Search Results (342)

Introduction: Vitamin D deficiency, a reversible cause of osteoporosis, is increasingly prevalent, showing varying degrees of severity that are notably pronounced among the growing population of multimorbid elderly patients. Given that the aging pancreas undergoes senescent processes leading to impaired function—which negatively impacts enteral vitamin D absorption and, consequently, elderly bone metabolism—a specific diagnostic and treatment approach is crucial. Our study aimed to determine the prevalence of vitamin D deficiency and exocrine pancreatic insufficiency (EPI) in orthogeriatric patients. We also evaluated differences in vitamin D deficiency severity between patients with normal and impaired pancreatic function. Furthermore, a short-term monitoring of vitamin D level increases after 12 days of substitution therapy in both groups aimed to inform osteoanabolic therapy for specific high-fracture-risk patients, assessing the influence of pancreatic function on substitution efficacy. Methods: We conducted a retrospective, monocentric cohort study, evaluating data from all patients hospitalized with manifest osteoporosis in an orthogeriatric department during a six-month spring/summer period. Demographic data, relevant comorbidities, the type of fracture, the amount of faecal elastase 1 (CALEX^® Cap Bühlmann), and the serum levels of 25-hydroxyvitamin D (25(OH)D) were assessed. Results: We found a high prevalence (70.6%) of vitamin D deficiency (25(OH)D < 30 µg/L) among all orthogeriatric patients. Of these, 16% met the criteria for mild to severe EPI. The group with normal exocrine pancreatic function showed a higher average vitamin D value, and their increase in vitamin D levels following short-term substitution was up to 100% greater compared to the group with impaired pancreatic function. Notably, 69% of women and 20% of men met the therapeutic threshold for specific osteoanabolic osteoporosis therapy, even without a T-score. Conclusions: Our findings reveal a very high prevalence of vitamin D deficiency and a high prevalence of EPI in orthogeriatric patients. Those with impaired exocrine pancreatic function exhibit lower baseline vitamin D levels and a diminished capacity for vitamin D absorption during short-term monitoring. These results have significant clinical implications for osteoporotic therapy, given that a substantial proportion of patients, particularly women, meet the criteria for specific osteoanabolic treatment. Full article

The petiole nitrate–nitrogen concentration (PNNC) has been an industry standard indicator for in-season potato (Solanum tuberosum L.) nitrogen (N) status diagnosis. Leaf sensors can be used to predict the PNNC and other N status indicators non-destructively. The SPAD meter is a common leaf chlorophyll (Chl) meter, while the Dualex is a newer leaf fluorescence sensor. Limited research has been conducted to compare the two leaf sensors for potato N status assessment. Therefore, the objectives of this study were to (1) compare SPAD and Dualex for predicting potato N status indicators, and (2) evaluate the potential prediction improvement using multi-source data fusion. The plot-scale experiments were conducted in Becker, Minnesota, USA, in 2018, 2019, 2021, and 2023, involving different cultivars, N treatments, and irrigation rates. The results indicated that Dualex’s N balance index (NBI; Chl/Flav) always outperformed Dualex Chl but did not consistently perform better than the SPAD meter. All N status indicators were predicted with significantly higher accuracy with multi-source data fusion using machine learning models. A practical strategy was developed using a linear support vector regression model with SPAD, cultivar information, accumulated growing degree days, accumulated total moisture, and an as-applied N rate to predict the vine or whole-plant N nutrition index (NNI), achieving an R² of 0.80–0.82, accuracy of 0.75–0.77, and Kappa statistic of 0.57–0.58 (near-substantial). Further research is needed to develop an easy-to-use application and corresponding in-season N recommendation strategy to facilitate practical on-farm applications. Full article

Climate variations impact the preservation of heritage buildings, necessitating a strategic understanding of potential effects to effectively guide preservation efforts. This study analyzes temperature- and precipitation-dependent climate-heritage indices in Trentino–South Tyrol using EURO-CORDEX regional climate models for the period 1971–2100 under RCP 4.5 and RCP 8.5 scenarios. The selected indices were calculated with climdex-kit and relied on bias-adjusted temperature and precipitation data with a 1 km spatial resolution. The obtained results indicate a geographically punctuated increase in biomass accumulation on horizontal surfaces, a slight decreasing trend in freeze–thaw events, an increase in growing degree days indicating a small, heightened insect activity, and a rise in heavy precipitation days. The Scheffer Index shows a significantly increased potential for wood degradation, particularly under the RCP 8.5 scenario, while the Wet-Frost Index remains consistently low. Finally, according to each identified hazard, adaptive solutions are suggested. These findings provide critical insights into future climate impacts on heritage buildings in the region, aiding stakeholders in planning targeted interventions. The study emphasizes the crucial role of integrating detailed climate data into heritage preservation strategies, advocating for the inclusion of future risk analysis in the “knowledge path” in order to enhance the resilience of buildings. Full article

