Search Results (10)

Pollination is the rate-limiting reproductive step in dioecious fruit crops. However, the developmental pathway through which pollination interventions translate into fruit weight remains unclear. Here, we tested whether seed set was the dominant pathway linking three pollination methods, namely, artificial pollination (AP), pollen dispenser-assisted bee pollination (BTD), and bee-only pollination (BT), to fruit weight and soluble solids content (SSC) in gold kiwifruit (Actinidia chinensis cv. ‘Haegeum’). A total of 2940 individually measured fruits were collected across two orchards in southern Korea (2018–2025), comprising 2022 main experiment (n = 1800), supporting trials (2018–2020, N = 540, including a six-treatment factorial design in 2020), and a 2025 replication of 600 fruits. Across the calibration range (seed number 100–700), each additional seed contributed 0.063–0.072 g of fruit weight (R² = 0.68–0.72). The slopes were statistically indistinguishable among AP, BTD, and BT. Mediation analysis was triangulated through three estimators: partial correlation (49.8–63.1% mediation), product-of-coefficients with 10,000 bootstrap resamples (70.3–77.4% indirect-effect mediation), and model-free stratification that converged on the same conclusion. When seed number was matched (500–700 range), treatment differences in fruit weight collapsed to non-significance (F = 0.34, p = 0.714). The two mediation percentages reflect different denominators, that is, standardised association vs. unstandardised total effect, and both estimators agree qualitatively. SSC was not mediated by the seed number (<8%). The small residual SSC pattern may reflect block-level confounding rather than a method-intrinsic effect. A random-effects meta-analysis across six-year site combinations returned pooled Hedges’ g = +0.43 (95% CI: −0.02 to +0.89, I² = 95.1%), with two years in which BTD significantly exceeded AP. In 2025, BTD achieved the Ferguson (1984) ≥1000-seed commercial standard in 79% of fruits. These findings identify the seed set as a method-independent reproductive bottleneck, reframing pollination system evaluation around pollen deposition-to-seed set conversion rather than around the delivery mechanism and support an efficiency-focused approach to orchard pollination management. Full article

The study of genetic effects induced by low-dose alpha radiation associated with radon and its decay progeny is critically important for assessing radiation risks in regions with elevated natural background levels. The aim of this study was to evaluate the mutagenic effects (in germline cells) and teratogenic effects (in somatic tissues) of alpha radiation using the D. melanogaster model. To differentiate between these effects, teratogenic outcomes were analyzed in directly exposed individuals (phenotypic analysis of adults that developed from irradiated larvae), whereas mutagenic effects were assessed in the progeny of irradiated flies. Larvae and adult flies were exposed to calibrated alpha-particle sources with energies ranging from 4.8 to 7.7 MeV and absorbed doses of 1.90–44.96 mGy. The results demonstrated a statistically significant increase in the frequency of morphological abnormalities in the exposed groups, including melanotic masses and deformities of the wings, thorax, and tergites. Under 72 h exposure, a strong correlation between absorbed dose and abnormality frequency was observed (r = 0.98). In the reporter system, induction of GFP expression was detected in imaginal discs at doses above 10 mGy, indicating threshold activation of the cellular stress response. The obtained data demonstrate that chronic low-dose α-irradiation leads to an increased frequency of morphological abnormalities (indirect phenotypic manifestations of compromised genetic stability) in D. melanogaster, with the most pronounced effects observed at the level of morphogenesis. The high sensitivity of the applied test systems was confirmed, supporting the use of D. melanogaster as a bioindicator for ecogenetic monitoring of radon-prone areas, including regions of Kazakhstan. Full article

