Effect of animal manure, crop type, climate zone, and soil attributes on greenhouse gas emissions from agricultural soils A global meta-analysis

Agricultural lands, because of their large area and exhaustive management practices, have a substantial impact on the earth's carbon and nitrogen cycles, and agricultural activities consequence in discharges of greenhouse gases (GHGs). Globally, greenhouse gases (GHGs) emissions especially carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from the agricultural sector are increasing due to anthropogenic activities. Although, the application of animal manure to the agricultural soil as an organic fertilizer not only improves soil health and agricultural production but also has a significant impact on GHGs emissions. But the extent of GHGs emissions in response to manure application under diverse environmental conditions is still uncertain. Here, a meta-analysis study was conducted using field data (48 peer-reviewed publications) published from 1989 to 2019. Meta-analysis results showed that poultry manure considerably increased CO2, CH4, and N2O emissions than pig and cattle manure. Furthermore, application of poultry manure also increased (¯(〖lnRR〗^ ) =0.141, 95% CI =0.526-0.356) GWP (global warming potential) of total soil GHGs emissions. While, the significant effects on CO2, CH4, and N2O emissions also occurred at manure rate > 320 kg N ha-1 and > 60% water filled pore space. The maximum concentrations of CO2, CH4, and N2O emissions were observed in neutral soils (¯(〖lnRR〗^ ) =3.375, 95% CI =3.323-3.428), alkaline soils (¯(〖lnRR〗^ ) =1.468, 95% CI =1.403-1.532), and acidic soils (¯(〖lnRR〗^ ) =2.355, 95% CI =2.390-2.400), respectively. Soil texture, climate zone and crop type were also found significant factors to increase GHGs emissions. Thus, this meta-analysis revealed a knowledge gap concerning the consequences of animal manure application and rate, climate zone, and physicochemical properties of soil on GHGs emissions from agricultural soils.Awais Shakoor would like to express his gratitude for the grant provided by the University of Lleida, Spain. The authors would like to appreciate the valuable comments from the editors and anonymous reviewers to improve the quality of this study

Genome-wide identification and characterization of bZIP transcription factors and their expression profile under abiotic stresses in Chinese pear (Pyrus bretschneideri)

Background: In plants, basic leucine zipper transcription factors (TFs) play important roles in multiple biological processes such as anthesis, fruit growth & development and stress responses. However, systematic investigation and characterization of bZIP-TFs remain unclear in Chinese white pear. Chinese white pear is a fruit crop that has important nutritional and medicinal values. Results: In this study, 62 bZIP genes were comprehensively identified from Chinese Pear, and 54 genes were distributed among 17 chromosomes. Frequent whole-genome duplication (WGD) and dispersed duplication (DSD) were the major driving forces underlying the bZIP gene family in Chinese white pear. bZIP-TFs are classified into 13 subfamilies according to the phylogenetic tree. Subsequently, purifying selection plays an important role in the evolution process of PbbZIPs. Synteny analysis of bZIP genes revealed that 196 orthologous gene pairs were identified between Pyrus bretschneideri, Fragaria vesca, Prunus mume, and Prunus persica. Moreover, cis-elements that respond to various stresses and hormones were found on the promoter regions of PbbZIP, which were induced by stimuli. Gene structure (intron/exon) and different compositions of motifs revealed that functional divergence among subfamilies. Expression pattern of PbbZIP genes differential expressed under hormonal treatment abscisic acid, salicylic acid, and methyl jasmonate in pear fruits by real-time qRT-PCR. Conclusions: Collectively, a systematic analysis of gene structure, motif composition, subcellular localization, synteny analysis, and calculation of synonymous (Ks) and non-synonymous (Ka) was performed in Chinese white pear. Sixty-two bZIP-TFs in Chinese pear were identified, and their expression profiles were comprehensively analyzed under ABA, SA, and MeJa hormones, which respond to multiple abiotic stresses and fruit growth and development. PbbZIP gene occurred through Whole-genome duplication and dispersed duplication events. These results provide a basic framework for further elucidating the biological function characterizations under multiple developmental stages and abiotic stress responses.This work was performed at the school of Life Sciences, Anhui agricultural university, Hefei, China and was supported by National Natural Science Foundation of China (No. 31640068) and Natural Science Youth Foundation of Anhui Agricultural University (No. 2019zd01). These funding bodies had no role in the design of the study, collection, analysis, and interpretation of data or in writing the manuscript

