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Fine-grained management of rice fields can enhance the yield and quality of rice crops. Challenges in achieving fine classification include interference from similar vegetation, the irregularity of natural field shapes, and complex scale variations. This paper introduces Rice Attention Cascade Network (RACNet), for the fine classification of rice fields in high-resolution satellite remote sensing imagery. The network employs the Hybrid Task Cascade network as the base framework and uses spectral and indices mixed multimodal data as input to reinforce the feature differentiation of similar vegetation. Initially, a Channel Attention Deformable-ResNet (CAD-ResNet) was designed to enhance the feature representation of rice on different channels. Deformable convolution improves the ability of CAD-ResNet to capture irregular field shapes. Then, to address the issue of complex scale changes, the multi-scale features extracted by the CAD-ResNet are progressively fused using an Asymptotic Feature Pyramid, reducing the loss of scale information between non-adjacent layers. Experiments on the Meishan rice dataset show that the proposed method is capable of accurate instance segmentation for fragmented or irregularly shaped rice fields. The evaluation metric AP50 of RACNet reaches 50.8%. [ABSTRACT FROM AUTHOR]

This study aimed for a better understanding of the niche specification of bacteria carrying the tfd-genes for aerobic 2,4-dichlorphenoxyacetic acid (2,4-D) degradation in the rice paddy ecosystem. To achieve this, a dedicated microcosm experiment was set up to mimic the rice paddy system, with and without 2,4-D addition, allowing spatial sampling of the different rice paddy compartments and niches, i.e., the main anaerobic bulk soil and the aerobic surface water, surface soil, root surface and rhizosphere compartments. No effect of 2,4-D on the growth and morphology of the rice plant was noted. 2,4-D removal was faster in the upper soil layers compared to the deeper layers and was more rapid after the second 2,4-D addition compared to the first. Moreover, higher relative abundances of the 2,4-D catabolic gene tfdA and of the mobile genetic elements IncP-1 and IS1071 reported to carry the tfd-genes, were observed in surface water and surface soil when 2,4-D was added. tfdA was also detected in the root surface and rhizosphere compartment but without response to 2,4-D addition. While analysis of the bacterial community composition using high-throughput 16S rRNA gene amplicon sequencing did not reveal expected tfd-carrying taxa, subtle community changes linked with 2,4-D treatment and the presence of the plant were observed. These findings suggest (i) that the surface soil and surface water are the primary and most favorable compartements/niches for tfdmediated aerobic 2,4-D biodegradation and (ii) that the community structure in the 2,4-D treated rice paddy ecosystem is determined by a niche-dependent complex interplay between the effects of the plant and of 2,4-D. [ABSTRACT FROM AUTHOR]

• Spider community composition changed during the rice growing season. • The rice field development generally decreased the number of horizontal web-building spiders and captured detritivorous prey. • Species identity and species traits of spider as well as environmental factors affect prey capture by web-building spiders. Understanding the effects of microhabitat changes on arthropod predator communities and their prey in agroecosystems is essential for field management and biocontrol. Few studies have investigated the trait composition of web-building spider communities in rice ecosystems. Here, we examined how temporal changes during the rice field development affect the abundance and traits of orb-web spiders, and how these effects consequently influence captured prey number and prey composition in irrigated rice ecosystems in southern Thailand. We used structural equation models to evaluate direct and indirect, spider-mediated effects of rice field development on captured prey numbers in each different guild. We found that the number of horizontal web-building spiders decreased during the rice field development, whereas there was no significant change in number of vertical web-building spiders. The number of captured detritivorous insects was positively related to the numbers of horizontal and vertical web-building spiders, while phytophagous insects and others were positively related only to the numbers of vertical web-building spiders. Moreover, the prey number captured by vertical web-building spiders seems to be indirectly increased through the decreasing number of horizontal web-building spiders in the late rice season. A fourth-corner analysis showed that spider species identity, spider traits (web type, web height and web diameter), vegetation height, and water level generally influenced the prey captured by web-building spiders. Horizontal web-building spider species with lower web placement during the flooding phase captured high numbers of detritus-feeding insects, while vertical web-building spider species with higher web placement captured high numbers of rice pests, predators and others. Our results suggest that the field development acted as an environmental factor that determined the species identity and traits of web-building spider communities. The findings of this study can help to predict the ecosystem services provided by the web-building spider community in rice ecosystems. [ABSTRACT FROM AUTHOR]

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Brazil, a leading rice producer globally, faces challenges in systematically mapping its diverse rice fields due to varying cropping systems, climates, and planting calendars. Existing rice mapping methods often rely on complex techniques like deep learning or microwave imagery, posing limitations for large-scale mapping. This study proposes a novel approach utilizing Sentinel-2 spectral–temporal metrics (STMs) in conjunction with a random forest classifier for rice paddy mapping. By extracting diverse STMs and training both regional and global classifiers, we validated the method across independent areas. While regional models tended to overestimate rice areas, the global model effectively reduced discrepancies between our data and the reference maps, achieving an overall classifier accuracy exceeding 80%. Despite the need for further refinement to address confusion with other crops, STM exhibits promise for national-scale rice paddy mapping in Brazil. [ABSTRACT FROM AUTHOR]

Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography–ion mobility spectrometry (GC-IMS), free amino acid analysis and taste nucleotide analysis. The E-nose and E-tongue revealed that deodorization reduced the content of sulfur-containing compounds, enhanced umami, bitterness, sourness and astringency, and decreased saltiness. PCA and OPLS-DA analysis successfully distinguished between the effects of the treatments. Free amino acids increased from 8777.67 to 11,125.98 mg/100 g and umami amino acids increased from 128.24 to 150.37 mg/100 g after PJ-CW deodorization (p < 0.05). Equivalent umami concentration (EUC) comparisons showed that PJ-CW treatment produced the greatest synergistic umami enhancement (to 3.15 g MSG equiv./100 g). GC-IMS detected 52 aroma compounds; PJ treatment produced the greatest diversity of aldehydes, including heptanal, nonanal, hexanal, 3-methylbutanal, (E)-2-heptenal and (E,E)-2,4-heptadienal. The total content of volatile flavor compounds was the highest after PJ-CW treatment, and the content of many characteristic flavor substances (3-hydroxy-2-butanone, benzaldehyde, 5-methyl-2(3H)-furanone) increased. These findings provided a theoretical basis for the further development of deodorization methods for Paddy Field Carp. [ABSTRACT FROM AUTHOR]

To investigate the dynamics of stomata, transpiration, and photosynthesis under varying light intensities and CO2 conditions during leaf development, the light response and CO2 response of stomatal conductance (gsw), transpiration rate (Tr), and net photosynthetic rate (Pn) were observed for rice leaves at different days after leaf emergence (DAE). The results showed that (1) as photosynthetically active radiation (PAR) increased, leaf gsw, Tr, and Pn initially increased rapidly and linearly, followed by a more gradual rise to maximum values, and then either stabilized or showed a declining trend. The maximum gsw, Tr, and Pn were smaller and occurred earlier for old leaves than for young leaves. The gsw, Tr, and Pn all exhibited a linear decreasing trend with increasing DAE, and the rate of decrease slowed down with the reduction in PAR; (2) as the CO2 concentration (Ca) increased, gsw and Tr decreased gradually to a stable minimum value, while Pn increased linearly and slowly up to the maximum and then kept stable or decreased. The gsw, Tr, and Pn values initially kept high and then decreased with the increase of DAE. These results contribute to understanding the dynamics in gsw, Tr, and Pn during rice leaf growth and their response to varied light and CO2 concentration conditions and provide mechanistic support to estimate dynamic evapotranspiration and net ecosystem productivity at field-scale and a larger scale in paddy field ecosystems through the upscaling of leaf-level stomatal conductance, transpiration, and photosynthesis. [ABSTRACT FROM AUTHOR]

Direct seeding is employed to circumvent the labor-intensive process of rice (Oryza sativa) transplantation, but this approach requires varieties with vigorous low-temperature germination (LTG) when sown in cold climates. To investigate the genetic basis of LTG, we identified the quantitative trait locus (QTL) qLTG11 from rice variety Arroz da Terra, which shows rapid seed germination at lower temperatures, using QTL-seq. We delineated the candidate region to a 52-kb interval containing GENERAL REGULATORY FACTOR14h (GF14h) gene, which is expressed during seed germination. The Arroz da Terra GF14h allele encodes functional GF14h, whereas Japanese rice variety Hitomebore harbors a 4-bp deletion in the coding region. Knocking out functional GF14h in a near-isogenic line (NIL) carrying the Arroz da Terra allele decreased LTG, whereas overexpressing functional GF14h in Hitomebore increased LTG, indicating that GF14h is the causal gene behind qLTG11. Analysis of numerous Japanese rice accessions revealed that the functional GF14h allele was lost from popular varieties during modern breeding. We generated a NIL in the Hitomebore background carrying a 172-kb genomic fragment from Arroz da Terra including GF14h. The NIL showed superior LTG compared to Hitomebore, with otherwise comparable agronomic traits. The functional GF14h allele from Arroz da Terra represents a valuable resource for direct seeding in cold regions. Author summary: Rice serves as a fundamental crop sustaining over half of the global population. With the rapid growth of the world's population, it will become increasingly important to improve rice productivity. On the other hand, the aging of rice farmers in Japan has resulted in a constant labor shortage. To address this, direct seeding, in which seeds are sown directly in rice fields without going through the most labor-intensive part of the rice cultivation process, i.e., seedling production and transplanting, has been recommended. However, prevalent elite rice varieties are known to be unsuitable for direct seeding due to their poor seed germination ability under low-temperature conditions. In this study, we show for the first time that GF14h gene from the Portuguese variety Arroz da Terra improves seed germination at low temperatures (LTG). In addition, a novel cross-bred line was generated by introducing the GF14h-containing genomic segment from Arroz da Terra into Hitomebore, a widely cultivated variety in northern Japan. This line is expected to be used as a pre-breeding material to enhance LTG. This study will provide a genetic basis for LTG and contribute to basic and applied research progress. [ABSTRACT FROM AUTHOR]