This study investigates the environmental regulation of sex expression and seed yield stability in four Thai dioecious hemp (Cannabis sativa L.) cultivars (RPF1, RPF2, RPF3, and RPF4) under different seasonal conditions to optimize seed production. The experiment was conducted across two planting periods (in-season and off-season) to evaluate the effects of varying day lengths and temperatures on growth, reproductive development, and yield. The results showed that shorter day lengths and lower temperatures during the off-season led to an increased proportion of female plants across all cultivars, except RPF3, which exhibited a stable female-to-male ratio. RPF4 had the highest increase in female plants (16%), followed by RPF1 and RPF2 (10%). Seed yield was significantly influenced by seasonal changes, with RPF3 and RPF4 consistently outperforming the other cultivars. In the in-season, RPF3 and RPF4 produced the highest seed yields, reaching 83.4 g/plant and 81.6 g/plant, respectively. During the off-season, both cultivars experienced a decline in seed yield (by 24–26%), primarily due to a reduction in seed production in secondary inflorescences. However, RPF3 compensated for this loss with a 31% increase in seed production at main inflorescences, ensuring yield stability. RPF4 maintained its high yield potential by increasing the proportion of female plants, offsetting the decline in seed yield per plant. Additionally, cumulative growing degree days (CGDD) at harvest were comparable between seasons, with values of 2434 °Cd (in-season) and 2502 °Cd (off-season), indicating that temperature accumulation remained within an optimal range for seed maturation. The study highlights the importance of cultivar selection based on yield component stability and adaptability to seasonal variations. These findings provide valuable insights for improving hemp seed production strategies in Thailand’s diverse agro-climatic conditions. Full article

The production of winter wines in Southeastern Brazil represents a relatively recent but expanding viticultural approach, with increasing adoption across diverse wine-growing regions. This system relies on the double-pruning technique, which allows for the harvest of grapes during the dry and cooler winter season, favoring a greater accumulation of sugars, acids, and phenolic compounds. This study aimed to characterize the phenological stages, thermal requirements, yield, and fruit quality of the fine wine grape cultivars ‘Sauvignon Blanc’, ‘Merlot’, ‘Tannat’, ‘Pinot Noir’, ‘Malbec’, and ‘Cabernet Sauvignon’ under double-pruning management in a subtropical climate. The vineyard was established in 2020, and two production cycles were evaluated (2022/2023 and 2023/2024). Significant differences in the duration of phenological stages were observed among cultivars, ranging from 146 to 172 days from pruning to harvest. The accumulated thermal demand was higher in the first cycle, with a mean of 1476.9 growing degree days (GDD) across cultivars. The results demonstrate the potential of Vitis vinifera L. cultivars managed with double pruning for high-quality wine production under subtropical conditions, supporting the viability of expanding viticulture in the state of São Paulo. ‘Cabernet Sauvignon’ and ‘Sauvignon Blanc’ showed the highest yields, reaching 3.03 and 2.75 kg per plant, respectively, with productivity values of up to 10.8 t ha⁻¹. ‘Tannat’ stood out for its high sugar accumulation (23.4 °Brix), while ‘Merlot’ exhibited the highest phenolic (234.9 mg 100 g⁻¹) and flavonoid (15.3 mg 100 g⁻¹) contents. These results highlight the enological potential of the evaluated cultivars and confirm the efficiency of the double-pruning system in improving grape composition and wine quality in non-traditional viticultural regions. Full article

