and farmers manage them by intensive tillage practices. Several studies have investigated the impact of various tillage practices on weed management in wheat. However, weed suppression abilities of different mulch types are rarely tested. This three-year (2019-20, 2020-21 and 2021-22) study investigated the impact of different mulch types (prepared from different crops) on weed infestation, soil properties and productivity of wheat under conventional and conservation production systems at three locations (Multan, Hafizabad and Faisalabad) in Punjab, Pakistan. The mulches included in the study were cotton sticks mulch, mungbean straw mulch, sorghum straw mulch, rice straw mulch, sunflower straw mulch, plastic mulch, and no mulch (as control). The production systems opted for wheat cultivation were conventionally tilled wheat (CTW), zero-tilled wheat (ZTW) and zero-tilled wheat sown with happy seeder machine (HSW). The CTW resulted in the lowest soil bulk density and the highest soil porosity after wheat harvest, while ZTW behaved oppositely. Similarly, incorporation of crop mulches resulted in the highest soil porosity and the lowest soil bulk density, while no-mulch incorporation and plastic mulch recorded the highest bulk density and the lowest soil porosity. Regarding mulches by production systems' interaction, CTW with sorghum straw- and plastic mulches recorded the lowest weed density and biomass, while ZTW with no-mulch recorded the highest weed density and biomass at all locations. The CTW with mungbean straw- and plastic mulches resulted in the highest yield due to significant improvement in yield-related traits. However, ZTW with sorghum straw mulch and no-mulch resulted in the lowest wheat yield. Although sorghum straw mulch suppressed weed infestation, it negatively affected wheat growth. Economic analysis revealed that CTW with mungbean straw mulch resulted in the highest gross and net incomes and benefit:cost ratio (BCR), while the ZTW with rice straw- and sorghum straw mulches produced the lowest gross and net incomes and BCR at all locations. Therefore, mungbean straw mulch is a viable option to improve wheat productivity and net economic returns under different agro-climatic conditions of Punjab, Pakistan.