Simple Summary: Methanogens are a group of microorganisms with the capability to convert inorganic or organic compounds into methane, impacting the global carbon cycle and greenhouse gas emissions. In anaerobic environments such as wetlands, paddy fields, and reservoirs, methanogens are the primary contributors to methane production. In this study, high-throughput sequencing of the mcrA functional gene was utilized to conduct a comprehensive analysis of the community structure, metabolic pathways, and influencing factors of methanogens in the sediment of 18 reservoirs on the northeastern Qinghai Plateau. The results indicated that the construction of reservoirs has altered the physicochemical properties of river water and sediments, significantly impacting the distribution and succession of methanogenic communities in the sediment. In general, this study can improve our understanding of the biological mechanisms of methane emissions from the reservoirs on the Qinghai Plateau. Reservoirs are a hotspot for methane emissions, a potent greenhouse gas. However, the microbial basis for methane production in the Qinghai Plateau reservoirs remains unclear. To explore the characteristics of methanogenic communities in reservoir sediments on the northeastern Qinghai Plateau, sediment samples were collected from 18 reservoirs in the Yellow River basin during May 2023 (dry season) and August 2023 (wet season). High-throughput sequencing technology was employed to analyze the community composition, diversity, and co-occurrence network of methanogens. Furthermore, FAPROTAX and Mantel analysis were used to assess the metabolic functions of methanogens and their influencing factors. The results showed that (1) the predominant genera of methanogens were Methanobacterium (28.87%) and Methanosarcina (21.67%). Hydrogenotrophic methanogenesis was the main pathway in the sediments. (2) Significant spatiotemporal differences were observed in the diversity of methanogenic communities (p < 0.05). The composition and diversity of these communities were found to be significantly influenced by temperature, pH, altitude, organic carbon, and total nitrogen (p < 0.05). (3) Methanosarcina, Methanobacterium, and Methanospirillum play crucial roles in maintaining the stability of methanogenic community networks. The co-occurrence network nodes are predominantly positively correlated (99.82%). These results provide data for further studies on carbon cycling in the Qinghai Plateau reservoirs. [ABSTRACT FROM AUTHOR]

Ratoon rice (RR) has emerged as an active adaptation to climate uncertainty, stabilizing total paddy rice yield and effectively reducing agriculture-related ecological environmental issues. However, identifying key remote sensing parameters for RR under cloudy and foggy conditions is challenging, and existing RR monitoring methods in these regions face significant uncertainties. Here, given the sensitivity of synthetic aperture radar (SAR) backscattering signals to the crop phenological period, this paper introduces a threshold model utilizing Sentinel-1A SAR data and phenological information for mapping RR. The Yongchuan District of Chongqing, which is often cloudy and foggy, was selected as a specific study region where VH-polarized backscatter coefficients of Sentinel-1 images were obtained at 10 m spatial resolution in 2020. Based on the proposed threshold model, the RR extraction overall accuracy was up to 90.24%, F1 score was 0.92, and Kappa coefficient was 0.80. Further analysis showed that the extracted RR boundaries exhibited high consistency with true Sentinel-2 remote sensing images and the RR extracted area was in good agreement with the actual planted area situation. This threshold model demonstrated good applicability in the studied cloudy and foggy region, and successfully distinguished RR from other paddy rice types. The methodological framework established in this study provides a basis for extensive application in China and other significant RR-producing regions globally. [ABSTRACT FROM AUTHOR]

In Asia, rice is the most consumed grain by humans, serving as a staple food in India. The yield of rice paddies is easily affected by nutrient deficiencies and leaf diseases. To overcome this problem and improve the yield productivity of rice, nutrient deficiency and leaf disease identification are essential. The main nutrient elements in paddies are potassium, phosphorus, and nitrogen (PPN), the deficiency of any of which strongly affects the rice plants. When multiple nutrient elements are deficient, the leaf color of the rice plants is altered. To overcome this problem, optimal nutrient delivery is required. Hence, the present study proposes the use of Fuzzy C Means clustering (FCM) with Improved Tunicate Swarm Optimization (ITSO) to segment the lesions in rice plant leaves and identify the deficient nutrients. The proposed ITSO integrates the Tunicate Swarm Optimization (TSO) and Bacterial Foraging Optimization (BFO) approaches. The Hybrid Convolutional Neural Network (HCNN), a deep learning model, is used with ITSO to classify the rice leaf diseases, as well as nutrient deficiencies in the leaves. Two datasets, namely, a field work dataset and a Kaggle dataset, were used for the present study. The proposed HCNN-ITSO classified Bacterial Leaf Bright (BLB), Narrow Brown Leaf Spot (NBLS), Sheath Rot (SR), Brown Spot (BS), and Leaf Smut (LS) in the field work dataset. Furthermore, the potassium-, phosphorus-, and nitrogen-deficiency-presenting leaves were classified using the proposed HCNN-ITSO in the Kaggle dataset. The MATLAB platform was used for experimental analysis in the field work and Kaggle datasets in terms of various performance measures. When compared to previous methods, the proposed method achieved the best accuracies of 98.8% and 99.01% in the field work and Kaggle datasets, respectively. [ABSTRACT FROM AUTHOR]

With growing concerns about global warming, it is crucial to adopt agronomic practices that enhance rice yields from paddy fields while reducing greenhouse gas (GHG) emissions for sustainable agriculture. An optimal nitrogen (N) fertilization rate and planting density are vital to ensure high rice yields, minimize GHG emissions, and understand emission behavior for better field management. We hypothesized that optimizing N application rates and planting density to improve nitrogen use efficiency (NUE) in rice cultivation would reduce resource losses and GHG emissions. To test this hypothesis, we implemented five treatments with a rice straw return cultural system: two planting densities (16 hills m−2 (traditional density, D1) and 20 hills m−2 (25% higher density, D2)) and three N application rates (no N fertilizer (N0), 180 kg N ha−1 (N1), and 144 kg N ha−1 (N2)). The control treatment (CK) was traditional planting density with no N fertilizer. The four new cropping modes were N1D1, N1D2, N2D1, and N2D2. We investigated the effects of N application rates and planting density on rice grain yield, NUE, and GHG emissions in multiple rice-growing seasons. The N1D2 treatment exhibited the highest grain yield over the three years, with a value of 10,452 kg ha−1, representing an increase of 12.2% compared to CK. Moreover, N uptake in N1D2 was the highest, averaging 39.2% (p < 0.05) higher than CK, and 8.5%, 3.5%, and 2.8% (p < 0.05) higher than N1D1, N2D1 and N2D2, respectively. N2D2 exhibited the highest NUE, with a value of 58.99 kg kg−1, surpassing all other treatments over the three years. GHG emissions, global warming potential (GWP), and greenhouse gas intensity (GHGI) in N2D2 were lower than in N1D1, N1D2, and N2D1. Additionally, reducing N application (comparing N1D1 to N2D1) and increasing plant density (comparing N1D1 to N1D2) improved N agronomic efficiency (NAE) and N partial productivity (PFPN). The negative correlation between the NAE and PFPN with GWP and GHG emissions further supports the potential for optimized N management and denser planting density to reduce environmental impact. These findings have important implications for sustainable rice cultivation practices in Southwest China and similar agroecosystems, emphasizing the need for integrated nutrient management strategies to achieve food security and climate change mitigation goals. [ABSTRACT FROM AUTHOR]

Drying involves the evaporation of moisture, accompanied by simultaneous heat transfer, mass transfer, and momentum transfer. While the diffusion law is considered an applicable model for explaining the drying phenomenon, the actual drying process cannot be accurately predicted using an analytical solution with a constant diffusion coefficient. Energy efficiency in the drying process is low due to an insufficient understanding of the mechanisms governing moisture migration from solids to air. The development of drying theory has stalled due to an unsolvable discrepancy between experimental results and analytical results. This study analyzes the effect of the binding energy of moisture in paddy rice on the diffusion coefficient. The theoretical relationship between water activity and drying rate in paddy rice was investigated, and the drying process was successfully explained by analyzing free energy transfer and transition theory. The mechanism of rice grain drying was described using a new theoretical solution for the drying process. These results provide new insights into the development of a scientific evaluation standard for assessing the efficiency of actual drying processes. [ABSTRACT FROM AUTHOR]