Climate variability, intensified by climate change, poses significant challenges to agriculture, affecting crop development and productivity. Integrating seasonal weather forecasts (SWF) into crop growth modelling tools is therefore essential for improving agricultural decision-making. This study assessed the uncertainties of raw (non-bias-corrected) temperature forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) SEAS5 seasonal (seven-month forecasts) to estimate the spring–summer maize, melon, sunflower, and tomato crops cycle from 2013 to 2022 in the Caia Irrigation Scheme, southern Portugal. AgERA5 reanalysis data, after simple bias correction using local weather station data, was used as a reference. The growing degree-day (GDD) approach was applied to estimate the crop cycle duration, which was then validated against ground truth and satellite data. The results show that SWF tend to underestimate maximum temperatures and overestimate minimum temperatures, with these biases partially offsetting to improve mean temperature accuracy. Forecast skill decreased non-linearly with lead time, especially after the second month; however, in some cases, longer lead times outperformed earlier ones. Temperature forecast biases affected GDD-based crop cycle estimates, resulting in a slight underestimation of all crop cycle durations by around a week. Nevertheless, the forecasts captured the overall increasing temperature trend, interannual variability, and anomaly signals, but with marginal added value over climatological data. This study highlights the potential of integrating ground truth and Earth observation data, together with reanalysis data and SWF, into GDD tools to support agricultural decision-making, aiming at enhancing yield and resources management. Full article

Soybean, a globally important food and oil crop, requires accurate estimation of above-ground biomass (AGB) to optimize management and prevent yield loss. Despite the availability of various remote sensing methods, systematic research on effectively integrating canopy height (CH) and spectral information for improved AGB estimation remains insufficient. This study addresses this gap using drone data. Three CH utilization approaches were tested: (1) simple combination of CH and spectral vegetation indices (VIs), (2) fusion of CH and VI, and (3) integration of CH, VI, and growing-degree days (GDDs). The results indicate that adding CH always enhances AGB estimation which is based only on VIs, with the fusion approach outperforming simple combination. Incorporating GDD further improved AGB estimation for highly accurate CH data, with the best model achieving a root mean square error (RMSE) of 87.52 ± 5.88 g/m² and a mean relative error (MRE) of 28.59 ± 1.99%. However, for the multispectral data with low CH accuracy, the VIs + GDD fusion (RMSE = 92.94 ± 6.84 g/m², MRE = 30.08 ± 2.29%) surpassed CH + VIs + GDD (RMSE = 97.99 ± 6.71 g/m², MRE = 31.41 ± 2.56%). The findings highlight the role of CH accuracy in AGB estimation and validate the value of growth-stage information in robust modeling. Future research should prioritize the refining of CH prediction and the optimization of composite variable construction to promote the application of this approach in agricultural monitoring. Full article

In the context of climate change and the development of sustainable agricultural, crop yield prediction is key to ensuring food security. In this study, long-term vegetation and meteorological indices were obtained from the MOD09A1 product and daily weather data. Three types of time series data were constructed by aggregating data from an 8-day period (DP), 9-month period (MP), and six growth periods (GP). And we developed the yield prediction model by using random forest (RF) and long short-term memory (LSTM) networks. Results showed that the average root mean squared error (RMSE) of the RF model in each province was 0.5 Mg/ha lower than that of the LSTM model. Both the RF and LSTM prediction accuracies increased with the later growth stages data. Partial dependence plots showed that the influence degree of DVI on yield was above 2 Mg/ha. When the time length of the feature variables was shortened to MP or GP, the growing degree days (GDD), average minimum temperature (AveTmin), and effective precipitation (EP) showed stronger nonlinear relationships with the statistical yields. Full article

German chamomile (Matricaria chamomilla L.) is a suitable medicinal and aromatic crop to cultivate in diverse regions, but its relationship with weather is a major concern in evaluating the development and crop production in the Western Himalayan region. Thus, a field experiment was executed for two years (2018–2019 and 2019–2020) at CSIR-Institute of Himalayan Bioresource Technology, Palampur, India, to evaluate the crop weather relationship studies and different phenological phases of German chamomile under acidic soil conditions of mid hills of Western Himalaya. Agrometeorological indices were worked out for four different sowing times from 20 November to 20 January with foliar application of elicitor, i.e., salicylic acid at three levels (viz., SA0: 0 mg/L, SA1: 25 mg/L, SA2: 50 mg/L). The results revealed that the number of days required for attaining each phenological stage decreased with a delay in sowing time. Higher growing degree days (GDDs), photothermal units (PTUs) and heliothermal units (HTUs) were accumulated for early sowing of 20 November and showed a gradual decrease with delayed sowing. Salicylic acid application produced a significant effect on the accumulation of agrometeorological indices, irrespective of the applied doses, and showed irregularity. Higher accumulation of GDDs, PTUs, and HTUs is associated with higher flower and essential oil yield; thus, the results showed that agrometeorological indices are associated with the production of German chamomile. Full article

