Search Results (28)

In recent years, early olive fruit drop has been observed in the northern Mediterranean regions, causing significant economic losses, although the exact cause remains unknown. Recent studies have identified several possible causes; however, our understanding of how olive trees respond to these environmental stresses remains limited. This study includes an analysis of selected meteorological and flowering data for Olea europaea L. “Istrska belica” to evaluate the use of a chilling and forcing model for a better understanding of flowering time dynamics under a changing climate. The flowering process is influenced by high diurnal temperature ranges (DTRs) during the pre-flowering period, resulting in earlier flowering. Despite annual fluctuations due to various climatic factors, an increase in DTRs has been observed in recent decades, although the mechanisms by which olive trees respond to high DTRs remain unclear. The chilling requirements are still well met in the region (1500 ± 250 chilling units), although their total has declined over the years. According to the Chilling Hours Model, chilling units—referred to as chilling hours—represent the number of hours with temperatures between 0 and 7.2 °C, accumulated throughout the winter season. Growing degree hours (GDHs) are strongly correlated with the onset of flowering. These results suggest that global warming is already affecting the synchrony between olive tree phenology and environmental conditions in the northern Mediterranean and may be one of the reason for the green drop. Full article

Ornamental plants play a crucial role in the mitigation of urban heat islands. Recent decades have seen an increased frequency of abnormal climatic events like warm springs, but how these climatic events impact plant phenology in ornamental plants in urban areas is unclear. This study examines how climate fluctuations affect the flowering patterns (1963–2018) and thermal requirements of 28 woody ornamental species in Xi’an, a principal city in Central China. Years were classified as cold (<13.3 °C), normal (between 13.3 and 17.2 °C), or warm (>17.2 °C) based on March–May temperatures. The results show that the first flowering dates (FFDs) advanced by 10.63 days in warm years but were delayed by 6.14 days in cold years compared to normal years. Notably, thermal requirements (5 °C threshold) were 11.3% higher in warm years (343.05 vs. 308.09 °C days) and 9.4% lower in cold years (279.19 °C days), likely due to reduced winter chilling accumulation in warm conditions. While thermal time models accurately predicted FFDs in normal years (error: 0.33–1.37 days), they showed systematic biases in abnormal years—overestimating advancement by 1.56 days in warm years and delays by 3.42 days in cold years. These findings highlight that the current phenological models assuming fixed thermal thresholds may significantly mispredict flowering times under climate variability. Our results emphasize the need to incorporate dynamic thermal requirements and chilling effects when forecasting urban plant responses to climate change, particularly for extreme climate scenarios. Full article

Chilling and spring temperature accumulation are both considered key factors determining the timing of the spring bloom in many flowering plants. The accumulated developmental progress (ADP) method predicted the first flowering date (FFD) of a species of Rosaceae well in a previous study. However, whether this approach can be applied to other species, and whether the prediction errors in FFD based on the ADP method can be further accounted for by fall and winter temperatures (FWTs), remains unknown. The ADP method and two others were tested using a 39-year apricot FFD data series. The goodness of fit obtained with each method was assessed using the root mean square error (RMSE) between the observed and predicted FFDs. We used the residuals obtained using the ADP method as a response variable to fit generalized additive models (GAMs) including six FWTs as predictors. The GAMs generated based on different combinations of predictors were compared using Akaike’s information criterion (AIC) to test whether using FWTs can reduce prediction error. The ADP method had the lowest RMSE, which equaled 3.0904 days. Together, the number of cold days, the number of chilling hours, the mean value of the daily maximum temperatures, and the mean value of the daily mean temperatures from 1 November of the preceding year to the starting date accounted for 96% of the deviance in the residuals obtained using the ADP method. Including these predictors reduced the RMSE to 0.6162 days. The ADP method is a valid technique to quantify the effect of spring temperatures from a given starting date on the FFD. The FWTs and the number of cold days can also influence the FFD. The present work provides evidence that FWTs including daily maximum temperatures and spring mean temperatures together determine the FFD of apricot. Full article