A precision agriculture approach that uses drones for crop protection and variable rate application has become the main method of rice weed control, but it suffers from excessive spraying issues, which can pollute soil and water environments and harm ecosystems. This study proposes a method to generate variable spray prescription maps based on the actual distribution of weeds in rice fields and utilize DJI plant protection UAVs to perform automatic variable spraying operations according to the prescription maps, achieving precise pesticide application. We first construct the YOLOv8n DT model by transferring the "knowledge features" learned by the larger YOLOv8l model with strong feature extraction capabilities to the smaller YOLOv8n model through knowledge distillation. We use this model to identify weeds in the field and generate an actual distribution map of rice field weeds based on the recognition results. The number of weeds in each experimental plot is counted, and the specific amount of pesticide for each plot is determined based on the amount of weeds and the spraying strategy proposed in this study. Variable spray prescription maps are then generated accordingly. DJI plant protection UAVs are used to perform automatic variable spraying operations based on prescription maps. Water-sensitive papers are used to collect droplets during the automatic variable operation process of UAVs, and the variable spraying effect is evaluated through droplet analysis. YOLOv8n-DT improved the accuracy of the model by 3.1% while keeping the model parameters constant, and the accuracy of identifying weeds in rice fields reached 0.82, which is close to the accuracy of the teacher network. Compared to the traditional extensive spraying method, the approach in this study saves approximately 15.28% of herbicides. This study demonstrates a complete workflow from UAV image acquisition to the evaluation of the variable spraying effect of plant protection UAVs. The method proposed in this research may provide an effective solution to balance the use of chemical herbicides and protect ecological safety. [ABSTRACT FROM AUTHOR]

Crop straw returning to the field is an effective practice for straw utilization to improve soil fertility and sustain crop productivity. However, little information is available about the long-term effects of paddy straw return on soil properties and rice yield under a double-rice system. The objectives of this study were to test the hypothesis of the effects of different amounts of paddy straw returned to the field on soil physicochemical properties and rice yield, and to clarify the correlation between crop yield and soil physicochemical properties as well as quick-acting nutrients under different straw-returning modes. The experiment, initiated in the 2005 rice season, utilized "Xiang 45" and "Xiang 13" long-grained rice cultivars within a double-season rice cropping system. Three straw-returning treatments were implemented: rotary tillage with full rice straw incorporation (RTS), incorporation of one-third of the rice straw (1/3RTS), and incorporation of two-thirds of the rice straw (2/3RTS). This study found that among the three straw return rates, 2/3RTS had the most significant impact on soil physicochemical properties. Soil nitrogen content was identified as a crucial factor influencing soil organic carbon (SOC) accumulation, while pH levels significantly affected rice yield. Straw incorporation effectively increased the content and stocks of SOC. [ABSTRACT FROM AUTHOR]

Taking fresh soil samples from a rice–wheat rotation field (RW), a permanently flooded rice field (PF), and a double-rice cropping field (DR: DRE for the early rice; DRL for the late rice), we measured the CH4 production potential (MPP), the relative contribution of acetate-dependent methanogenesis (ƒac), soil properties, and methanogenic archaeal communities mainly in order to reveal the temporal variation and corresponding influencing factors of methanogenic pathways in paddy soils. Consistent with the change in dissolved organic C (DOC) content, the MPP generally decreased with rice growth in RW and DRL while increasing in PF and DRE. Based on the measurements of stable carbon isotopes, the estimated ƒac-value in PF dropped sharply from 54%-61% at the tillering stage to 30%-35% at the booting stage and rose again at the ripening stage. This variation pattern was positively correlated with that of acetate content, perhaps resulting from the activation of acetoclastic Methanosarcina. In contrast, the ƒac-value in RW and DR rose from 20%-44% at the tillering stage to 49%-59% at the ripening stage, possibly owing to the increase in the relative abundance of acetoclastic Methanothrix. The relative abundance of Methanosarcina in PF was 3%-4% higher than those in RW and DR, whereas that of Methanothrix was 3%-7% lower (P < 0.05). Soil acetate, DOC, and moisture contents significantly affected the methanogenic community composition. Our results demonstrate that the temporal variation of methanogenic pathways was influenced by the relative abundance of acetoclastic methanogens depending on the acetate level. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) residues (root and straw) are unique substrates for microbes in paddy soils. Microbial respiration (RH) of paddy soils is likely to be affected by substrate quality. However, no relevant study on the effects of changed rice residue chemistry by climate change on the temperature sensitivity (Q10) of the RH of soils amended with the residues is available. To fill this knowledge gap, we conducted an incubation experiment (at 15, 25, and 35 °C) with rice residues of which lignin, nonstructural carbohydrate (NSC), and carbon-to-nitrogen ratio (C/N) were modified by growing the rice plants under different CO2 and air temperature (Tair). Co-elevated CO2 and Tair decreased lignin and C/N but increased the NSC contents of the residues, leading to the greater RH in the soils amended with rice residues produced under co-elevated CO2 and Tair compared to other CO2 or Tair treatments. However, the Q10 values of the RH of soils amended with rice residues produced under different CO2 and Tair were marginally changed, probably due to other confounding factors such as soil enzyme activity and nutrient availability. Despite that, there was a negative relationship between NSC and Q10 for soils amended with straw of which C/N is lower than root, agreeing with the kinetic theory on "substrate quality–Q10 relationship". Our result suggests that residue chemistry may not affect the Q10 of soils with root residue, but for straw-amended soils, less-recalcitrant NSC rather than more-recalcitrant lignin of straw may be critical in determining the Q10 of the soils. [ABSTRACT FROM AUTHOR]

Irrigated and rain-fed rice fields are unique agroecosystems and anthropogenic wetlands whose main feature is seasonal flooding. Flooded soils are characterized by spatiotemporal shifts and oscillation of the oxygen status and redox potential, sustaining varieties of microbial metabolisms, where bacteria and methanogenic archaea play principal roles and thus have been the major research targets. In this review, we focus on the diversity and ecology of protists—often overlooked biological entities—in wetland rice field soils. Protists with different ecological functions, i.e., phagotrophs, phototrophs, saprotrophs, and parasites, inhabit a rice field soil with a community- and individual-level adaptation to the wide range of oxygen tensions and redox potential. Other agricultural managements like fertilization and char application also influence the protist community. They link to the material cycling in rice soil and affect the activities and community composition of the microorganisms involved in the biogeochemical cycles. Rice roots are the hot spot for protists, which control the rhizospheric bacterial community and could increase the plant productivity through enhancing nutrient release and altering bacterial activities. This review highlights the essential roles of protists in a wetland rice field soil and needs for further research to fill the gaps in knowledge regarding the diversity and functions of the protists in this unique agroecosystem. [ABSTRACT FROM AUTHOR]

Dry direct-seeding can get rid of the constraints of high-water demand, and is the simplest and most laborsaving mode in rice (Oryza sativa L.) cultivation. However, weeds are more prone to occur in dry direct-seeding rice fields, coupled with increased herbicide resistance, leading to confusion among growers regarding herbicide selection. In this study, our investigation results revealed total grass quantity reached 458.82 plants m-2. Two round of field experiments were conducted to determine suitable post-emergence herbicides for dry directseeding indica rice. The results showed that among the herbicides safe to indica rice, the efficacy of the combination of pyraquinate (a new 4-hydroxyphenylpyruvate dioxygenase inhibitor, 150.0 g ai ha-1) + florpyrauxifen-benzyl (13.5 g ai ha-1) on Leptochloa chinensis (L.) Nees, Eclipta prostrata (L.) L., Cyperus iria L., Fimbristylis miliacea auct., and total grasses were 89.1%, 97.8%, 97.2%, 90.1%, and 92.8%, respectively; the efficacy of metamifop (120.0 g ai ha-1) + florpyrauxifen-benzyl (18.0 g ai ha-1) and 22.0% cyhalofop-butyl + pyrazosulfuron-ethyl + bispyribac-sodium OD (148.5 g ai ha-1) on main weeds also exceeds 85.0%, except for cyhalofop-butyl-resistant L. chinensis. The combination of metamifop + florpyrauxifen-benzyl and 22.0% cyhalofop-butyl + pyrazosulfuron-ethyl + bispyribac-sodium OD can be selected for fields where L. chinensis is not resistant to acetyl-CoA carboxylase (ACCase) inhibitors. The combination of pyraquinate + florpyrauxifenbenzyl is the most promising combination to control multiple weeds, even ACCase inhibitors-resistant weeds. This study could also provide references for herbicides selection and management of ACCase inhibitors-resistant L. chinensis in dry direct-seeding indica rice field worldwide. [ABSTRACT FROM AUTHOR]