Applying a top dressing of nitrogen fertilizer before harvesting spring tea is vital for producing high-quality spring tea. However, the interaction between the sprouting phenological characteristics of various cultivars and the timing of top dressing remains unclear. A field trial was conducted to investigate such interaction. Urea enriched with ¹⁵N was applied to soil of the early-sprouting cultivar Jia-ming-1 (JM1) and the late-sprouting cultivar Tie-guan-yin (TGY) on 29 January (early application, EApp) or 10 March (late application, LApp), respectively. The bud density and yield of young spring shoots were significantly decreased in LApp compared to EApp. Such differences were more remarkable in the early-sprouting cultivar (JM1) than in the late-sprouting cultivar (TGY). The N_dff (N derived from ¹⁵N-enriched urea) in mature leaves and young spring shoots as well as the amount of ¹⁵N in young spring shoots were all higher in EApp than in LApp. N_dff in both mature leaves (R² = 0.99, p < 0.001) and young spring shoots (R² = 0.61–0.89, p < 0.01) could be well predicted by the growing degree days of the duration between the N fertilization and sampling. N_dff and ¹⁵N concentrations in mature leaves were significantly correlated with the content of nitrate and the ratio of ammonium to total inorganic nitrogen. Partial least squares path modeling revealed that thermal condition directly affected soil N supply and soil pH and thereby affected N_dff in mature leaves and young spring shoots. Our findings highlight the importance of early pre-spring topdressing of N fertilizer to improve the yield and N use efficiency of spring tea in both early- and late-sprouting tea cultivars. The work identified a synergistic effect of N uptake by tea plants, N transformation, and soil pH related to the thermo-conditions of early and late N topdressing. Full article

The cultivation of table grapes in Brazil is economically significant, with production influenced by edaphoclimatic factors and rootstock selection. The cultivar ‘BRS Núbia’ (Vitis vinifera L. x Vitis labrusca L.) is a promising alternative; however, its phenological behavior, thermal requirements, and compatibility with different rootstocks under subtropical conditions require further evaluation. This study aimed to assess the duration of phenological stages, thermal requirement, and ripening dynamics of ‘BRS Núbia’ grapevines grafted onto the rootstocks ‘IAC 572 Jales’, ‘IAC 766 Campinas’, and ‘Paulsen 1103’. The experiment was conducted in São Manuel, São Paulo, Brazil during the 2021 and 2022 production cycles using a split-plot experimental design (3 × 2). Evaluations included the duration of phenological stages from pruning to budburst, flowering, fruit set, onset of ripening, and harvest, as well as the ripening curve and thermal accumulation from pruning to harvest. Rootstocks did not significantly affect (p > 0.05) the duration of phenological stages; however, differences were observed between production cycles. The 2022 cycle was longer (167.7 days) compared to 2021 (142.6 days), with greater thermal accumulation (1871.7 GDDs vs. 1743.4 GDDs). The analysis of phenological stages revealed that, across both production cycles evaluated, the ‘BRS Núbia’ cultivar required an average accumulation of 1807.5 growing degree days from pruning to harvest. Soluble solids content ranged from 17.43 to 18.50°Brix, and titratable acidity decreased throughout maturation. The maturation index was highest in vines grafted onto ‘Paulsen 1103’, indicating its positive influence on fruit quality. The ‘BRS Núbia’ grapevine exhibited a mean thermal requirement of 1807.5 growing degree days (GDDs) to complete its phenological cycle, which lasted approximately 150 days under subtropical conditions. Full article

(1) Background: The variability and trend in harvest dates of table and Pisco grapes have been scarcely studied. This can be closely influenced by bioclimatic indices since they account for the interactions between climatic factors and vine phenology. Understanding the environmental factors influencing harvest timing has become increasingly critical to perform specific viticultural practices. (2) Methods: The aim of this research was to evaluate the influence of bioclimatic indices on variability and trend of harvest date from the 2002–2003 to 2017–2018 seasons in Flame Seedless, Thompson Seedless, Muscat of Alexandria, and Moscatel Rosada growing in Northern Chile. (3) Results: The harvest date of Flame Seedless advanced significantly with an increasing Growing Season Temperature (GST) (from 1 October to 31 December), while Thompson Seedless showed a significant advancement in harvest date with rising the Maximum Springtime Temperature Summation SON_max (from 1 September to 30 November) values. Similarly, the harvest date of Muscat of Alexandria was significantly earlier with higher Heliothermal Index (HI) (from 1 July to 31 January and from 1 August to 30 April) values, whereas Moscatel Rosada exhibited a significant advancement in harvest date as the GST (from 1 July to 31 December and from 1 July to 31 January) increased. The trend in the harvest date of Thompson Seedless was statistically significant, reaching a coefficient of determination of 0.42. (4) Conclusions: Understanding the influence of bioclimatic indices on harvest date in long-term periods is critical in the context of climatic variability since producers can make more informed decisions to optimize grape quality and maintain sustainability in production systems. Full article

