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Zaheri Abdehvand Z, Karimi D, Rangzan K, Mousavi SR. Assessment of soil fertility and nutrient management strategies in calcareous soils of Khuzestan province: a case study using the Nutrient Index Value method. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:503. [PMID: 38700640 DOI: 10.1007/s10661-024-12665-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 04/25/2024] [Indexed: 06/21/2024]
Abstract
Soil fertility (SF) is a crucial factor that directly impacts the performance and quality of crop production. To investigate the SF status in agricultural lands of winter wheat in Khuzestan province, 811 samples were collected from the soil surface (0-25 cm). Eleven soil properties, i.e., electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (TN), calcium carbonate equivalent (CCE), available phosphorus (Pav), exchangeable potassium (Kex), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn), and soil pH, were measured in the samples. The Nutrient Index Value (NIV) was calculated based on wheat nutritional requirements. The results indicated that 100%, 93%, and 74% of the study areas for CCE, pH, and EC fell into the low, moderate, and moderate to high NIV classes, respectively. Also, 25% of the area is classified as low fertility (NIV < 1.67), 75% falls under medium fertility (1.67 < NIV value < 2.33), and none in high fertility (NIV value > 2.33). Assessment of the mean wheat yield (AWY) and its comparison with NIV showed that the highest yield was in the Ramhormoz region (5200 kg.ha-1), while the lowest yield was in the Hendijan region (3000 kg.ha-1) with the lowest EC rate in the study area. Elevated levels of salinity and CCE in soils had the most negative impact on irrigated WY, while Pav, TN, and Mn availability showed significant effects on crop production. Therefore, implementing SF management practices is essential for both quantitative and qualitative improvement in irrigated wheat production in Khuzestan province.
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Affiliation(s)
- Zeinab Zaheri Abdehvand
- Department of Remote Sensing and GIS, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Danya Karimi
- Department of Remote Sensing and GIS, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
| | - Kazem Rangzan
- Department of Remote Sensing and GIS, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran
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Li X, Cao X, Wang H, Sun Y, Zhang S, Khodseewong S, Sakamaki T. The promotion of the atrazine degradation mechanism by humic acid in a soil microbial electrochemical system. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 357:120767. [PMID: 38560953 DOI: 10.1016/j.jenvman.2024.120767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/11/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024]
Abstract
The enhancing effects of anodes on the degradation of the organochlorine pesticide atrazine (ATR) in soil within microbial electrochemical systems (MES) have been extensively researched. However, the impact and underlying mechanisms of soil microbial electrochemical systems (MES) on ATR degradation, particularly under conditions involving the addition of humic acids (HAs), remain elusive. In this investigation, a soil MES supplemented with humic acids (HAs) was established to assess the promotional effects and mechanisms of HAs on ATR degradation, utilizing EEM-PARAFAC and SEM analyses. Results revealed that the maximum power density of the MES in soil increased by 150%, and the degradation efficiency of ATR improved by over 50% following the addition of HAs. Furthermore, HAs were found to facilitate efficient ATR degradation in the far-anode region by mediating extracellular electron transfer. The components identified as critical in promoting ATR degradation were Like-Protein and Like-Humic acid substances. Analysis of the microbial community structure indicated that the addition of HAs favored the evolution of the soil MES microbial community and the enrichment of electroactive microorganisms. In the ATR degradation process, the swift accumulation of Hydrocarbyl ATR (HYA) was identified as the primary cause for the rapid degradation of ATR in electron-rich conditions. Essentially, HA facilitates the reduction of ATR to HYA through mediated bonded electron transfer, thereby markedly enhancing the efficiency of ATR degradation.
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Affiliation(s)
- Xinyu Li
- School of Energy and Environment, Southeast University, Nanjing, 210096, China.
| | - Xian Cao
- School of Energy and Environment, Southeast University, Nanjing, 210096, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Hui Wang
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi, 710048, China.
| | - Yilun Sun
- School of Energy and Environment, Southeast University, Nanjing, 210096, China.
| | - Shuai Zhang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Sirapat Khodseewong
- Faculty of Public Health, Mahasarakham University, Maha Sarakham, 44150, Thailand.
| | - Takashi Sakamaki
- Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, Aoba Aramaki 6-6-06, Sendai, 980-8579, Japan.
