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3. EDCs exposure-induced alteration in the germination, growth, and physiological trait of the plant

Author

Saraswat, Anuj, primary, Ram, Shri, additional, Sharma, Sonal, additional, Chawla, Rukoo, additional, Khardia, Neha, additional, Chauhan, Deeksha, additional, Vishwakarma, Dinesh Kumar, additional, Raza, Md Basit, additional, Rajput, Vishnu D., additional, Dey, Prithwiraj, additional, Meena, Ram Swaroop, additional, and Behera, Biswaranjan, additional

Published
2024
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8. Environmental education for sustainable development

Author

Yadav, Shailesh Kumar, primary, Banerjee, Arnab, additional, Jhariya, Manoj Kumar, additional, Meena, Ram Swaroop, additional, Raj, Abhishek, additional, Khan, Nahid, additional, Kumar, Sandeep, additional, and Sheoran, Seema, additional

Published
2022
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10. Contributors

Author

Abhayapala, Ruvini, primary, Abhiram, Gunaratnam, additional, Acharya, Kamlesh K., additional, Adamczewska-Sowińska, Katarzyna, additional, Adeel, Muhammad, additional, Ahmad, Zahoor, additional, Ahmed, Sharif, additional, Ahmed, Mukhtar, additional, Akça, Erhan, additional, Alam, Mohammad Saiful, additional, Alvi, Sarosh, additional, Archangi, Azin, additional, Ashraf, Muhammad Irfan, additional, Athar, Tabinda, additional, Ayub, Muhammad Ashar, additional, Bamboriya, Shanti Devi, additional, Banerjee, Arnab, additional, Banerjee, Hirak, additional, Basit, Abdul, additional, Bedwal, Sandeep, additional, Behera, Biswaranjan, additional, Bhat, Shripad, additional, Bijani, Hemali, additional, Binagwa, Papias H., additional, Biswas, Jatish Chandra, additional, Boleta, Eduardo Henrique Marcandalli, additional, Büyük, Gökhan, additional, Carbonell-Bojollo, R.M., additional, Chakraborty, Somsubhra, additional, Chandana, Pebbeti, additional, Dahiya, Anupma, additional, Dev, Purushottam, additional, Domínguez-Núñez, José Alfonso, additional, Dutta, Sudarshan, additional, Eeswaran, Rasu, additional, Fikri-Benbrahim, Kawtar, additional, Filho, Marcelo Carvalho Minhoto Teixeira, additional, Garai, Sourav, additional, García-Tejero, I.F., additional, Gezgin, Sait, additional, Ghosh, Sarbaswarup, additional, Ginigaddara, G.A.S., additional, Goswami, Rupak, additional, Hamurcu, Mehmet, additional, Haque, M. Moynul, additional, Hariharan, Ganeshamoorthy, additional, Hayat, Rifat, additional, Heidari, Bahram, additional, Hossain, Akbar, additional, Hussain, Qaiser, additional, Islam, Md. Moshiul, additional, Jakhar, Shish Ram, additional, Jalal, Arshad, additional, Jangir, Chetan Kumar, additional, Jhariya, Manoj Kumar, additional, Jiménez, Oswalt R., additional, K.S., Aditya, additional, Kahraman, Abdullah, additional, Kamal, Mohammed