A robust analysis of water use in major food production systems is crucial for improving their productivity and sustainability in water-scarce arid and semi-arid regions like Punjab (India) facing the depletion of groundwater resources. This study aimed to assess blue water use and blue water productivity in dairy farming systems across different farm sizes in Punjab. Comprehensive monitoring and assessment of water use over a full year (from July 2022 to June 2023) was conducted on 24 dairy farm sheds in Punjab, revealing significant variability in their blue water use (measured in L per adult animal per day) and blue water productivity quantified as kg of fat- and protein-corrected milk (FPCM) produced per m³ of the blue water consumed. The variability was influenced by factors such as livestock species, farm size (medium with 15–25 livestock, large with 25–100 livestock, and commercial with >100 livestock), bathing and servicing routines, and energy use patterns. The average dairy livestock total blue water consumption varied from 112 ± 14 to 131 ± 19 L per adult animal per day, with 20–40% higher livestock drinking water and about six times higher livestock bathing and serving water used during the summer months. Interestingly, a large share (45%) of the average total blue water consumption is contributed by indirect water consumption via the use of energy (electricity and diesel) in dairy farm sheds. Dairy milk blue water productivity was quantified higher, ranging from 154 ± 11 to 225 ± 59 kg FPCM per m³ in buffalo- and crossbred cattle-based dairy farm sheds. However, indigenous cattle showed a lower blue water productivity ranging from 56 to 97 kg FPCM per m³, reflecting their lower milk yields and limited use of intensified management practices. The state-level water scarcity footprint (WSF) of Punjab dairy farm sheds was quantified at 4870 million m³ world-eq, which showed a significant spatial variation among Punjab districts. However, the results of this study offer novel seasonally and spatially disaggregated benchmarks of blue water consumption, blue water productivity, and the water scarcity footprint of Punjab’s dairy farming sheds. This new information is crucial for the development of locally calibrated and validated models for improving the water productivity and sustainability of dairy farming across Punjab and other similar arid and semi-arid regions in Southeast Asian countries. Full article

Satellite remote sensing has become essential for water quality assessment across inland and coastal environments, with rapid improvements in recent years. Significant advances have been made in detecting optically active parameters (such as chlorophyll-a, suspended matter, and turbidity), showing consistently strong performance across multiple studies. Specifically, the median validation performance (R²) derived from the quantitative synthesis indicates R² = 0.82 for chlorophyll-a (interquartile range—IQR: 0.75–0.90), R² = 0.80 for total suspended matter (IQR: 0.78–0.85), and R² = 0.88 for turbidity (IQR: 0.85–0.90). Conversely, the retrieval of optically inactive parameters (such as nutrients like total phosphorus and total nitrogen) remains more context dependent. It exhibits moderate, more variable results, with median R² = 0.68 (IQR: 0.64–0.74) for total phosphorus and R² = 0.75 (IQR: 0.70–0.80) for total nitrogen. These findings clearly illustrate the varying success of retrievals of optically active and inactive parameters and underscore the inherent difficulties of indirect estimation methods. However, high reported accuracy has yet to translate into transferable, uncertainty-informed, and operational monitoring systems. This gap stems from structural issues in validation design, physics integration, uncertainty management, and multi-sensor compatibility rather than data limitations alone. We present a PRISMA-guided, distribution-aware quantitative synthesis of 152 peer-reviewed studies (1980–2025), based on a systematic search protocol, to evaluate satellite-based retrievals of both optically active and inactive parameters. Instead of simply averaging performance, we analyse the empirical distributions of validation metrics, considering the validation protocol, sensor type, parameter category, degree of physics integration, and uncertainty quantification. The synthesis demonstrates that validation strategy often influences reported results more than the algorithm class itself, with accuracy inflated under non-independent cross-validation methods and notable variability between studies concealed by mean-based reports. Across four decades, four persistent structural challenges remain: limited transferability across sites and sensors beyond calibration areas; weak or implicit physical integration in many data-driven models; lack of or inconsistency in uncertainty quantification; and fragmented multi-sensor harmonisation that restricts operational scalability. To address these issues, we introduce two evidence-based coding frameworks: a physics-integration taxonomy (P0–P4) and an uncertainty-quantification hierarchy (U0–U4). Applying these frameworks shows that most studies remain focused on low-to-moderate levels of physics integration and primarily consider uncertainty at the prediction stage, with limited attention to upstream sources throughout the observation and inference process. Building on this structured synthesis, we propose a transferable, physics-informed, and uncertainty-aware conceptual framework that links model architecture, validation robustness, and probabilistic uncertainty to well-founded design principles. By shifting satellite water quality modelling from isolated algorithm demonstrations towards integrated, evidence-based system design, this study promotes scalable, decision-grade environmental monitoring amid the accelerating impacts of climate change. Full article