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Zang M, Wang X, Chen Y, Faramarzi SE. Estimation of soil health in the semi‑arid regions of northwestern Iran using digital elevation model and remote sensing data. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:353. [PMID: 38466443 DOI: 10.1007/s10661-024-12527-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/05/2024] [Indexed: 03/13/2024]
Abstract
Nowadays, neglecting soil conservation issues is one of the most critical factors in reducing soil health (SH). In this regard, to facilitate the estimation of the SH in northwestern Iran, 292 soil samples were taken from a depth of 0-30 cm of this area, and a wide range of soil properties were determined. Then, soil health indices (SHIs) were calculated. Simultaneously, the normalized difference vegetation index (NDVI), surface water capacity index (SWCI), and a digital elevation model (DEM) were obtained from satellite data. Finally, multiple linear regression (MLR) relationships between these parameters and SHIs were calculated. In this study, there was a highest significant positive correlation (P < 0.01) between IHI-LTDS and SWCI (0.71**), DEM (0.76**), and NDVI (0.73**). The MLR, with both the whole total (TDS) and minimal (MDS) dataset methods, which includes the aforementioned indices, strongly described the spatial variability of the Integrated Soil Health Index (IHI) (R2 = 0.78, AIC = - 416, RMSE = 0.05, and ρc = 0.76). According to the results of this study, it can be said that the development of SH estimation models using remote sensing extracted parameters can be one of the effective ways to reduce the cost and time of soil sampling in extensive areas.
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Affiliation(s)
- Mingli Zang
- School of Science and Technology, Xinyang University, Xinyang, 464000, Henan, China.
| | - Xiaodong Wang
- School of Science and Technology, Xinyang University, Xinyang, 464000, Henan, China
| | - Yunling Chen
- School of Medicine, Huanghe College of Science and Technology, Zhengzhou, 450063, Henan, China
| | - Seyedeh Ensieh Faramarzi
- Department of Soil Science, Faculty of Agriculture and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran
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Zhang M, Khosravi Aqdam M, Abbas Fadel H, Wang L, Waheeb K, Kadhim A, Hekmati J. Evaluation of soil fertility using combination of Landsat 8 and Sentinel‑2 data in agricultural lands. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:131. [PMID: 38198078 DOI: 10.1007/s10661-024-12301-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/02/2024] [Indexed: 01/11/2024]
Abstract
Today, remote sensing is widely used to estimate soil properties. Because it is an easy and accessible way to estimate soil properties that are difficult to estimate in the field. Based on this, to evaluate the soil fertility (SF), soil sampling was performed irregularly from the surface depth of 0-30 cm in 216 points, 11 soil properties were measured, and the soil fertility index (SFI) was calculated by soil properties. Simultaneously, we combined satellite images of Landsat 8 and Sentinel-2 using the Gram-Schmidt algorithm. Finally, multiple linear regression SFI was calculated using satellite data, as well as the spatial distribution of SFI was obtained in very low, low, moderate, high, and very high classes. Our findings showed that the combination of Landsat 8 and Sentinel-2 data using the Gram-Schmidt algorithm has a higher correlation with SFI than when these data are individually. Therefore, combined Landsat 8 and Sentinel 2 data were used for SFI modeling. Using model selection procedure indices (including Cp, AIC, and ρc criteria), the visible range bands, notably blue (r = 0.65), green (r = 0.63), and red (r = 0.61), provide the best model for estimating SFI (R2 = 0.43, Cp = 3.34, AIC = -277.4, and ρc = 0.44). Therefore, these bands were used to estimate the SFI index. Also, the spatial distribution of the SIF index showed that the most significant area was related to the low class, and the lowest area belonged to the high and very high fertility classes. According to these results, it can be concluded that using the combination of Landsat 8 and Sentinel 2 bands to estimate soil fertility index in agricultural lands can increase the accuracy of soil fertility estimation.
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Affiliation(s)
- Ming Zhang
- Department of Resources and Environment, Anhui Vocational and Technological College of Forestry, Hefei, Anhui, 230031, China.
| | | | | | - Lei Wang
- Ministry of Ecology and Environment, Nanjing Institute of Environmental Sciences, Nanjing, 210042, China
| | - Khlood Waheeb
- Medical Technical College, Al-Farahidi University, Baghdad, Iraq
| | - Angham Kadhim
- Department of Optical Techniques, Al-Zahrawi University College, Karbala, Iraq
| | - Jamal Hekmati
- Department of Horticultural Sciencess, University Campus 2, University of Guilan, Rasht, Iran
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