Zia Uddin, additional, Karunarathna, Brintha, additional, Khalid, Rizwan, additional, Khan, Nahid, additional, Khan, Ayesha, additional, Khan, Khalid Saifullah, additional, Khan, Mohd. Kamran, additional, Kodithuwakku, A.N., additional, Kumar, Sandeep, additional, Kumar, Vikram, additional, Kumar, Ashok, additional, Kumar, Narender, additional, Kumar, Dinesh, additional, Kumari, Binita, additional, Kumari, Pritam, additional, Kumawat, Anita, additional, Kırpık, Muzaffer, additional, Lalotra, Shivani, additional, Lebrazi, Sara, additional, Loyal, Atul, additional, Maitra, Sagar, additional, Mandal, Subhasis, additional, Meena, Ram Swaroop, additional, Meena, Ajit Kumar, additional, Miah, Md. Giashuddin, additional, Minkina, Tatiana, additional, Mishra, Ajay Kumar, additional, Mishra, Manju Lata, additional, Mitra, Biplab, additional, Modi, Rajesh U, additional, Mondal, Mousumi, additional, Mrunalini, Kancheti, additional, Nayak, Jagamohan, additional, Oliveira, Carlos Eduardo da Silva, additional, Ordóñez-Fernández, R., additional, Pandey, Anamika, additional, Patnaik, Girija Prasad, additional, Piquet-Pissaloux, A., additional, Pradhan, Gourisankar, additional, Prasad, Saroj Kumar, additional, Punia, Himani, additional, R, Thribhuvan, additional, Rahman, Md. Mizanur, additional, Rahman, G.K.M. Mustafizur, additional, Raj, Abhishek, additional, Rajput, Vishnu D., additional, Ramtekey, Vinita, additional, Rani, Kavita, additional, Rani, Anju, additional, Rashid, Muhammad, additional, Rathi, Neelmani, additional, Ray, Krishnendu, additional, Riaz, Muhammad, additional, Rodríguez, B. Cárceles, additional, Rodríguez, M. Soriano, additional, Ruiz, B. Gálvez, additional, Saini, Manisha, additional, Saraswat, Anuj, additional, Sassi, Giovanna, additional, Sendhil, R., additional, Shabaan, Muhammad, additional, Shah, Tariq, additional, Shams, Zahra, additional, Shankar, Tanmoy, additional, Shariatipour, Nikwan, additional, Sharma, Sheetal, additional, Sharma, Pankaj, additional, Sheoran, Sindhu, additional, Sheoran, Seema, additional, Shukla, Uma Nath, additional, Singh, Ambuj Kumar, additional, Singh, Abhishek, additional, Sinha, Devi Dayal, additional, Solomon, Juan K.Q., additional, Sowiński, Józef, additional, Srivastava, Amit Kumar, additional, Tavira, S. Cuadros, additional, Thakur, Anjali, additional, Thakur, Praveen, additional, Umar, Wajid, additional, Yadav, Devideen, additional, Yeggina, Pavan Kumar, additional, Zakeel, Mohamed Cassim Mohamed, additional, Zia ur Rehman, Muhammad, additional, Zuazo, V.H. Durán, additional, Zuhra, Naqshe, additional, da Silva, André Luis Máximo, additional, de Torres, M.A. Repullo-Ruibérriz, additional, von Wettberg, Eric Bishop, additional, and İnan, Memet, additional

