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In order to solve the problem of large image noise and unremarkable features caused by factors such as fluctuations in the power of a light source during the terahertz image acquisition of wheat, this paper proposes a THz image-denoising model called G-RRDB. Firstly, a module called Ghost-LKA is proposed by combining a large kernel convolutional attention mechanism module with a Ghost convolutional structure, which improves the characteristics of the network to acquire a global sensory field. Secondly, by integrating a spatial attention mechanism with channel attention, an attention module called DAB is proposed to enhance the network's attention to important features. Thirdly, the Ghost-LKA module and DAB module are combined with the baseline model, thus proposing the dense residual denoising network G-RRDB. Compared with traditional denoising networks, both the PSNR and SSIM are improved. The prediction accuracy of G-RRDB is verified through the classification of the VGG16 network, achieving a rate of 92.8%, which represents an improvement of 1.7% and 0.2% compared to the denoised images obtained from the baseline model and the combined baseline model with the DAB module, respectively. The experimental results demonstrate that G-RRDB, a THz image-denoising model based on dense residual structure for moldy wheat, exhibits excellent denoising performance. [ABSTRACT FROM AUTHOR]

Aims: Rice cultivation plays a significant role in greenhouse gas emissions, particularly nitrous oxide (N2O) emissions. Although the effects of upland and flooded rice cultivation on soil N2O emissions have been reported, scholars have not comparatively investigated the mechanism underlying N2O emissions during the rice cultivation seasons of rice-based rotation systems.Herein, a two-year field experiment including two rice cultivation modes, namely, conventional upland rice–rapeseed (UL-R) and flooded rice–rapeseed (FL-R) rotations, was conducted to determine the effect of different rice plantation models on soil N2O emissions in Central China. Non-rice treatments (UL-B and FL-B) during the rice season were also implemented to confirm the effect of rice plantation or soil condition on N2O emissions.Seasonal N2O emissions were higher in UL-R rotation than in FL-R rotation (1.54 ± 0.16 vs. 0.71 ± 0.20 and 2.57 ± 0.28 vs. 0.76 ± 0.04 kg N ha−1 for the first and following rice cultivation seasons, respectively). Also, N2O emissions were higher in UL-B treatment than that in FL-B treatment during both rice seasons (2.45 ± 0.07 vs. 1.43 ± 0.35 and 3.74 ± 0.37 vs. 1.16 ± 0.08 kg N ha−1, respectively). The yield-based N2O emissions were higher in the UL model than in the FL model (0.21 ± 0.01 vs. 0.10 ± 0.02 and 0.34 ± 0.03 vs. 0.11 ± 0.01 kg N ha−1, respectively). The responses of N2O emission fluxes to soil ammonium (NH4+) and dissolved organic carbon (DOC) in UL rotation were stronger than those in FL rotation. Furthermore, total N2O emissions from non-rice treatments were higher than those from rice-cultivated treatments for both rice-based rotations. The increase in N2O emissions in UL-B treatment could be attributed to the higher abundance of amoA gene and elevated soil mineral nitrogen content compared to UL-R treatment. The higher amount of N2O generated in FL-B treatment than that in FL-R treatment was ascribed to the increased abundance of the nirS gene and the decreased abundance of the nosZ gene. The structural equation model supported that soil moisture, temperature, available C and N, and ammonium oxidation-related functional genes explained more than 70% of the effect on soil N2O emissions in UL rotation. Meanwhile, soil moisture, temperature, available N, and denitrification-related functional genes explained 80% of the effect in FL rotation. Our results highlight that the response of N2O emissions mainly relies on soil available N and C and critical functional genes, which may contribute to improve the understanding for N2O mitigation strategies.These findings highlight the importance of rice plantation and their contribution to decreased field N2O emission, and suggest that soil available C, N, and critical functional genes should be considered when investigating N2O mitigation pathways during rice cultivation seasons.Methods: Rice cultivation plays a significant role in greenhouse gas emissions, particularly nitrous oxide (N2O) emissions. Although the effects of upland and flooded rice cultivation on soil N2O emissions have been reported, scholars have not comparatively investigated the mechanism underlying N2O emissions during the rice cultivation seasons of rice-based rotation systems.Herein, a two-year field experiment including two rice cultivation modes, namely, conventional upland rice–rapeseed (UL-R) and