Investigation of input and output energy for wheat production : a comprehensive study for Tehsil Mailsi (Pakistan)

The global increasing food demand can be met by efficient energy utilization in mechanized agricultural productions. In this study, input–output energy flow along with CO2 emissions for different wheat production cases (C-I to C-V) were investigated to identify the one that is most energy-efficient and environment-friendly case. Data and information about input and output sources were collected from farmers through questionnaires and face-to-face interviews. Input and output sources were converted into energy units by energy equivalents while CO2 emissions were calculated by emission equivalents. Data envelopment analysis (DEA) was conducted to compare technical efficiencies of the developed cases for optimization of inputs in inefficient cases. Results revealed that case C-Ⅴ (higher inputs, larger fields, the tendency of higher fertilizer application and tillage operations) has the highest energy inputs and outputs than the rest of the cases. Moreover, it possesses the lowest energy use efficiency and energy productivity. The highest CO2 emissions (1548 kg-CO2/ha) referred to C-Ⅴ while lowest emissions per ton of grain yield were determined in C-Ⅳ (higher electricity water pumping, moderate energy input). The grain yield increases directly with input energy in most of the cases, but it does not guarantee the highest values for energy indices. C-Ⅲ (moderate irrigations, educated farmers, various fertilizer applications) was found as an optimum case because of higher energy indices like energy use efficiency of 4.4 and energy productivity of 153.94 kg/GJ. Optimum input and better management practices may enhance energy proficiency and limit the traditionally uncontrolled CO2 emissions from wheat production. Therefore, the agricultural practices performed in C-Ⅲ are recommended for efficient cultivation of wheat in the studied area.The global increasing food demand can be met by efficient energy utilization in mechanized agricultural productions. In this study, input–output energy flow along with CO2 emissions for different wheat production cases (C-I to C-V) were investigated to identify the one that is most energy-efficient and environment-friendly case. Data and information about input and output sources were collected from farmers through questionnaires and face-to-face interviews. Input and output sources were converted into energy units by energy equivalents while CO2 emissions were calculated by emission equivalents. Data envelopment analysis (DEA) was conducted to compare technical efficiencies of the developed cases for optimization of inputs in inefficient cases. Results revealed that case C-Ⅴ (higher inputs, larger fields, the tendency of higher fertilizer application and tillage operations) has the highest energy inputs and outputs than the rest of the cases. Moreover, it possesses the lowest energy use efficiency and energy productivity. The highest CO2 emissions (1548 kg-CO2/ha) referred to C-Ⅴ while lowest emissions per ton of grain yield were determined in C-Ⅳ (higher electricity water pumping, moderate energy input). The grain yield increases directly with input energy in most of the cases, but it does not guarantee the highest values for energy indices. C-Ⅲ (moderate irrigations, educated farmers, various fertilizer applications) was found as an optimum case because of higher energy indices like energy use efficiency of 4.4 and energy productivity of 153.94 kg/GJ. Optimum input and better management practices may enhance energy proficiency and limit the traditionally uncontrolled CO2 emissions from wheat production. Therefore, the agricultural practices performed in C-Ⅲ are recommended for efficient cultivation of wheat in the studied area.King Saud University, Riyadh, Saudi Arabi

Performance Evaluation of Solar Cells by Different Simulating Softwares

In the contemporary era of technological advancements, solar energy emerges as a promising and easily implementable solution to meet future energy demands sustainably. This chapter delves into recent innovative techniques and simulation software pertaining to this environmentally friendly technology, focusing on device simulation, novel structures, and cutting-edge methods. A comparative analysis among major solar cell modeling simulators, such as PC1D, SCAPS-1D, wxAMPS-1D, AMPS-1D, ASA, Gpvdm, SETFOS, PECSIM, ASPIN, ADEPT, AFORS-HET, TCAD, and SILVACO ALTAS, is presented. These simulators not only aid in analyzing fabricated cells but also predict the impact of device modifications. The current year has witnessed significant efforts in developing sustainable energy systems through innovative solar cell simulators and semiconductor models. A concise evaluation of well-established solar cell simulators is provided to identify the most reliable tool for assessing photovoltaic technology performance. The chapter offers a user-friendly linear operating procedure and a congenial dialog box for multi-junction solar cells, providing valuable benefits for scientists, researchers, and skilled programmers in the photovoltaic community. This solar simulation software plays a crucial role in designing environment-friendly solar energy systems and calculating potential solar PV system outcomes for various projects, both grid-tied and off-grid, continually improving the solar energy technology landscape