Published
2022
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14. Agroforestry a model for ecological sustainability

Author

Raj, Abhishek, primary, Jhariya, Manoj Kumar, additional, Banerjee, Arnab, additional, Meena, Ram Swaroop, additional, Nema, Sharad, additional, Khan, Nahid, additional, Yadav, Shailesh Kumar, additional, and Pradhan, Gourisankar, additional

Published
2022
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15. Species invasion and ecological risk

Author

Jhariya, Manoj Kumar, primary, Banerjee, Arnab, additional, Raj, Abhishek, additional, Meena, Ram Swaroop, additional, Khan, Nahid, additional, Kumar, Sandeep, additional, and Bargali, Surendra Singh, additional

Published
2022
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21. Contributors

Author

Abirami, S., primary, Adil, Muhammad Faheem, additional, Akhtar, Nishar, additional, Amanet, Khizer, additional, Ambastha, Vivek, additional, Anantharaju, K.S, additional, Anarna, Julieta A., additional, Anwar, Ali, additional, Athar, Habib-ur-Rehman, additional, Baby, S., additional, Baldodiya, Gajendra Mohan, additional, Banday, Saba, additional, Behera, Lopamudra, additional, Bisen, Kartikay, additional, Bisht, Jaideep Kumar, additional, Borah, Basanta Kumar, additional, Bose, Bandana, additional, Brown, Cristine Marie B., additional, Brown, Marilyn B., additional, Chandra, Ram, additional, Chitara, Manoj Kumar, additional, Çiğ, Arzu, additional, Danish, Subhan, additional, Das, Priyanka, additional, Datta, Diptanu, additional, Dwivedi, Padmanabh, additional, Erman, Murat, additional, Gade, R.M., additional, Gaur, R.K., additional, Gorain, Bisweswar, additional, Goyal, Vanshika, additional, Hidangmayum, Akash, additional, Hossain, Akbar, additional, Imran, Muhammad, additional, Iqbal, Muhammad Aamir, additional, Islam, Md. Sohidul, additional, Joshi, Naveen Chandra, additional, Kannan, Aarthy, additional, Kant, Lakshmi, additional, Kaur, Manmeet, additional, Kaur, Ravneet, additional, Keerthana, U., additional, Koche, Mina D., additional, Kohli, Isha, additional, Korra, Tulasi, additional, Kulvir, Singh, additional, Kumar, Gagan, additional, Kumar, Utkarsh, additional, Kumar, Vivek, additional, Kumar, Sumit, additional, Kumar, Sunil, additional, Kumari, Asha, additional, Kumawat, K.C., additional, Liyun, Liu, additional, Marwal, Avinash, additional, Meena, Ram Swaroop, additional, Mondal, Sananda, additional, More, Veena S., additional, More, Sunil S., additional, Mubeen, Muhammad, additional, Muthukumar, A., additional, Nagpal, Sharon, additional, Nair, Ajay, additional, Nanda, Satyabrata, additional, Naveen Kumar, R., additional, Nepomuceno, Robert A., additional, Panda, Debasish, additional, Pandey, Rachna, additional, Pandey, Anand Kumar, additional, Parihar, Manoj, additional, Paswan, Ricky Raj, additional, Perween, Shahina, additional, Prabhukarthikeyan, S.R., additional, Raj, T. Suthin, additional, Ram, Hanuman, additional, Rana, Kiran, additional, Rao, Archana S., additional, Rashid, Md. Mahtab, additional, Raza, Ali, additional, Raza, Muhammad Ali, additional, Sabagh, Ayman EL, additional, Saikia, Richita, additional, Sakthieaswari, P., additional, Shahnaz, Efath, additional, Sharma, Poonam, additional, Singh, Ankita, additional, Singh, Bansh Narayan, additional, Singh, U.B., additional, Singh, Shailendra, additional, Singh, Prashant Kumar, additional, Sodhi, H.S., additional, Sravani, Bana, additional, Sree Gayathri, S., additional, Srivastava, Akhilesh Kumar, additional, Sumiahadi, Ade, additional, Tiwari, Gopal, additional, Ueda, Akihiro, additional, Usha, C., additional, Varma, Ajit, additional, Verma, Shalja, additional, Wasaya, Allah, additional, Yashu, Bhudeo Rana, additional, and Yasir, Tauqeer Ahmad, additional

Published
2022
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22. Preface

Author

Jhariya, Manoj Kumar, primary, Meena, Ram Swaroop, additional, Banerjee, Arnab, additional, and Meena, Surya Nandan, additional

Published
2022
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24. Residual nitrogen for succeeding crops in legume-based cropping system

Author

Jangir, Chetan Kumar, primary, Thakur, Anjali, additional, Bijani, Hemali, additional, Thakur, Praveen, additional, Kumar, Sandeep, additional, Meena, Ram Swaroop, additional, Bedwal, Sandeep, additional, Rani, Kavita, additional, Shukla, Uma Nath, additional, Meena, Ajit Kumar, additional, and Dev, Purushottam, additional