The identification and classification of pests in rice field are the prerequisites of early warning systems for pest dis-asters. Among these pests, the rice planthoppers cause the most serious damage. However, the existing deep learning models for rice planthopper recognition are characterized by large size and numerous parameters, which makes them unsuitable for the deployment on embedded devices with limited computational resources. To address this issue, a lightweight rice planthopper recognition model based on YOLOv5 is proposed in this paper. In the model, a lightweight convolutional network named GhostNet is employed as the backbone to reduce the operational parameters. Additionally, a convolutional attention module (CBAM) is integrated into the backbone network to effectively enhance the transmission of deep information, so as to improve the model's ability of recognizing rice planthopper images. The original CIoU loss function is replaced by the SIoU loss function to expedite model convergence. Experimental results demonstrate that the modified model achieves the mAP@0.5 as 82.8%, with the parameter count of 3.12x106 and the model size of 7.2MB. Compared to the original model, it is a reduction of 46.7% in size and 43.3% in parameters, with a minor accuracy loss of 0.1%. Clearly, the improved model can achieve lightweight characteristics and robust performance, and thus it provides a theoretical and practical foundation for early warning systems against rice planthopper infestations in rice fields. [ABSTRACT FROM AUTHOR]

Methanotrophs of the genus Methylocystis are frequently found in rice paddies. Although more than ten facultative methanotrophs have been reported since 2005, none of these strains was isolated from paddy soil. Here, a facultative methane-oxidizing bacterium, Methylocystis iwaonis SD4, was isolated and characterized from rhizosphere samples of rice plants in Nanjing, China. This strain grew well on methane or methanol but was able to grow slowly using acetate or ethanol. Moreover, strain SD4 showed sustained growth at low concentrations of methane (100 and 500 ppmv). M. iwaonis SD4 could utilize diverse nitrogen sources, including nitrate, urea, ammonium as well as dinitrogen. Strain SD4 possessed genes encoding both the particulate methane monooxygenase and the soluble methane monooxygenase. Simple and rapid genetic manipulation methods were established for this strain, enabling vector transformation and unmarked genetic manipulation. Fast growth rate and efficient genetic tools make M. iwaonis SD4 an ideal model to study facultative methanotrophs, and the ability to grow on low concentration of methane implies its potential in methane removal. [ABSTRACT FROM AUTHOR]

Manure application is a recommended method to improve soil quality and mitigate global warming via soil carbon (C) sequestration. However, such application can significantly increase ammonia (NH3) volatilization loss and cause secondary environmental problems, such as acidification, eutrophication, and particulate matter formation. To investigate the potential of reducing NH3 emissions in flooded rice paddies, three types of stabilized swine manure amendments (fresh, composted, and biochar) were applied at a rate of 12 Mg ha-1 (dry weight) under standard fertilization (N-P2O5-K2O = 90-45-57 kg ha-1), and NH3 emission was characterized using the static chamber method. Regardless of manure management practices, NH3 fluxes increased significantly immediately after application of an inorganic nitrogen (N) fertilizer (urea). The manure was applied completely as the basal fertilizer before rice transplanting, but the NH3 emission rates increased more dramatically following urea application in the manure treatments. Fresh and composted manure applications significantly increased seasonal NH3 volatilization losses compared to the control but the biochar did not. Compost manure significantly increased rice grain productivity owing to the higher N content, while fresh and biochar manures did not increase rice productivity because of fewer panicles per hill and fewer grains per panicle. Consequently, biochar application resulted in lower NH3 flux intensity and seasonal NH3 flux per grain yield, whereas fresh and compost manures substantially increased this intensity. Therefore, biochar manure may be a more reasonable organic amendment than fresh and composted manures for reducing NH3 emission impacts on rice paddies. [ABSTRACT FROM AUTHOR]

Data on the soil nutrient content are required to calculate fertilizer rate recommendations. The soil laboratory determines these soil properties, yet the measurement is time-consuming and costly. Meanwhile, portable devices to assess the soil nutrient content in real-time are limited. However, a proprietary and low-cost NPK sensor is available and commonly used in IoT for agriculture. This study aimed to assemble and test a portable, NPK sensor-based device in irrigated and rainfed paddy soils from Java, Indonesia. The device development followed a prototyping approach. The device building included market surveys and opted for an inexpensive, light, and compact soil sensor, power storage, monitor, and wire connectors. Arduino programming language was used to write scripts for data display and sub-device communication. The result is a real-time, portable soil nutrient detector that measures the soil temperature, moisture, pH, electrical conductivity, and N, P, and K contents. Field tests show that the device is sensitive to soil properties and location. The portable soil nutrient detector may be an alternative tool for the real-time measurement of soil nutrients in paddy fields in Indonesia. [ABSTRACT FROM AUTHOR]

Wheat and barley yields in Japan are considerably lower than those in the UK, even where similar Climate Zones (CZs) of relatively cold and humid nature are shared. In order to understand this difference, it is first necessary to find out if any common climate–yield relationship exists between the two countries. The Climate Zonation Scheme (CZS) developed in the Global Yield Gap Atlas (GYGA) was used to analyse actual yield (Ya) with three climatic factors of the GYGA-CZS, i.e., growing degree days (GDD), aridity index (AI) and temperature seasonality (TS). A significant relationship was found between AI scores and Ya values across the two countries. Ya values decreased with an increase in AI scores; in other words, lower yields are associated with higher AI scores. In addition, the degree of yield reduction with the rise in AI scores was greater in Japan than in the UK. The present study also proposed a novel method to link CZs of the GYGA-CZS to regional classification units, especially for countries where statistical crop yield data are available only at a coarse scale. [ABSTRACT FROM AUTHOR]

Paddy field leveling is an essential step before rice transplanting. During the operation of a paddy field grader, a common issue is the wrapping of rice straw around the blades, resulting in a low rice straw burial rate. This study focused on analyzing the operating parameters of a disc spring–tooth-combined paddy field grader. A soil–straw mechanism simulation model was created using EDEM 2021 software to simulate the field operation status. Firstly, the single-factor test was carried out, with the working speed, the working depth of the disc cutter roller, and the rotation speed of the cutter roller as the factors and the straw-buried rate (SBR) and the machine forward resistance (MFR) as the test indexes, and the parameter range was optimized. The parameters were optimized by the response surface method (RSM) and machine learning algorithms. The results indicated that the genetic algorithm–back propagation (GA-BP) neural network outperformed other optimization models in terms of prediction accuracy and stability. By utilizing the GA-BP regression model and RSM model for regression fitting, two sets of optimal parameter combinations were obtained. Verification experiments were carried out using two sets of parameter combinations. Taking the average of the experimental results, the simulation results showed that the straw burial rate was 93.47% and the forward resistance was 6487 N for the parameter combinations of RSM, and the straw burial rate was 94.86% and the forward resistance was 6352 N for the parameter combinations of GA-BP; the field experiments showed that the straw burial rate was 92.86% and the forward resistance was 6518 N for the parameter combinations of RSM, and the straw burial rate was 95.17% and the forward resistance was 6249 N for the parameter combinations of GA-BP. The results demonstrated that the GA-BP prediction model exhibited better predictive capabilities compared to the traditional RSM, providing more accurate predictions of the paddy field grader's field operation performance. [ABSTRACT FROM AUTHOR]

The surge in global agricultural input prices, particularly for nitrogen (N) fertilizers, has presented challenges for farmers facing stagnant crop prices and rising production costs. This study explored a system designed to sustain or enhance farmers' income while reducing production costs, with a specific focus on implementing practices that involve cultivating crops with lower rates of fertilizer than conventional rates, particularly in smaller land settings, through on-farm experimentation (OFE). OFE was conducted over three years across 11 fields in Gifu, Japan, utilizing a strip trial design to investigate the effect of fertilizer input rates on rice yield. To collect yield data, unmanned aerial vehicle (UAV)-mounted multispectral cameras were deployed. A Gaussian process model was used to address the impact of fertilizer input rates on yield while accounting for spatial yield variation. The study further assessed the number of field trials achieving positive profits at certain probability levels by integrating outcomes from multiple OFEs. The results highlighted little rice yield response to fertilizer input in most of the fields, while several fields showed significant positive yield responses. Notably, the use of lower fertilizer input rates in certain fields proved to be more profitable whereas higher fertilizer input rates were less profitable in most fields. The results further emphasized the economic viability of lower rates, especially when fertilizer prices are high, thus contributing valuable insights for sustainable and profitable rice production in Japanese cultivation. [ABSTRACT FROM AUTHOR]

To investigate difference in the quality of the different parts (back, tail muscles, and fish skin) of Opsariichthys bidens from pond and rice field cultures, a comparative study was conducted in terms of nutritional composition, volatile flavor profiles and gut microbiota. In detail, the texture, free amino acids, fatty acids were further assessed. The results suggested that the moisture content, crude protein and crude fat content in the skin of O. bidens are higher than those in the back and tail muscles, regardless of breeding modes. The fish cultured in the rice field had a higher protein content than those from the pond culture, while the fat content of the rice field-cultured fish was significantly low compared to the fish from the pond culture, especially in the back and tail parts. A total of 43 volatile components were detected by Gas Chromatography–Mass Spectrometry (GC-MS), with a maximum of 18 types of aldehydes and the highest concentration being nonanal. Compared to pond cultures, the fish from the rice field cultures showed more abundant flavor composition and odor-active compounds. The total content of DHA (Docosahexaenoic Acid) and EPA (Eicosapentaenoic Acid) in the rice field-cultured fish was higher than that of the pond group, while no significant disparity in amino acid composition was observed (p > 0.05). Comparative and clustering analyses of gut microbiota revealed notable discrepancies in the gut microbiota of O. bidens from two aquaculture systems. However, an inherent correlation between the gut microbiome and meat quality would be further emphasized in further studies. This study can offer a theoretical reference for the development of high-quality aquatic products by selecting the appropriate aquaculture models. [ABSTRACT FROM AUTHOR]