Precise detection of meat freshness levels is essential for food consumer safety and real-time quality monitoring. This study aims to achieve the high-accuracy freshness detection of chilled mutton freshness by integrating hyperspectral imaging with deep learning methods. Although hyperspectral data can effectively capture changes in mutton freshness, sparse raw spectra require optimal data processing strategies to minimize redundancy. Therefore, this study employs a multi-stage data processing approach to enhance the purity of feature spectra. Meanwhile, to address issues such as overlapping feature categories, imbalanced sample distributions, and insufficient intermediate features, we propose a Dual-Branch Hierarchical Spectral Feature-Aware Network (DBHSNet) for chilled mutton freshness detection. First, at the feature interaction stage, the PBCA module addresses the drawback that global and local branches in a conventional dual-branch framework tend to perceive spectral features independently. By enabling effective information exchange and bidirectional flow between the two branches, and injecting positional information into each spectral band, the model’s awareness of sequential spectral bands is enhanced. Second, at the feature fusion stage, the task-driven MSMHA module is introduced to address the dynamics of freshness variation and the accumulation of different metabolites. By leveraging multi-head attention and cross-scale fusion, the model more effectively captures both the overall spectral variation trends and fine-grained feature details. Third, at the classification output stage, dynamic loss weighting is set according to training epochs and relative losses to balance classification performance, effectively mitigating the impact of insufficiently discriminative intermediate features. The results demonstrate that the DBHSNet enables a more precise assessment of mutton freshness, achieving up to 7.59% higher accuracy than conventional methods under the same preprocessing conditions, while maintaining superior weighted metrics. Overall, this study offers a novel approach for mutton freshness detection and provides valuable support for freshness monitoring in cold-chain meat systems. Full article

Accurate prediction of flowering times is essential for efficient orchard management for kiwifruit, facilitating timely pest and disease control and pollination interventions. In this study, we developed a predictive model for flowering time using weather data and observations of budbreak dynamics for the ‘Hayward’ and ‘Zesy002’ kiwifruit. We used historic data of untreated plants collected from 32 previous studies conducted between 2007 and 2022 and analyzed budbreak and flowering timing alongside cumulative heat sum (growing degree days, GDDs), chilling unit (CU) accumulation, and other environmental variables using weather data from the weather stations nearest to the study orchards. We trained/parameterized the model with data from 2007 to 2019, and then evaluated the model’s efficacy using testing data from 2020 to 2022. Regression models identified a hierarchical structure with the accumulation of GDDs at the start of budbreak, one of the key predictors of flowering time. The findings suggest that integrating climatic data with phenological events such as budbreak can enhance the predictability of flowering in kiwifruit vines, offering a valuable tool for kiwifruit orchard management. Full article

The rest-breaking agent, hydrogen cyanamide (HC), can substitute insufficient chill unit accumulation in Vitis vinifera and induce uniform bud-break; however, due to its toxicity it is being banned. In South Africa, red seedless grapes, including V. vinifera Crimson Seedless (CS), are the largest table grape export group; therefore, replacing HC in V. vinifera CS is crucial. This study aimed to confirm the molecular triggers induced by HC and assess the bud-break-enhancing abilities of commercial plant biostimulants. Forced bud-break assay experiments using V. vinifera CS single-node cuttings and a small-scale field trial were performed. Results demonstrated that increased chill unit accumulation (CUA) reduced HC efficacy. Bud-break started between 10 and 20 days after treatment, irrespective of final CUA. The small-scale field trial found that HC 3% and biostimulants were similar to the negative control. The treatment of dormant grapevine compound buds with nitric oxide (NO), hydrogen peroxide (H₂O₂), and hypoxia trigger dormancy release to a certain extent, supporting the molecular models proposed for HC action. NO, H₂O₂, and hypoxia, in combination with PBs, may potentially replace HC; however, this needs to be confirmed in future experiments. Full article