Published
2022
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25. Prospects of beneficial microbes as a natural resource for sustainable legumes production under changing climate

Author

Sabagh, Ayman EL, primary, Islam, Md. Sohidul, additional, Hossain, Akbar, additional, Iqbal, Muhammad Aamir, additional, Imran, Muhammad, additional, Raza, Ali, additional, Çiğ, Arzu, additional, Wasaya, Allah, additional, Yasir, Tauqeer Ahmad, additional, Sumiahadi, Ade, additional, Amanet, Khizer, additional, Mubeen, Muhammad, additional, Kulvir, Singh, additional, Meena, Ram Swaroop, additional, Athar, Habib-ur-Rehman, additional, Danish, Subhan, additional, Adil, Muhammad Faheem, additional, Raza, Muhammad Ali, additional, Ueda, Akihiro, additional, Liyun, Liu, additional, and Erman, Murat, additional

Published
2022
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26. Legumes for nutrient management in the cropping system

Author

Hossain, Akbar, primary, Maitra, Sagar, additional, Ahmed, Sharif, additional, Mitra, Biplab, additional, Ahmad, Zahoor, additional, Garai, Sourav, additional, Mondal, Mousumi, additional, Adeel, Muhammad, additional, Shankar, Tanmoy, additional, and Meena, Ram Swaroop, additional

Published
2022
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29. Agriculture models for restoring degraded land to enhance CO 2 biosequestration and carbon credits in the Vindhyan region of India.

Author

Meena RS, Pradhan G, Singh K, Kumar S, Singh AK, Shashidhar KS, Mina KK, and Rao CS

Abstract

The study's objective was to evaluate the status of converted degraded land into productive agricultural models by improving the physicochemical properties of the soil, soil organic matter (SOM), soil organic carbon (SOC) fractions (active and passive), and microbial biomass carbon (MBC), while also generating carbon (C) credit for additional farmers' income. Six models were analyzed, namely: (1) Arjun forest-based agroecosystems (AFBAE); (2) Lemon grass-based agroecosystems (LGBAE); (3) Legume-cereal-moong-based agroecosystems (LCMBAE); (4) Bael-black mustard-based agroecosystems (BMBAE); (5) Guava-wheat-based agroecosystems (GWBAE), and (6) Custard apple -lentil -based agroecosystems (CALBAE). These models were replicated three times in a randomized block design (RBD). Soil samples were collected from the study area at two depths (0-0.30 and 0.30-0.60 m). At a 0-0.30 m depth, the highest bulk density (ρb) of 1.50 Mg m -3 was observed in LCMBAE, while the lowest ρb of 1.43 Mg m -3 was recorded in BMBAE. The soil organic carbon (SOC) and SOC stock values exhibited a range of 4.2-7.7 g kg -1 and 19.0-33.4 Mg ha -1 , respectively. In the AFBAE, the highest levels of 163.1 % MBC were found over LCMBAE. At a 0-0.30 m depth, the recalcitrant index (RI) and lability index (LI) ranged from 0.35-0.46 to 1.97-2.11, respectively. Additionally, the AFBAE exhibited the highest total biomass accumulation (39.23 Mg ha -1 ), carbon dioxide (CO 2 ) biosequestration (287.9 Mg ha -1 ), and the total social cost of CO 2 at US$ 277 ha -1 . Furthermore, in the AFBAE, there was a 198.1 % increase in total C credit (US$ 161 ha -1 ) compared to LCMBAE (US$ 54 ha -1 ). However, at 0.30-0.60 m depths, GWBAE and CALBAE were statistically equivalent (p ≤ 0.05) in total C stocks. Principal component analysis (PCA) reveals that component-1 accounts for 77.4 % of the variability, while component-2 contributes 18.6 %. This article aimed to convert the degraded land into a sustainable agricultural module by increasing SOC and CO 2 biosequestration and producing more C-credit, or climate currency, on underutilized land., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests/personal relationships that could have appeared to influence the research work reported in this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Published
2024
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30. Industrial garbage-derived biocompost enhances soil organic carbon fractions, CO 2 biosequestration, potential carbon credits and sustainability index in a rice-wheat ecosystem.