Background: Crop diversification is considered as an imperative approach for synchronizing the plant nutrient demands and soil nutrient availability. Taking two or more crops from the same field in one year is considered as multiple cropping. It improves the diversity and abundance of soil microbes, thereby improving the growth and yield of crops. Therefore, the present study was conducted to explore the effects of different multiple winter cropping on soil microbial communities in paddy fields. In this study, eight rice cropping patterns from two multiple cropping systems with three different winter crops, including Chinese milk vetch (CMV), rape, and wheat were selected. The effects of different multiple winter cropping on soil microbial abundance, community structure, and diversity in paddy fields were studied by 16 S rRNA high-throughput sequencing and real-time fluorescence quantitative polymerase chain reaction (PCR). Results: The results showed that different multiple winter cropping increased the operational taxonomic units (OTUs), species richness, and community richness index of the bacterial community in 0 ~ 20 cm soil layer. Moreover, soil physical and chemical properties of different multiple cropping patterns also affected the diversity and abundance of microbial bacterial communities. The multiple cropping increased soil potassium and nitrogen content, which significantly affected the diversity and abundance of bacterial communities, and it also increased the overall paddy yield. Moreover, different winter cropping changed the population distribution of microorganisms, and Proteobacteria, Acidobacteria, Nitrospira, and Chloroflexi were identified as the most dominant groups. Multiple winter cropping, especially rape-early rice-late rice (TR) andChinese milk vetch- early rice-late rice (TC) enhanced the abundance of Proteobacteria, Acidobacteria, and Actinobacteria and decreased the relative abundance of Verrucomicrobia and Euryarchaeota. Conclusion: In conclusion, winter cropping of Chinese milk vetch and rape were beneficial to improve the soil fertility, bacteria diversity, abundance and rice yield. [ABSTRACT FROM AUTHOR]

Introduction: There is lack of information on the impact of acidity correctives (lime and silicate) and nitrogen (N), phosphorus (P), and potassium (K) fertilizers on the fertility, carbon stocks, carbon stratification, and carbon sequestration potential of paddy soils. To fill this knowledge gap and contribute to knowledge on how the treatments impact the soil ecosystem functions and services, a longterm field experiment was established in 1954 with four treatments and five replicates arranged in a randomized complete block design. Methods: Four treatments with five replicates per treatment were laid out in a randomized complete block design. The treatments included control/untreated (CT), only NPK, silicate-fortified NPK (NPKSi), and lime-fortified NPK (NPKLi). The treatments were applied to paddy soils classified as Fluvaquentic Eutrudepts. Results and discussion: Application of the treatments led to significant increases in soil pH by 0.9, 1.12, and 1.5 pH units in the NPK, NPKLi, and NPKSi-treated soils in 2021, respectively, compared to the initial soil pH. The increase in pH subsequently led to significant reductions in C stratification and C stocks, with reduced rates of C sequestration observed to be more pronounced in the soils treated with lime and silicate-fortified NPK fertilizers (NKPSi and NPKLi). Both NPKSi and NPKLi moderately increased soil fertility. The highest increase in soil fertility was observed in the NPKSi treatment, with an annual growth rate of 0.0160 and a relative change ratio of 128.2% relative to the initial soil fertility index recorded in 1970. A Pearson correlation analysis revealed that soil pH, exchangeable calcium, and available silicate were the soil properties that significantly contributed to the increase in the soil fertility of the treated soils in the rice paddy agroecosystem. Significance: Conclusively, the inclusion of silicate in long-term fertilization is an effective strategy to mitigate soil acidity and increase soil fertility. [ABSTRACT FROM AUTHOR]

Background: Grain quality is an important index of rice production, particularly when plants are grown under stress. Arsenic (As) contamination in paddy fields severely affects rice grain yield and quality. Here, the effects of As and combinations of As(III)-oxidizing bacteria (Pseudomonas stutzeri 4.25, 4.27, and 4.44) and plant growth-promoting bacteria (Delftia acidovorans KKU2500-12 and Cupriavidus taiwanensis KKU2500-3) on enzymes related to starch accumulation in grains and the grain quality of Khao Dawk Mali 105 rice cultivated in As-contaminated soil under greenhouse conditions were investigated. Results: Arsenic affected the activities of starch biosynthesis-related enzymes, and decreases of up to 76.27%, 71.53%, 49.74%, 73.39%, and 47.46% in AGPase, SSS, GBSS, SBE, and SDBE activities, respectively, and 9.42–61.07% in starch accumulation in grains were detected after growth in As-contaminated soil. However, the KKU2500-3/4.25 and KKU2500-3/4.44 combinations yielded the greatest enzyme activities in grains, and compared with the results observed in uninoculated seedlings, increases in starch accumulation of up to 51.16% and 23.81% were found in the inoculated seedlings after growth in medium- and high-As-contaminated soils, at 10–17 and 10–24 days after anthesis, respectively. The bacteria increased the 2-AP content in rice under As stress, possibly via the induction of proline, a 2-AP substrate. Bacterium-inoculated rice had significantly greater 2-AP levels than uninoculated rice, and 2.16–9.93% and 26.57–42.04% increases were detected in rice plants grown in medium- and high-As-contaminated soils, respectively. Conclusions: Arsenic toxicity can be mitigated in rice growing under greenhouse conditions by maintaining starch biosynthesis, accumulating amylose, and increasing 2-AP content. The effectiveness of these bacteria should be validated in paddy fields; hence, safe rice grains with a good starch content and aroma could be produced. Highlights: As(III) oxidation and PGPB improved the quality of the KDML 105 rice grains. Bacteria maintained starch biosynthesis-related enzyme activity in As-contaminated soils. Bacteria increased starch accumulation and the 2-AP aromatic content in rice grains. Bacteria improved the crop yield and grain quality of As-stressed rice plants. [ABSTRACT FROM AUTHOR]

Agricultural Heritage Systems (AHS) are pivotal in preserving rich agricultural production experience and traditional culture, as well as in maintaining biodiversity and promoting sustainable development in agriculture and rural economies. However, climate change poses significant threats to these systems, such as ecological degradation, biodiversity loss, and shifts in agricultural production patterns. This study, grounded in theories of information asymmetry and bounded rationality, constructs evolutionary game models for adaptive management of AHS under market mechanisms and government guidance. By employing stability analysis and numerical simulation with Delay Differential Equations (DDE) that consider historical delays, and through sensitivity analysis, this research delves into the strategic evolutionary outcomes of stakeholders under various scenarios. It aims to provide theoretical insights and policy recommendations for the dynamic protection and adaptive management of AHS in the face of climate change. The findings indicate that the public goods nature of AHS, alongside externalities and information asymmetry, leads to market failure. Sole reliance on autonomous actions by farmers and meteorological departments is insufficient for optimal resource allocation and effective protection. Government intervention, through regulatory and incentive measures, can effectively mitigate market failures and steer adaptive management of AHS towards efficiency and sustainability. Moreover, the study identifies key factors for adaptive management, such as enhancing stakeholders' initial willingness to participate, reducing the costs of adapting to climate change, optimizing cooperative benefit distribution mechanisms, and increasing the profitability of resource cooperation. Sensitivity analysis of government subsidies and penalty mechanisms further reveals the complex and critical role these policy tools play in fostering stakeholder engagement. Based on these findings, the study recommends enhancing initial participation willingness, controlling transformation costs to alleviate economic burdens, optimizing benefit distribution mechanisms to boost cooperative resource profitability, and establishing dynamic subsidy and penalty mechanisms for optimal resource allocation. The theoretical and practical contributions of this research lie in applying theories of information asymmetry and bounded rationality to the adaptive management of AHS under climate change, enriching the theoretical framework in this field, and providing scientific decision-making support for policymakers. By demonstrating an effective path for AHS protection through combined government and market mechanisms in the context of global climate change, this research holds significant theoretical and practical implications for enhancing the efficiency of adaptive management of AHS, protecting, and inheriting valuable agricultural cultural heritage. [ABSTRACT FROM AUTHOR]