flooded rice–rapeseed (FL-R) rotations, was conducted to determine the effect of different rice plantation models on soil N2O emissions in Central China. Non-rice treatments (UL-B and FL-B) during the rice season were also implemented to confirm the effect of rice plantation or soil condition on N2O emissions.Seasonal N2O emissions were higher in UL-R rotation than in FL-R rotation (1.54 ± 0.16 vs. 0.71 ± 0.20 and 2.57 ± 0.28 vs. 0.76 ± 0.04 kg N ha−1 for the first and following rice cultivation seasons, respectively). Also, N2O emissions were higher in UL-B treatment than that in FL-B treatment during both rice seasons (2.45 ± 0.07 vs. 1.43 ± 0.35 and 3.74 ± 0.37 vs. 1.16 ± 0.08 kg N ha−1, respectively). The yield-based N2O emissions were higher in the UL model than in the FL model (0.21 ± 0.01 vs. 0.10 ± 0.02 and 0.34 ± 0.03 vs. 0.11 ± 0.01 kg N ha−1, respectively). The responses of N2O emission fluxes to soil ammonium (NH4+) and dissolved organic carbon (DOC) in UL rotation were stronger than those in FL rotation. Furthermore, total N2O emissions from non-rice treatments were higher than those from rice-cultivated treatments for both rice-based rotations. The increase in N2O emissions in UL-B treatment could be attributed to the higher abundance of amoA gene and elevated soil mineral nitrogen content compared to UL-R treatment. The higher amount of N2O generated in FL-B treatment than that in FL-R treatment was ascribed to the increased abundance of the nirS gene and the decreased abundance of the nosZ gene. The structural equation model supported that soil moisture, temperature, available C and N, and ammonium oxidation-related functional genes explained more than 70% of the effect on soil N2O emissions in UL rotation. Meanwhile, soil moisture, temperature, available N, and denitrification-related functional genes explained 80% of the effect in FL rotation. Our results highlight that the response of N2O emissions mainly relies on soil available N and C and critical functional genes, which may contribute to improve the understanding for N2O mitigation strategies.These findings highlight the importance of rice plantation and their contribution to decreased field N2O emission, and suggest that soil available C, N, and critical functional genes should be considered when investigating N2O mitigation pathways during rice cultivation seasons.Results: Rice cultivation plays a significant role in greenhouse gas emissions, particularly nitrous oxide (N2O) emissions. Although the effects of upland and flooded rice cultivation on soil N2O emissions have been reported, scholars have not comparatively investigated the mechanism underlying N2O emissions during the rice cultivation seasons of rice-based rotation systems.Herein, a two-year field experiment including two rice cultivation modes, namely, conventional upland rice–rapeseed (UL-R) and flooded rice–rapeseed (FL-R) rotations, was conducted to determine the effect of different rice plantation models on soil N2O emissions in Central China. Non-rice treatments (UL-B and FL-B) during the rice season were also implemented to confirm the effect of rice plantation or soil condition on N2O emissions.Seasonal N2O emissions were higher in UL-R rotation than in FL-R rotation (1.54 ± 0.16 vs. 0.71 ± 0.20 and 2.57 ± 0.28 vs. 0.76 ± 0.04 kg N ha−1 for the first and following rice cultivation seasons, respectively). Also, N2O emissions were higher in UL-B treatment than that in FL-B treatment during both rice seasons (2.45 ± 0.07 vs. 1.43 ± 0.35 and 3.74 ± 0.37 vs. 1.16 ± 0.08 kg N ha−1, respectively). The yield-based N2O emissions were higher in the UL model than in the FL model (0.21 ± 0.01 vs. 0.10 ± 0.02 and 0.34 ± 0.03 vs. 0.11 ± 0.01 kg N ha−1, respectively). The responses of N2O emission fluxes to soil ammonium (NH4+) and dissolved organic carbon (DOC) in UL rotation were stronger than those in FL rotation. Furthermore, total N2O emissions from non-rice treatments were higher than those from rice-cultivated treatments for both rice-based rotations. The increase in N2O emissions in UL-B treatment could be attributed to the higher abundance of amoA gene and elevated soil mineral nitrogen content compared to UL-R treatment. The higher amount of N2O generated in FL-B treatment than that in FL-R treatment was ascribed to the increased abundance of the nirS gene and the decreased abundance of the nosZ gene. The structural equation model supported that soil moisture, temperature, available C and N, and ammonium oxidation-related functional genes explained more than 70% of the effect on soil N2O emissions in UL rotation. Meanwhile, soil moisture, temperature, available N, and denitrification-related functional genes explained 80% of the effect in FL rotation. Our results highlight that the response of N2O emissions