Background: Antinuclear antibodies (ANAs) play a crucial role in diagnosing systemic autoimmune rheumatic diseases, particularly systemic lupus erythematosus. The recommended standard for ANA detection is indirect immunofluorescence testing (IIFT) using human epithelial (HEp-2) cells. Since visual interpretation (VI) of IIFT images is time-consuming and labor-intensive, research is focusing on automated interpretation systems that use artificial intelligence (AI). Methods: Consecutive serum samples (number of sera = 143) from routine clinical care were collected from patients visiting our tertiary rheumatology center. ANA were detected by IIFT with visual interpretation and compared with IIFT using the AI-based interpretation system akiron^® NEO (Medipan, 15827 Blankenfelde-Mahlow, Germany). ANA titer levels and patterns were analyzed according to the Competent Level of the International Consensus on ANA Pattern classification. Results: Agreement of positive/negative ANA discrimination between AI-aided and VI-IIFT at the recommended cut-off of 80 was good (Cohen’s kappa [κ] 0.69) but significantly different (McNemar test, p < 0.0001). At a cut-off of ≥1/80, the agreement was improved (κ 0.76) and the difference between both methods was non-significant (p = 1.0000). The ANA pattern recognition agreement between both approaches was moderate (κ = 0.54). The direct comparison using only the akiron^® NEO HEp-2 cell ANA assay revealed a good agreement (0.67), which improved to very good (κ = 0.80) when differences between ANA patterns anti-cell (AC)4/5 and AC2 were neglected. Notably, titer levels in the automated evaluations were frequently assessed at higher values than in the gold standard interpretation. Conclusions: Our study demonstrates a good agreement for positive/negative ANA discrimination. ANA pattern recognition by AI-aided interpretation showed moderate to very good agreement with VI. Further research and algorithm refinement (e.g., improved pattern recognition and titer calibration) are necessary to support its future implementation as a reliable screening method. Full article

In this paper, a calibration method for gyro bias that changes depending on the position of the IMU (inertial measurement unit) is proposed to improve the navigation performance of RLG-based RINS (ring-laser-gyro-based rotational inertial navigation system). RINS is a navigation device that compensates for the inertial sensor errors by utilizing the rotation of the IMU. In previous studies, the rotation scheme of the IMU is designed assuming that inertial sensor errors are not affected by position of the IMU. However, changes in temperature distribution, direction of gravity, and dithering according to the rotation of the IMU affect the inertial sensor errors, such as gyro bias. These errors could degrade the long-term navigation performance of RLG-based RINS. To deal with this problem, this paper proposed a compensation method of the gyro bias that changes depending on the position of the IMU. First, RINS is reviewed using a dual-axis 16-position rotation scheme and RLG. Next, the attitude error of RLG-based RINS is derived utilizing navigation equations. The effect of the gyro bias change caused by the change in the IMU attitude for the navigation performance of RINS is analyzed based on navigation equations and simulations. Finally, system-level indirect calibrations for the Z–axis up position and Z–axis down position are performed to calculate the gyro bias change caused by the IMU attitude. The accuracy of the proposed calibration method is verified by long-term navigation test. The test results show that the proposed calibration method improves the navigation performance of RINS compared with the conventional calibration method. Full article

Grain loss in the harvesting process of combine harvesters not only causes economic losses to farmers but also affects the soil environment because of the lost grain covering the soil, influencing crop growth in the next season. Grain sieve loss-monitoring sensors represent an important accessory in combine harvesters, as they can not only provide current grain loss levels for the operator to adopt a rational action in time but also serve as an important performance signal for the control system. To reflect the rice grain sieve loss level of combine harvesters in real time, an indirect grain sieve loss-monitoring system is proposed in this paper. First, the grain collision rise time was obtained by the finite element method (FEM), and the parameters of the grain loss sensor signal processing circuit were determined accordingly to upgrade the monitoring accuracy. Then, grain loss distribution behind the cleaning shoe was analyzed in detail under different working parameters. Grain loss distribution functions at the end of the sieve and a monitoring mathematical model with relevant variables were established based on the laboratory experiment results. Finally, calibration experiments were carried out to verify the measurement accuracy of the sensor on a cleaning test bench, with an obtained relative monitoring error ≤6.41 % under different working conditions. Full article