The rice waterlogging stress test was conducted at the experimental base of the College of Agriculture, Yangtze University, using Yangxian You 418 as the test subject, in order to investigate the impact of waterlogging on rice growth during the period from July to August each year. Six waterlogging stress tests with different waterlogging depth (1/4 plant height (1/4PH), 2/4 PH, and 3/4 PH) and duration (5 d and 7 d) were set up at the jointing–booting stage of rice (T1: 1/4 PH, 7 d; T2: 2/4 PH, 7 d; T3: 3/4 PH, 7 d; T4: 1/4 PH, 5 d; T5: 2/4 PH, 5 d; T6: 3/4 PH, 5 d;) with shallow water irrigation (CK) as control. The plant height, population leaf area, above-ground dry matter, and the yield of rice were measured. The correlation between the waterlogging depth and rice yield reduction was analyzed, and the flood disaster threshold index of rice was established. The results showed that at the end of stress, the plant height of all waterlogged treatments exceeded CK, and the plant height of T3 and T6 treatments significantly increased by 31.90% and 15.93%, respectively. The leaf area of rice treated with T1, T3, T4, and T5 was higher than CK (p < 0.05), and the above-ground dry matter of rice treated with T2, T3, T4, T5, and T6 was higher than CK (p < 0.05). When normal irrigation was restored to the maturity stage, the plant height of all rice treated with waterlogging was still higher than CK (p < 0.05). However, as the degree of waterlogging increased, rice yield decreased significantly, with a notable reduction of 31.68% observed in the T3 treatment compared to CK. Assuming a drainage index based on a 20% decrease in rice yield, it is imperative that the ratio of flooded depth to plant height remains below 37% when waterlogging persists for 7 days in rice cultivation. These research findings offer crucial scientific insights for implementing effective drainage management measures during flood disasters in rice paddies. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the impacts of wild and breeding juvenile rice field eel under conditions of ammonia and heat stress. The growth performance (FBW, WGR, SGR, and FCR) of 360 wild (24.22 ± 0.30 g) and 360 breeding (24.16 ± 0.27 g) strains was significantly hindered by ammonia and heat stress. The inhibitory effects were more obvious when the two stresses were combined. The growth performance and survival rates of the breeding strains outperformed that of the wild strains under identical stress conditions, this was explained by the expression of the growth-related gene (gh). They have increased the enzyme activity (CAT and GSH-Px) and expression of immune-related genes (cat, gpx3, and hsp90a) in response to oxidative stress. However, the results of certain indicator enzymes indicate the presence of oxidative damage in their tissues. The presence of an inflammatory response in the tissues was suggested by the up-regulation of genes associated with pro-inflammatory cytokines (il-1b and il-8) and the downregulation of genes related to anti-inflammatory cytokines (il-10). Additionally, the presence of tissue damage was shown by the up-regulation of genes connected to apoptosis (cas2, cas8, and cas9) and the down-regulation of genes connected to tight junctions (zo-1). Nevertheless, it is noteworthy that breeding strains exhibited superior adaptability to ammonia and heat stress in comparison to wild strains. [ABSTRACT FROM AUTHOR]

As one of the most widely cultivated grain crops, paddy rice is a vital staple food in China and plays a crucial role in ensuring food security. Over the past decades, the planting area of paddy rice in China has shown substantial variability. Yet, there are no long-term high-resolution rice distribution maps in China, which hinders our ability to estimate greenhouse gas fluxes and crop production. This study developed a new optical satellite-based rice mapping method using a machine learning model and appropriate data preprocessing strategies to address the challenges of cloud contamination and missing data in optical remote sensing observations. This study produced CCD-Rice (China Crop Dataset-Rice), the first high-resolution rice distribution dataset in China from 1990 to 2016. Based on 391,659 validation samples, the overall accuracy of the distribution maps in each provincial administrative region averaged 90.26 %. Compared with 20,759 county-level statistical data, the coefficients of determination (R 2) of single- and double-season rice in each year averaged 0.84 and 0.80, respectively. The distribution maps can be obtained at https://doi.org/10.57760/sciencedb.15865 (Shen et al., 2024a). [ABSTRACT FROM AUTHOR]

The rice–fish co-culture is an important model of carp farming in China; however, research on the dynamics and assembly of water bacterial communities in this system remains limited. Therefore, this study aimed to explore the dynamics and assembly of bacterial communities, as well as their correlation with environmental factors in paddy water. For these purposes, this study was divided into two groups: a rice–carp co-culture (WRC) group and a rice monoculture (WRM) group, with 20 rice fields in each group. After 60 days of farming, the concentrations of NH4+-N, NO2−-N, TN, and PO43− were significantly higher in the WRC group than those in the WRM group. Alpha diversity analysis showed that the Shannon index in the WRC group was significantly decreased compared with the WRM group. At the phylum level, the relative abundance of Actinobacteria significantly increased, while the relative abundance of Proteobacteria and Bacteroidetes significantly decreased in the paddy water of the WRC group. The neutral community model (NCM) indicated that a random process played a dominant role in the construction of bacterial communities in the two groups, and common carp cultivation increased migration rates, thereby affecting community assembly. The co-occurrence network displayed that common carp cultivation led to looser interactions between bacterial communities. In addition, the contents of nutrients significantly affected the abundance of bacteria in paddy water. In summary, carp cultivation decreased the diversity of bacteria and changed the relative abundance of dominant bacteria, thereby affecting the stability and assembly of bacterial communities. [ABSTRACT FROM AUTHOR]

Simple Summary: Anammox microorganisms are beneficial for use in wastewater treatment reactors. However, the application is limited due to the slow growth, high sensitivity, and the lack of a pure culture. To expand the sources of anammox bacteria, we used terrestrial soils from rice paddy fields to enrich and detect the anammox bacteria. This approach revealed potential anammox activities in both microaerobic and anaerobic soil conditions. Anammox, a reaction in which microorganisms oxidize ammonia under anaerobic conditions, is used in the industry to remove ammonium from wastewater in an environmentally friendly manner. This process does not produce intermediate products such as nitrite or nitrate, which can act as secondary pollutants in soil and water environments. For industrial applications, anammox bacteria should be obtained from the environment and cultivated. Anammox bacteria generally exhibit a slow growth rate and may not produce a large number of cells due to their anaerobic metabolism. Additionally, their habitats appear to be limited to specific environments, such as oxidation-reduction transition zones. Consequently, most of the anammox bacteria that are used or studied originate from marine environments. In this study, anammox bacterial evidence was found in rice paddy soil and cultured under various conditions of aerobic, microaerobic, and anaerobic batch incubations to determine whether enrichment was possible. The anammox-specific gene (hzsA) and microbial community analyses were performed on the incubated soils. Although it was not easy to enrich anammox bacteria due to co-occurrence of denitrification and nitrification based on the chemistry data, potential existence of anammox bacteria was assumed in the terrestrial paddy soil environment. For potential industrial uses, anammox bacteria could be searched for in rice paddy soils by applying optimal enrichment conditions. [ABSTRACT FROM AUTHOR]

Exploring the growth and physiological response mechanisms of rice under continuous drought stress circumstances can provide a significant scientific foundation and technological assistance for meeting drought difficulties, improving drought resistance and rice (Oryza sativa L.) output, and ensuring food security. In this study, a rice field experiment was conducted under a rain shelter with five different treatments set up: P1 (drought stress from tillering stage), P2 (drought stress from jointing–booting stage), P3 (drought stress from heading–flowering stage), P4 (drought stress from grain filling stage), and CK (adequate water management throughout the growth stage). Continuous drought stress from different growth stages with four levels (mild, medium, moderate, and severe). The results showed that the effects of different drought stress treatments on rice growth varied significantly. Compared with the CK treatment, plant height was reduced by 12.10%, 8.14%, 3.83%, and 1.06% in the P1, P2, P3, and P4 treatments, respectively, and the number of tillers was reduced by 23.83%, 18.91%, 13.47%, and 8.68%, respectively. With the increase in drought stress levels, SPAD values and Rubisco activity of rice leaf continued to decrease; SOD activity showed a decreasing trend, but the decreasing trend of POD and CAT activities was not significant, while MDA content showed an increasing trend. For yield components, continuous drought stress significantly reduced spike length of rice by an average of 3.5%, effective number of spikes by 18.9%, thousand grain weight by 3.7%, grain number per spike by 11.6%, and fruiting rate by 1.8%, respectively, compared to CK treatments during the growth period. In general, continuous drought stress during the early growth period affected the effective spike number and the grain number per spike. Continuous drought stress after the grain filling stage had the least effect on yield (17.62% of yield reduction), and water use efficiency (1.76 kg m−3) was much higher than other treatments. These researchers' findings provide insight into how rice physiology and growth react to continuous drought stress, which is significant for agricultural operations. [ABSTRACT FROM AUTHOR]