mainly relies on soil available N and C and critical functional genes, which may contribute to improve the understanding for N2O mitigation strategies.These findings highlight the importance of rice plantation and their contribution to decreased field N2O emission, and suggest that soil available C, N, and critical functional genes should be considered when investigating N2O mitigation pathways during rice cultivation seasons.Conclusions: Rice cultivation plays a significant role in greenhouse gas emissions, particularly nitrous oxide (N2O) emissions. Although the effects of upland and flooded rice cultivation on soil N2O emissions have been reported, scholars have not comparatively investigated the mechanism underlying N2O emissions during the rice cultivation seasons of rice-based rotation systems.Herein, a two-year field experiment including two rice cultivation modes, namely, conventional upland rice–rapeseed (UL-R) and flooded rice–rapeseed (FL-R) rotations, was conducted to determine the effect of different rice plantation models on soil N2O emissions in Central China. Non-rice treatments (UL-B and FL-B) during the rice season were also implemented to confirm the effect of rice plantation or soil condition on N2O emissions.Seasonal N2O emissions were higher in UL-R rotation than in FL-R rotation (1.54 ± 0.16 vs. 0.71 ± 0.20 and 2.57 ± 0.28 vs. 0.76 ± 0.04 kg N ha−1 for the first and following rice cultivation seasons, respectively). Also, N2O emissions were higher in UL-B treatment than that in FL-B treatment during both rice seasons (2.45 ± 0.07 vs. 1.43 ± 0.35 and 3.74 ± 0.37 vs. 1.16 ± 0.08 kg N ha−1, respectively). The yield-based N2O emissions were higher in the UL model than in the FL model (0.21 ± 0.01 vs. 0.10 ± 0.02 and 0.34 ± 0.03 vs. 0.11 ± 0.01 kg N ha−1, respectively). The responses of N2O emission fluxes to soil ammonium (NH4+) and dissolved organic carbon (DOC) in UL rotation were stronger than those in FL rotation. Furthermore, total N2O emissions from non-rice treatments were higher than those from rice-cultivated treatments for both rice-based rotations. The increase in N2O emissions in UL-B treatment could be attributed to the higher abundance of amoA gene and elevated soil mineral nitrogen content compared to UL-R treatment. The higher amount of N2O generated in FL-B treatment than that in FL-R treatment was ascribed to the increased abundance of the nirS gene and the decreased abundance of the nosZ gene. The structural equation model supported that soil moisture, temperature, available C and N, and ammonium oxidation-related functional genes explained more than 70% of the effect on soil N2O emissions in UL rotation. Meanwhile, soil moisture, temperature, available N, and denitrification-related functional genes explained 80% of the effect in FL rotation. Our results highlight that the response of N2O emissions mainly relies on soil available N and C and critical functional genes, which may contribute to improve the understanding for N2O mitigation strategies.These findings highlight the importance of rice plantation and their contribution to decreased field N2O emission, and suggest that soil available C, N, and critical functional genes should be considered when investigating N2O mitigation pathways during rice cultivation seasons. [ABSTRACT FROM AUTHOR]

Aims: Nitrogenous fertilizer has been recognized as a key factor regulating nitrous oxide (N2O) emissions from agricultural soils. However, the effect of nitrogen (N) fertilization of preceding season on soil N2O emission in subsequent season remain poorly understood. Methods: Herein, a field-based study was done to examine the effect of prior N fertilization on N2O emissions under a rapeseed-rice rotation (RR) system in central China. Treatments were as follows: no N fertilizer was applied in both rapeseed and rice-growing seasons (N0-0), N fertilizer (150 kg N ha−1 y−1) was only applied during rapeseed-growing season (N150-0,), N fertilizer (150 kg N ha−1 y−1) was applied in both rapeseed and rice-growing seasons (N150-150), and N fertilizer (150 kg N ha−1 y−1) was only applied during rice-growing season (N0-150). Soil N2O fluxes and the key soil factors (soil available C and N and their ratios, soil temperature and moisture) that further drive N2O emissions were determined after N fertilization in preceding and subsequent seasons. Results: The application of N fertilizer during the rapeseed-growing season caused a significant increase in soil N2O emission from rice-growing season, but no such promotion effect was observed during rapeseed growing season due to N fertilization during prior rice season. Higher N2O emission from rapeseed-growing season, after N fertilization was attributed to high soil mineral nitrogen content (including NH4+-N and NO3−-N). N2O efflux