Author

Meena RS and Pradhan G

Subjects
Triticum, Carbon, Carbon Dioxide, Ecosystem, Agriculture methods, Fertilizers analysis, Nitrogen analysis, Soil, Oryza
Abstract

The objectives of this experiment were i) to study on the garbage composting to improve the soil organic carbon (SOC) pools (active and passive), ii) work out the carbon (C) budgeting, and iii) cut off C footprints (CFs) in the rice (Oryza sativa L.)-wheat (Triticum aestivum L.) farming to achieve the long-term sustainability. The main plots show four fertilizer levels (F0 = control, F1 = 112.5:45:45 kg nitrogen; phosphorus; potassium (NPK) ha -1 , F2 = 150:60:60 kg NPK ha -1 and F3 = 150:60:60 kg NPK ha -1 + 5 kg iron (Fe) + 5 kg zinc (Zn) were applied, while in sub plots with the combination of three industrial garbage (I1 = carpet garbage; I2 = pressmud; I3 = bagasse) and three microbial culture (M1 = Pleurotus sajor-caju, M2 = Azotobacter chroococcum; M3 = Trichoderma viride) made into nine treatment combinations were applied. Based on the interaction, treatment F3 × I1+M3 resulted in a maximum of 25.1 and 22.4 Mg ha -1 total CO 2 biosequestration by rice and wheat, respectively. However, it was cut off CFs by 29.9 and 22.2% more than F1 × I3+M1. Based on the soil C fractionation study, in the main plot treatment, F3 was active very labile C (VLC) and moderately labile C (MLC) and passive less labile C (LLC) and recalcitrant C (RC) SOC fractions contributed by 68.3 and 30.0%, respectively, of total SOC. However, in the sub plot, treatment I1+M3 found 68.2% and 29.8% active and passive SOC fractions, respectively, of total SOC. Regarding the soil microbial biomass C (SMBC) study, F3 had 37.7% higher than F0. However, in the sub plot, I1+M3 was seen to be 21.5% greater than I2+M1. Furthermore, wheat and rice had higher 1002 and 897 US$ ha -1 potential C credit in F3 × I1+M3, respectively. SOC fractions were perfectly positively correlated with SMBC. A positive (+) correlation was observed among grain yield (wheat and rice) and SOC pools in soil. However, a negative correlation was found between the C sustainability index (CSI) and greenhouse gas intensity (GHGI). The variability in wheat and rice grain yield was 46 and 74%, respectively, contributed by the SOC pools. Therefore, this study hypothesised that applying inorganic nutrients and industrial garbage converted into biocompost cut off C emissions and reduced the demand for chemical fertilizers, opening garbage disposal, and simultaneously enhancing the SOC pools., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Published
2023
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31. Utilizing waste compost to improve the atmospheric CO 2 capturing in the rice-wheat cropping system and energy-cum‑carbon credit auditing for a circular economy.