(1) Background: Cyperaceae weeds have become a major type of weed in local paddy fields in China. (2) Methods: We assessed the impact of environmental factors, including temperature, light, salinity, water stress and soil depth, on the germination and emergence of three dominant Cyperaceae weeds: Cyperus difformis L., C. iria L. and Fimbristylis littoralis Gaudich. Using the dish dipping method, the performances of the pre- and post-emergence herbicides commonly used in paddy fields on three Cyperaceae weeds were evaluated using the pot method. (3) Results: The seeds optimally germinated at 35 °C in constant conditions and 25 °C/40 °C in alternating conditions. The seeds of the three Cyperaceae weeds were sensitive to light and could not germinate under dark conditions. The germination rate of the three weeds decreased with the increase in the NaCl concentration and water potential; the three weeds could not germinate at a 320 mmol·L−1 NaCl concentration and −0.1 MPa water potential. When the pH levels were 4 to 9, the germination rates of the three weeds were all greater than 80%. The burial depths to inhibit 50% of the emergence of C. difformis, C. iria and F. littoralis were 0.27, 1.06 and 0.42 cm, respectively. The control efficacy of the pre-emergence herbicides of pretilachlor, butachlor and oxyfluorfen on the three weeds were all above 90% at the recommended dose in the field. Halosulfuron-methyl, florpyrauxifen-benzyl and bentazone could effectively control the three Cyperaceae weeds; their performances on the three weeds at the 3- to 4-leaf stage were all above 82%. (4) Conclusions: The three Cyperaceae weed seeds have a strong adaptability to temperature, water potential, salinity and soil depth, and these weeds are sensitive to most pre- and post-emergence herbicides. Therefore, taking Cyperaceae weed seeds into the deep soil layer by tillage or selecting appropriate herbicides according to their growth stages can effectively control Cyperaceae weeds in rice fields. [ABSTRACT FROM AUTHOR]

Tillage practices are of critical importance in maintaining soil quality on cropland and for food production, with rice cultivation representing a significant portion of the world's food production and greenhouse gas (GHG) emissions. While numerous studies have examined the effects of reduced and no-tillage on soil GHG emissions and rice yields, the impact of adopting a rotational approach to tillage practices on the rice cultivation cycle remains uncertain. In this study, we conducted a four-year (2017–2020) field experiment in a single rice-growing area in Northeast China with the aim of investigating the effects of different tillage practices on GHG emissions from paddy fields and rice yields under full straw return conditions. We set up three experimental treatments: rotary tillage, plowing, and rotational tillage (i.e., a combination of one year of plowing and one year of rotary tillage). The results showed that averaged across all treatments, average methane (CH4, 302.6 ± 51.1 kg ha−1) and nitrous oxide (N2O, 0.86 ± 0.361 kg ha−1) emissions and rice yield (9.0 ± 0.9 t ha−1) did not exhibit significant inter-annual variability during the entire experimental period and were comparable to the average for the region. The ranking of GHG emissions during the rice-growing season was as follows: rotary tillage > plowing > rotational tillage. Across the experimental period, CH4 and N2O emissions were 9.1% and 8.5% lower in the plowing treatment and 21.2% and 13.1% lower in the rotational tillage treatment compared to the rotary tillage treatment. During the experimental period, there was no significant effect of tillage treatments on rice yield. This reduction in emissions may be attributed to changes in soil penetration resistance. In the rotational and plowing treatments, soil penetration resistance was in a range more adapted to rice growth and GHG emissions reduction compared to the rotary tillage treatment. The yield-scale GHG emission intensity was reduced by 12.7% and 26.1% in the plowing and rotational tillage treatments, respectively, in comparison to the rotary tillage treatment. This suggests that rotational tillage is a management practice that can achieve greenhouse gas emission reductions in paddy fields and stabilize or possibly increase rice yields. Consequently, the results demonstrated that a rotational alternation of multiple tillage practices is a synergistic strategy for achieving low carbon and high yield in rice in the cold rice-growing region of Northeast China. [ABSTRACT FROM AUTHOR]

Paddy-rice cultivation using the traditional continuous flooding method requires much water, up to 2500 L, to produce 1 kg of rice. Decreasing water availability is being exacerbated by climate dynamics, i.e., droughts and rainfall variability negatively affecting food security in developing regions, particularly Africa. Alternate wetting and drying (AWD) practice is a climate-smart water management strategy that, together with puddling (a critical field preparation process), significantly affects soil hydrological and physicochemical regimes, such as soil water dynamics and oxidation states in paddy fields. However, there are limited reviews on the effects and interaction of the AWD duration on hydrological conditions in the paddy-rice rhizosphere continuum under AWD practice at different rice growth stages. Our review synthesizes key scientific literature to examine water management and hydrological properties of paddy soils under AWD practice with climate change and sheds light on why farmers are skeptical in adopting the practice. To develop this paper, we reviewed scientific information from published journal articles, reliable reports, and our knowledge on paddy-rice cultivation and water management with climate change in Asia and Sub-Saharan Africa. Several studies confirm that AWD practice increases water–rice–crop productivity, yields, and reduces methane emissions. Limitations and challenges of AWD irrigation, including changes in soil structure that influence irrigation water application, variations in hydraulic conductivity caused by the duration and frequency of irrigation cycles, and frequent manual water level (WL) monitoring, are discussed. Opportunities to improve the integration of AWD strategies within government policies, irrigation schemes, and farmer acceptance due to skepticism, limited knowledge, and fear of unreliable water hindering adoption are highlighted. Future research suggestions include the following: (i) long-term measurement of water stress indices using infrared thermometers; (ii) seasonal suitability mapping using NDVI, GIS, and remote sensing; and (iii) application of smart sensors based on the Internet of Things (IoT) to address AWD challenges for precision water management in paddy fields with climate change. [ABSTRACT FROM AUTHOR]

Regenerated rice, characterized by single planting and double harvesting, saves labor and costs, significantly contributing to global food security. Hyperspectral imaging technology, which integrates image and spectral data, provides comprehensive, non-destructive, and pollution-free vegetation canopy analysis, making it highly effective for crop nutrient diagnosis. In this study, we selected two varieties of regenerated rice for field trials. Hyperspectral images were captured during key growth stages (flush, grouting, and ripening) of both the first and regenerated seasons. Utilizing a two-dimensional convolutional neural network (2D-CNN) as a deep feature extractor and a fully connected layer for nitrogen content prediction, we developed a robust model suitable for estimating nitrogen content in regenerated rice. The experimental results demonstrate that our method achieves a mean squared error (MSE) of 0.0008, significantly outperforming the back-propagation (BP) network and multiple linear regression by reducing the MSE by 0.0151 and 0.0247, respectively. It also surpasses the one-dimensional convolutional neural network (1D-CNN) by 0.003. This approach ensures accurate nitrogen content prediction throughout the growth cycle of regenerated rice, aiding in yield and economic benefit enhancement. [ABSTRACT FROM AUTHOR]

The phenomenon of leveling off and environmental degradation that occurs as a negative impact of the excessive use of chemical fertilizers and pesticides encourages the development of organic farming systems that can produce crop yields that are not contaminated and free from synthetic chemicals and maintain a healthier environment. The research was conducted from October to December 2022 by taking soil samples from farmers' paddy fields in Tegal Regency using an organic (Cawitali Village) and conventional or non-organic (Jembayat Village) farming system. Composite soil samples were taken from a soil depth of 0 to 20 cm from the soil surface using a soil drill on lowland rice fields with organic farming systems and conventional farming after harvest. The analysis of the chemical properties of the soil carried out was C-organic (Walkley and Black), N-total (Kjeldahl), CEC and soil bases (exch-Ca, exch-Mg, exch-K, and exch-Na), total P (25% HCl) and available P (Bray I), while the observed soil biological properties were the total number of microbial and fungal populations. The results showed that organic paddy soil's chemical and biological properties were relatively higher than conventional paddy soil's. Total fungi in organic lowland soils were lower than in conventional paddy fields. The nutrient status of C-organic and N-total in organic rice fields tended to increase compared to conventional rice fields, namely from very low to low and low to moderate, respectively. In contrast, the other nutrient statuses observed tended to remain relatively unchanged. Generally, soil biological and chemical properties were better in organic farming than in conventional farming systems. [ABSTRACT FROM AUTHOR]

Lindernia dubia (L.) Pennell is a species with invasive behavior outside of its native range of distribution (America), linked mainly to aquatic habitats. This annual species has been acknowledged as a weed in rice paddies in Europe and Asia. Due to the impacts of this invasive plant, some authors have even listed this species as a global invader. The present work focused on spontaneous plant species occurring in seedlings of Typha domingensis Pers. grown in central Spain for the establishment of constructed wetlands. Weed inventory revealed the presence of L. dubia as a dominant spontaneous species in this crop environment. A suite of mesocosm experiments were designed to study the population density of L. dubia versus that of the other dominant plant species, and to determine traits associated with its weedy potential. The results showed that L. dubia presents competitive attributes such as morphological variability, early flowering, long seeding time, short growth cycle, small and light seeds and a high seed production and germination rate (25 °C), meaning a high reproductive capacity in a cycle of about three months for plant growth in non-limiting conditions. The data obtained from this work provide a basis for understanding the weedy potential of L. dubia, and for management decisions of a potentially invasive species, which has been little investigated in Europe [ABSTRACT FROM AUTHOR]

The interconnection between the objectives of territorial development and those of the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, the lack of data creates difficulties for retrospection in rural areas. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous information sources with the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geovisualisations. This virtual environment fostered participation and interactivity, supported by representations of the paleo-landscape (Ottoman period). Furthermore, synergies were achieved between information sources, which were integrated into local spatial systems. The application example involved identifying a rice field that existed between the 15th and 19th centuries in Thessaly, Greece. It is an interesting case because the research results indicated that the location and organisation of the crop, combined with the spatio-temporal coordination required, ensured the sustainable use of natural resources. The interplay between information and communication facilitated community participation and the activation of its collective memory as an information source that enriched the search itself and local intelligence. [ABSTRACT FROM AUTHOR]