was higher when dissolved organic carbon (DOC) to NO3− content ratio (DOC/NO3−) was < 0.5 but lower when DOC/NO3− ratio was > 0.5 for both N150-0 and N150-150 treatments. Pulse N2O emission during the rice-growing period was observed due to higher soil DOC content derived from soil organic matter decomposition. The positive correlation between soil N2O fluxes and DOC/NO3− ratio for both N150-150 and N0-150, also revealed that soil available carbon to nitrogen ratio could be a crucial factor regulating peaks of N2O during the rice season. Structural equation model (SEM) displayed the explanation of impact factors on N2O emission was 62% during the rapeseed-growing season, while that explanation was 45% during the rice-growing season. Conclusions: These results showed that not only labile C and N content, but also soil DOC/NO3−, influenced by prior N fertilization, play a key role in soil N2O emissions under the RR system. [ABSTRACT FROM AUTHOR]

A highly stable amino-coordinated metal–organic framework ZJU-198 has been synthesized and structurally characterized, exhibiting high CO2 uptake of 105.8 cm3 cm−3 while blocking off N2 adsorption at 1.0 bar and 298 K, attributed to the unique pore window sizes. [ABSTRACT FROM AUTHOR]

The traditional detection of impurities in wheat has difficulties such as low precision, time-consuming, and cumbersome, therefore, it is important to study the method of rapid and accurate detection of impurities in wheat for correctly assessing the quality grade of wheat. Terahertz (THz) technology has many superior properties such as transient, broadband, low-energy, and penetrating, which can realize rapid and nondestructive detection of wheat quality. In this study, a classification and recognition algorithm AHA-RetinaNet-X for wheat impurity terahertz images based on RetinaNet and Artificial hummingbird algorithm (AHA) is proposed.A THz three-dimensional tomography imaging system is used to image wheat and its impurities, and two THz image datasets, respectively the wheat and impurity dataset for verifying the classification effect of wheat and impurities and the impurity dataset for verifying the classification effect of impurities. The experimental results show that the AHA-RetinaNet-X model outperforms other detection and classification models in terms of accuracy, F1-score, precision, recall, and specificity, and is able to achieve 96.1%, 94.9%, 95.2%, 95.8%, 95.5%, 95.3%, and 93.3% for the wheat and impurity dataset and the impurity dataset, respectively, 95.6%, 96.3%, and 95.2%, and the mAP value of AHA-RetinaNet-X is also higher than the other models and can reach 92.1%. The combination of THz imaging technology and AHA-RetinaNet-X can realize the classification and identification of wheat and impurities, which provides a new method for the non-contact rapid nondestructive detection and identification of wheat and impurities, and also provides a reference for the research of the identification and detection methods of other substances., 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 © 2024 Elsevier B.V. All rights reserved.)

The separation of carbon dioxide (CO 2 ) from hydrocarbons is a critical process for the production of clean energy and high-purity chemicals. Adsorption based on molecular sieving is an energy-saving separation process; however, most of molecular sieves with narrow and straight pore channels exhibit low CO 2 uptake capacity. Here, we report that a twofold interpenetrated copper coordination network with a consecutive pocket-like pore structure, namely, SIFSIX-14-Cu-i (SIFSIX = hexafluorosilicate, 14 = 4,4'-azopyridine, i = interpenetrated) is a remarkable CO 2 /CH 4 molecular sieving adsorbent which completely blocks the larger CH 4 molecule with unprecedented selectivity, whereas it has excellent CO 2 uptake (172.7 cm 3 /cm 3 ) under the ambient condition. The exceptional separation performance of SIFSIX-14-Cu-i is attributed to its unique pore shape and functional pore surface, which combine a contracted pore window (3.4 Å) and a relatively large pore cavity decorated with high density of inorganic anions. Dispersion-corrected density functional theory calculation and neutron powder diffraction were performed to understand the CO 2 binding sites. The practical feasibility of SIFSIX-14-Cu-i for CO 2 /CH 4 mixtures separation was validated by experimental breakthrough tests. This study not only demonstrates the great potential of SIFSIX-14-Cu-i for CO 2 separation but also provides important clues for other gas separations.

A highly stable amino-coordinated metal-organic framework ZJU-198 has been synthesized and structurally characterized, exhibiting high CO 2 uptake of 105.8 cm 3 cm -3 while blocking off N 2 adsorption at 1.0 bar and 298 K, attributed to the unique pore window sizes.