Author

Pradhan G and Meena RS

Abstract

The study aimed to manage industrial wastes and create a module for using compost from waste for crops cultivation to conserve energy, reduce fertilizer use and Greenhouse gas (GHG) emissions, and improve the atmospheric CO 2 capturing in agriculture for a green economy. In the main-plot, the experiment's results using NS3 found 50.1 and 41.8 % more grain yield and total carbon dioxide (CO 2 ) sequestration in the wheat-rice cropping sequence, respectively, compared to the NS0. Moreover, the treatment CW + TV in the sub-plot observed 24.0 and 20.3 % higher grain yield and total CO 2 sequestration than B + PS. Based on interaction, the NS3× CW + TV resulted in a maximum total CO 2 sequestration and C credit of 47.5 Mg ha -1 and US$ 1899 ha -1 , respectively. Further, it was 27.9 % lower in carbon footprints (CFs) than NS1 × B + PS. Regarding another parameter, the treatment NS3 observed a 42.4 % more total energy output in the main-plot than that of NS0. Further, in the sub-plot, the treatment CW + TV produced 21.3 % more total energy output than B + PS. Energy use efficiency (EUE) and net energy return in the interaction of NS3× CW + TV were 20.5 and 138.8 % greater than the NS0 × B + PS, respectively. In the main-plot, the treatment NS3 obtained a maximum of 585.0 MJ US$ -1 and US$ 0.24 MJ -1 for energy intensity in economic terms (EIET) and eco-efficiency index in terms of energy (EEIe), respectively. While in the sub-plot, the CW + TV was observed at a maximum of 571.52 MJ US$ -1 and US$ 0.23 MJ -1 EIET and EEIe, respectively. The correlation and regression study showed a perfect positive correlation between grain yield and total C output. Moreover, a high positive correlation (0.75 to 1) was found with all other energy parameters for grain energy use efficiency (GEUE). The variability in the wheat-rice cropping sequence's energy profitability (EPr) was 53.7 % for human energy profitability (HEP). Based on principal component analysis (PCA), the eigenvalues of the first two principal components (PCs) had been greater than two, explaining 78.4 and 13.7 % of the variability. The experiment hypothesis was to develop a reliable technology for safely using industrial waste compost, minimizing energy consumption and CO 2 emissions by reducing chemical fertilizer input in agriculture soils., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests/personal relationships that could have appeared to influence the research work reported in this manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Published
2023
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32. Application of analytical hierarchical process, multi-influencing factor, and geospatial techniques for groundwater potential zonation in a semi-arid region of western India.

Author

Yadav B, Malav LC, Jangir A, Kharia SK, Singh SV, Yeasin M, Nogiya M, Meena RL, Meena RS, Tailor BL, Mina BL, Alhar MSO, Jeon BH, Cabral-Pinto MMS, and Yadav KK

Subjects
India, Environmental Monitoring methods, Geographic Information Systems, Analytic Hierarchy Process, Groundwater
Abstract

Groundwater resources are alarmingly depleting due to over-exploitation and significant climate changes over time. Therefore, demarcation of groundwater potential zones is essential for addressing the needs of various industries in semi-arid area. Depleting groundwater resources, topography, aquifer features and climatic factors make it necessary to demarcate ground water potential zones in semiarid region of Rajasthan. The Analytical Hierarchy Process (AHP), Geographic Information System (GIS), and Multi Influence Factor (MIF) were used to determine the groundwater potential zones (GWPZs) in the semi-arid region of Jaipur, located in western Rajasthan. In present study, ten influential factors were employed i.e., geomorphology, land use/land cover (LULC), drainage density, rainfall, topographic wetness index (TWI), soil texture, slope, roughness, topographic position index (TPI) and curvature. In AHP technique, the pairwise comparison matrix was generated, and weightages were given to each thematic layer while for MIF, a proposed score for each layer was computed from the aggregate weight of major and minor effects. The GWPZ map generated by AHP technique was categorised into three parts: high, moderate and poor potential zones, covering 13%, 50.7% and 36.3% of the district. While, the GWPZ map produced with the MIF technique was also divided into the same poor, moderate, and high categories, encompassing 35.3, 44.1, and 20.6% of the district, respectively. The results of AHP and MIF techniques were then cross-validated with well depth data obtained from CGWB report, 2019-20. The receiver operating characteristics (ROC) were plotted and the findings shows that the Area under the Curve (AUC) was 79% and 76% for AHP and MIF, respectively which is considered as moderate to high in predictive precision. The study would be helpful in locating drilling sites for groundwater exploration and developing sustainable groundwater and land use policies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Published
2023
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