The Korean Demilitarized Zone (DMZ) is an area where human disturbance has been strictly restrained for about seven decades since 1953. As a result, compared with rural and urban areas in Korea with similar ecological conditions, the landscape structure of the Korean DMZ today shows a big difference in that it has a riparian forest and lacks any of the artificial landscape elements, such as agricultural and residential areas. The vegetation maps made in the 1950s and those made in recent years of a model site that extends throughout the DMZ, the Civilian Control Zone (CCZ), and adjacent rural areas show that successional changes in the DMZ and CCZ areas are remarkable, while changes in the rural areas are not clear. Rice fields have been replaced by riparian forests, whereas young forests in areas previously subjected to excessive use and pine forests have been replaced by broad-leaved forests. Among the three landscape elements that changed, it was found that riparian zones, where natural disturbance is usually frequent, could mitigate the impacts of human disturbance and restore the original features of nature sooner than any other elements. The results of analyses on landscape change that focused on rice fields before the Korean War also showed similar results: most of these fields had turned into riparian vegetation. Stand ordination of riparian vegetation investigated in the CCZ, rural areas, and urban areas showed clear differences in species composition and diversity among regions. In this study, we confirmed the passive restoration of the Korean DMZ and CCZ through natural regeneration processes as a result of restricted human disturbance over a period of about seven decades. [ABSTRACT FROM AUTHOR]

Rice is a globally important food crop, and it is crucial to accurately and conveniently obtain information on rice fields, understand their spatial patterns, and grasp their dynamic changes to address food security challenges. In this study, Chongqing's Yongchuan District was selected as the research area. By utilizing UAVs (Unmanned Aerial Vehicles) to collect multi-spectral remote sensing data during three seasons, the phenological characteristics of rice fields were analyzed using the NDVI (Normalized Difference Vegetation Index). Based on Sentinel data with a resolution of 10 m, the NDVI difference method was used to extract rice fields between 2019 and 2023. Furthermore, the reasons for changes in rice fields over the five years were also analyzed. First, a simulation model of the rice harvesting period was constructed using data from 32 sampling points through multiple regression analysis. Based on the model, the study area was classified into six categories, and the necessary data for each region were identified. Next, the NDVI values for the pre-harvest and post-harvest periods of rice fields, as well as the differences between them, were calculated for various regions. Additionally, every year, 35 samples of rice fields were chosen from high-resolution images provided by Google. The thresholds for extracting rice fields were determined by statistically analyzing the difference in NDVI values within the sample area. By utilizing these thresholds, rice fields corresponding to six harvesting regions were extracted separately. The rice fields extracted from different regions were merged to obtain the rice fields for the study area from 2019 to 2023, and the accuracy of the extraction results was verified. Then, based on five years of rice fields in the study area, we analyzed them from both temporal and spatial perspectives. In the temporal analysis, a transition matrix of rice field changes and the calculation of the rice fields' dynamic degree were utilized to examine the temporal changes. The spatial changes were analyzed by incorporating DEM (Digital Elevation Model) data. Finally, a logistic regression model was employed to investigate the causes of both temporal and spatial changes in the rice fields. The study results indicated the following: (1) The simulation model of the rice harvesting period can quickly and accurately determine the best period of remote sensing images needed to extract rice fields. (2) The confusion matrix shows the effectiveness of the NDVI difference method in extracting rice fields. (3) The total area of rice fields in the study area did not change much each year, but there were still significant spatial adjustments. Over the five years, the spatial distribution of gained rice fields was relatively uniform, while the lost rice fields showed obvious regional differences. In combination with the analysis of altitude, it tended to grow in lower areas. (4) The logistic regression analysis revealed that gained rice fields tended to be found in regions with convenient irrigation, flat terrain, lower altitude, and proximity to residential areas. Conversely, lost rice fields were typically located in areas with inconvenient irrigation, long distance from residential areas, low population, and negative topography. [ABSTRACT FROM AUTHOR]

In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which greatly affects the operational performance and harvesting efficiency of crawler combine harvesters. To address this issue, this paper proposes a high-traction track grouser based on the structure of an ostrich's foot sole. First, a traction force mathematical model is constructed to analyze the interaction between a track grouser and wet and soft rice fields, and parameter optimization is conducted. Then, the bionic information of a dung beetle's non-smooth body surface is extracted, and the surface of the track is designed with biomimetic convex hull patterns based on the geometric similarity principle and adhesive experiments. Finally, the analysis results indicate that the optimized track grouser significantly improved the traction of the track in wet and soft rice fields. For the track plate with a bionic desorption convex hull pattern, a convex hull diameter of 6 mm, convex hull spacing of 8.25 mm, and convex hull height of 3 mm led to good adhesion reduction and desorption effects in wet and soft soil. [ABSTRACT FROM AUTHOR]

Comprehending the impacts of land-use type on soil nutrition and stoichiometry in watersheds is crucial for effective regional ecosystem management. However, a deeper understanding of the influence of land-use type on soil stoichiometry in karst agricultural watersheds is still lacking. Here, we analyzed the contents, stoichiometries, and drivers of topsoil C, N, and P in a karst agricultural watershed in China, focusing on six land-use types: paddy fields, dry farmland, tussock land, shrubland, shrubby tussock land, and woodland. We found that woodland exhibited significantly higher soil organic carbon (SOC) content than other land-use types except shrubland. Moreover, woodland exhibited the highest total nitrogen (TN) and total phosphorus (TP) contents compared with other land-use types. C/N and N/P ratios did not vary significantly with land-use type, whereas dry farmland (18.68) showed a significantly lower C/P ratio than woodland (39), shrubland (39.92), and paddy fields (34.87). In addition, our results revealed that soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced C, N, and P content and stoichiometry. These findings reveal that interactions between multiple biotic and abiotic factors drive variability in soil stoichiometry, offering valuable insight for land improvement and ecological management in karst agricultural watersheds. [ABSTRACT FROM AUTHOR]

Bioorganic fertilizer (BOF) represents favorable potential for agricultural production, but the safe and residual effects of BOF application in heavy-metal-contaminated soils still remain unclear. A two-year field experiment of four rice-growing cycles were conducted to study the effects of the one-time addition of BOF (low and high dosages, 0.45 and 0.9 kg/m2, namely, BOF1 and BOF2, respectively) on the lead (Pb) and arsenic (As) accumulations in brown rice, rice yield, and soil properties in an acidic and Pb-As-contaminated paddy field. The results show that BOF application enhanced the rice yields by 7.9–25.5% and increased the soil pH, organic carbon contents, and fluorescein diacetate hydrolase activity in the former two rice-growing cycles, while these attributes declined gradually and were not significant in the last two cycles. The soil bulk density decreased marginally due to the BOF. Furthermore, the BOF1 treatment barely affected the rice Pb and As concentrations during all cycles, whereas the BOF2 treatment clearly increased the Pb concentrations in brown rice, exceeding the food quality standard limit of 0.2 mg/kg in the last three cycles, and slightly increased the rice As in the former three cycles. The BOF effects on Pb and As in brown rice were due to the changes in the available soil Pb and As, respectively. Our results indicate that a one-time application of BOF could ameliorate the soil conditions of rice growth in two rice-growing cycles, while the high-dose BOF seemed undesirable in toxic-metal-contaminated soils. BOF application at the rate of 0.45 kg/m2 per annum may be a potential strategy for safe rice production in Pb-As-contaminated fields. [ABSTRACT FROM AUTHOR]

The substitution of chemical fertilizers with organic manure plays a critical role in sustainable crop production. Nevertheless, organic amendments promote the global warming potential (GWP) in rice paddies due to increased methane (CH4) emissions. Increasing evidence shows that lime application can reduce CH4 emissions from acidic paddy soils; however, it is still not clear whether liming can reduce the GWP in rice fields under organic manure substitution. A two-year field experiment was conducted to investigate the impacts of pig manure substitution and lime application on grain yield, CH4 and nitrous oxide (N2O) emissions in a subtropical double-cropped rice field in China. The experiment consisted of three treatments: CF (100% chemical nitrogen fertilizer), 1/2N + M (50% of the applied nitrogen substituted by pig manure, M represents manure), and 1/2N + M + L (lime amendment with 50% of the applied nitrogen substituted with pig manure, L represents lime). On average, 1/2N + M reduced rice yield by 5.65% compared to CF, while the lime application had no effect on rice yield. Mean cumulative CH4 emissions were 218.8% higher in 1/2N + M than in CF, whereas 1/2N + M + L reduced CH4 emissions by 36.6% compared to 1/2N + M. Neither pig manure substitution nor lime application affected N2O emissions. Consequently, 1/2N + M increased the GWP and greenhouse gas intensity (GHGI) by 214.6% and 228.3%, respectively, compared to CF. In contrast, 1/2N + M + L reduced the GWP and GHGI by 36.4% and 36.5% compared to 1/2N + M. Lime application can mitigate CH4 emissions and GWP induced by pig manure amendment in double-cropped rice fields. [ABSTRACT FROM AUTHOR]