Evapotranspiration (ET) is a key variable in the hydrological cycle and it directly impacts the surface balance and its accurate assessment is essential for a correct water management. ET is difficult to measure, since the existing methods for its direct estimate, such as the weighing lysimeter or the eddy-covariance system, are often expensive and require well-trained research personnel. To overcome this limit, different authors developed experimental models for indirect estimation of ET. However, since the accuracy of ET prediction is crucial from different points of view, the continuous search for more and more precise modeling approaches is encouraged. In light of this, the aim of the present work is to test the efficiency in predicting ET fluxes in a newly introduced physical-based model, named Prospero, which is based on the ability to compute the ET using a multi-layer canopy model, solving the energy balance both for the sunlight and shadow vegetation, extending the recently developed Schymanski and Or method to canopy level. Additionally, Prospero is able to compute the actual ET using a Jarvis-like model. The model is integrated as a component in the hydrological modelling system GEOframe. Its estimates were validated against observed data from five Eddy covariance (EC) sites with different climatic conditions and the same vegetation cover. Then, its performances were compared with those of two already consolidated models, the Priestley–Taylor model and Penman FAO model, using four goodness-of-fit indices. Subsequently a calibration of the three methods has been carried out using LUCA calibration within GEOframe, with the purpose of prediction errors. The results showed that Prospero is more accurate and precise with respect to the other two models, even if no calibrations were performed, with better performances in dry climatic conditions. In addition, Prospero model turned to be the least affected by the calibration procedure and, therefore, it can be effectively also used in a context of data scarcity. Full article

The assessment of already installed anchorages for a possible exceeding of the service load level is a question that is gaining more and more importance, especially in building maintenance. Bonded anchors are of particular interest here, as the detection of a capacity reduction or load exceedance can cause damage to the concrete-bonded mortar behavior. This article investigates the extent to which ultrasonic methods can be used to make a prediction about the condition of anchorages in concrete and about their load history. A promising innovative assessment method has been developed. The challenges in carrying out the experimental investigations are the arrangement of the transducers, the design of the test set-up and the applicability of direct, indirect or semidirect ultrasonic transmission. The experimental investigations carried out on a test concrete mix and a bonded anchor system show that damage to the concrete structure can be detected by means of ultrasound. The results indicate the formation of cracks and therefore a weakening of the response determined by means of direct, indirect and semidirect ultrasonic transmission. However, for application under non-laboratory conditions and on anchors with unknown load history, the calibration with a reference anchor and the identification of the maximum load is required. This enables a referencing of the other loaded anchors to the unloaded conditions and allows an estimation of the load history of individual anchors. Full article

High-quality inner FoV (Field of View) stitching is currently a prerequisite step for photogrammetric processing and application of image data acquired by spaceborne TDI CCD cameras. After reviewing the technical development in the issue, we present an inner FoV stitching method based on sensor geometry and projection plane in object space, in which the geometric sensor model of spaceborne TDI CCD images is used to establish image point correspondence between the stitched image and the TDI CCD images, using an object-space projection plane as the intermediary. In this study, first, the rigorous geometric sensor model of the TDI CCD images is constructed. Second, principle and implementation of the stitching method are described. Third, panchromatic high-resolution (HR) images of ZY-1 02C satellite and triple linear-array images of ZY-3 satellite are utilized to validate the correctness and feasibility of the method. Fourth, the stitching precision and geometric quality of the generated stitched images are evaluated. All the stitched images reached the sub-pixel level in precision. In addition, the geometric models of the stitched images can be constructed with zero loss in geometric precision. Experimental results demonstrate the advantages of the method for having small image distortion when on-orbit geometric calibration of satellite sensors is available. Overall, the new method provide a novel solution for inner FoV stitching of spaceborne TDI CCD images, in which all the sub-images are projected to the object space based on the sensor geometry, performing indirect image geometric rectification along and across the target trajectory. At present, this method has been successfully applied in the daily processing system for ZY-1 02C and ZY-3 satellites. Full article