The present study was conducted in Extremadura, a region in southwestern Spain with a significant area dedicated to olive cultivation. An analysis of the olive growing climatology of its territory was conducted using bioclimatic indices that affect the development of olive cultivation, focusing on water requirements, thermal requirements, and leaf carbohydrate synthesis. The study revealed that very dry conditions during the olive growing season are the main characteristic of the Mediterranean climate in the region. A principal component analysis was performed to analyze the main sources of variability, revealing two main components, determined by annual rainfall, annual water requirement, mean annual temperature, degree days above 14.4 °C accumulated during the olive growing season, and the number of days with optimal temperatures for leaf carbohydrate synthesis. Three homogeneous groups were determined by cluster analysis, one of which had cooler thermal conditions and no water requirements. The study found that an increase in the olive growing season or a shortening of the dormant period could result in a higher water input during the growing season and a lack of accumulation of chilling hours during the dormant period, causing crop maintenance problems in warmer locations. Climate change is expected to have significant impacts on this crop where climatic conditions are already very hot and dry. In the future, it is possible that the current olive-growing areas in Extremadura will move to other areas where the temperature is cooler. Full article

Dry weather can severely limit water availability, harming agriculture and natural habitats. Several drought indices assess meteorological conditions relative to historical norms, but absolute indices, expressed in millimeters of water depth, are particularly crucial for agriculture. Every millimeter of water that a crop cannot evaporate results in an almost proportional yield loss. Using daily precipitation, potential evapotranspiration, and temperature data, we calculated five absolute drought indices for a sandy area in the Netherlands. We then validated these indices against the annual registered amount of irrigation water from 2001 to 2021, which served as a proxy for the drought experienced by farmers. The cumulative potential precipitation deficit calculated with (a) a temperature sum-dependent start of the growing season or (b) a start in the wet winter season most closely matched irrigation amounts (R² = 95% and 94%, respectively). The latter index is likely to be applicable in climates where a dry growing season follows a wet season. These indices can be updated daily, providing real-time insight into drought development and can be used in climate projections. To our knowledge, this is the first study to validate meteorological drought indices using irrigation data, which advances the assessment of drought events. Full article

As a measure of the accumulated heat deficit during the growing season transition, cooling degree days (CDDs) play a crucial role in regulating vegetation phenology and ecosystem dynamics. However, systematic analyses of CDD trends and their driving mechanisms remain limited, particularly in high-altitude regions where climate variability is pronounced. This study investigated the spatiotemporal variability in CDDs from 1982 to 2022 in alpine grasslands on the Qinghai–Tibetan Plateau (TP) and quantified the contributions of key climatic factors. The results indicate that lower CDD values (<350 °C-days) were predominantly found in warm, arid regions, whereas higher CDD values (>600 °C-days) were concentrated in colder, wetter areas. Temporally, area-averaged CDDs exhibited a significant decline, decreasing from 490.9 °C-days in 1982 to 495.8 °C-days in 2022 at a rate of 3.8 °C-days per year. Elevation plays a critical role in shaping CDD patterns, displaying a nonlinear relationship: CDDs decrease as elevation increases up to 4300 m, beyond which they increase, suggesting a transition from global climate-driven warming at lower elevations to local environmental controls at higher elevations, where snow–albedo feedback, topographic effects, and atmospheric circulation patterns regulate temperature dynamics. Tmax was identified as the dominant climatic driver of CDD variation, particularly above 4300 m, while radiation showed a consistent positive influence across elevations. In contrast, precipitation had a limited and spatially inconsistent effect. These findings emphasize the complex interactions between elevation, temperature, radiation, and precipitation in regulating CDD trends. By providing a long-term perspective on CDD variations and their climatic drivers, this study enhances our understanding of vegetation–climate interactions in alpine ecosystems. The results offer a scientific basis for modeling late-season phenological changes, ecosystem resilience, and land-use planning under ongoing climate change. Full article