Soft computing based feature selection for environmental sound classifcation

The topic of this thesis work is soft computing based feature selection for environmental sound classification. Environmental sound classification systems have a wide range of applications, like hearing aids devices, handheld devices and auditory protection devices. Sound classification systems typically extract features which are learnt by a classifier. Using too many features can result in reduced performance by making the learning algorithm to learn wrong models. The proper selection of features for sound classification is a non-trivial task. Soft computing based feature selection methods are not studied for environmental sound classification, whereas these methods are very promising, because these can handle uncertain information in a more ecient way, using simple set theoretic functions and because these methods are more close to perception based reasoning. Therefore this thesis investigates different feature selection methods, including soft computing based feature selection and classical information, entropy and correlation based approaches. Results of this study show that rough set neighborhood based method performs best in terms of number of features selected, recognition rate and consistency of performance. Also the resulting classification system performs robustly in presence of reverberation

Sustainable Development: Factors Influencing Public Intention towards Vertical Farming in China and Moderating Role of Awareness

Vertical farming brings an innovation in agriculture sector by improving production of food in optimized space within controlled environment without wastage of natural resources by using an automated technological system. It acquiring prominence around the world however incapable to accomplish goals, reason was lack of awareness, lack of public intention and participation towards vertical farming. This study filled the gap in prior literature and adding more creativity to influence public intention. The research used TPB to investigate the factors influencing public intention toward vertical farming and a moderating role of awareness. Data collected from Chinese consumers by convenience sampling technique, total 335 responses obtained and analyzed by using Structural Equation Model. The result of the study demonstrated that food safety and environmental concern are the best predictors of public intention towards vertical farming. Further awareness significantly strengthened the relationship between food safety concern and public intention. In the conclusion, study proposed appropriate recommendations to local government, stakeholders, urban planners, and food companies for the best practices to facilitate the successful implementation of vertical farming as sustainable for environment and health, which is also profitable business as public intention concurs

The FBK ASR system for Evalita 2011

Abstract. This report describes the system developed in FBK for participating in the Evalita 2011 evaluation campaign, providing some details on the techniques included in the transcription system

EXPLORING THE VERITY OF IDEALISTIC CONCEPTS IN THE NOVEL “A FAREWELL TO ARMS” BY EARNEST HEMINGWAY

By the time World War I (1914-1918) finally ended, 10 million people were expected to have died, and 20 million were wounded. The death of Archduke Franz Ferdinand of Austria-Hungary triggered the conflict in June 1914, but the causes of the dispute went further. A kind of strong patriotism flourished throughout Europe. Political power employed state individuals as well as colonized individuals through the basic workings of the belief system. Germany, France, and England have become huge capabilities through cash competitions all over the planet. Europe's interlocking royal groups formed remote federations and promised to favor one side in the conflict. Add to that the upcoming progressive battle in Russia, and each piece is primed for disaster. A four-year struggle ensued. Germany, Austria-Hungary, and the Ottoman Empire (mostly present-day Turkey) clashed against the Allies run by France, England, Russia, Italy, and eventually America. Ernest Hemingway’s novel, A Farewell to Arms depicts manipulation of the Ideological State Apparatus, that are glory, duty, honor, and obligation, how they work inside people, and how Oppressive State Apparatuses work against the people who understand the exploitation of ideology. From the perspective of postcolonial theory, this paper attempts to highlight the conspiracy of ideological weapon, which gives people the sense of self-betterment to initiate patriotism and nationalism in their mind, but this works only to take their service. &nbsp

Precision Nitrogen Management for Cotton Using (GreenSeeker) Handheld Crop Sensors

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 (Nreq) using (PNAR) G.S was determined through the nitrogen fertilizer optimization algorithm (NFOA). The Nreq 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