The phenomenon of dormancy and the evolutionary causes for its development are presented together with the effects of the climatic factors: temperature and light. Shade and darkness have been found to enhance bud breaking in peach. The effects of various temperatures on chilling accumulation, chilling negation and chilling enhancement are described. The way these are computed in the face of global warming is explained, using the dynamic model. When natural chilling is less than that required, there are ways of compensation, up to a certain level. Various horticultural, physical and chemical means to achieve this are described, including bending branches, reducing vegetative vigor, shading the orchard, sprinkling to reduce daytime temperature and the application of various chemicals to break dormancy. When winter chilling is markedly reduced and temperatures increase considerably, the use of dormancy avoidance is suggested in frost-free places. This technique can induce a new growing cycle by avoiding dormancy altogether. However, the best approach is to breed high-quality cultivars requiring much less chilling. Another aspect discussed in this work, independent of the chilling requirement, is the negative effect of heat spells in winter and spring on the abnormal development of flower buds, leading to a low level of the stone fruit set and a reduced yield. Full article

This study focuses on the behavior of volatile organic compounds in beef after irradiation with 1 MeV accelerated electrons with doses ranging from 0.25 kGy to 5 kGy to find reliable dose-dependent markers that could be used for establishing an effective dose range for beef irradiation. GC/MS analysis revealed that immediately after irradiation, the chemical yield and accumulation rate of lipid oxidation-derived aldehydes was higher than that of protein oxidation-derived aldehydes. The nonlinear dose-dependent relationship of the concentration of volatile organic compounds was explained using a mathematical model based on the simultaneous occurrence of two competing processes: decomposition of volatile compounds due to direct and indirect action of accelerated electrons, and accumulation of volatile compounds due to decomposition of other compounds and biomacromolecules. A four-day monitoring of the beef samples stored at 4 °C showed that lipid oxidation-derived aldehydes, protein oxidation-derived aldehydes and alkanes as well as alcohol ethanol as an indicator of bacterial activity were dose-dependent markers of biochemical processes occurring in the irradiated beef samples during storage: oxidative processes during direct and indirect action of irradiation, oxidation due to the action of reactive oxygen species, which are always present in the product during storage, and microbial–enzymatic processes. According to the mathematical model of the change in the concentrations of lipid oxidation-derived aldehydes over time in the beef samples irradiated with different doses, it was found that doses ranging from 0.25 kGy to 1 kGy proved to be most effective for beef irradiation with accelerated electrons, since this dose range decreases the bacterial content without considerable irreversible changes in chemical composition of chilled beef during storage. Full article

For several years, there has been a need in phenological modeling to better account for physiological processes during the winter dormancy of woody plants, which is here addressed to the sweet cherry cultivar ‘Summit’ (Prunus avium L.). This study compares three sequential phenology models (M1–M3) for the beginning of ‘Summit’ blossom in the experimental sweet cherry orchard in Berlin-Dahlem (Germany) between 2011/12–2019/20 (model development) and 2020/21–2022/23 (model validation). M1 represents an inverse modeling approach where the chilling and forcing requirements of ‘Summit’ were optimized solely from observed flowering data. In contrast, M2 and M3 are more physiologically based as they already incorporate biological knowledge, so that the model parameters were calculated directly within the specified developmental phases. Here, M2 is a two-phase model that considers experimental data for the date of endodormancy release (t₁) of nine years (2011/12–2019/20) to calculate the chilling and forcing requirements. Finally, M3 is a newly developed three-phase model that additionally includes the onset of ontogenetic development (t₁*) and the abscisic acid (ABA) content of ‘Summit’ flower buds during the ecodormancy phase (t₁ − t₁*). The results indicate that the inclusion of ABA-related heat weighting during ecodormancy significantly improves the performance of M3 compared to M1 and M2. While M1 gives satisfactory results in terms of fit and validation, it is considered physiologically unacceptable as it greatly overestimates the chilling requirement of ‘Summit’ by ignoring the ecodormancy phase. M2 accumulates too much heat during ecodormancy as it does not include control by the bud ABA content. The results highlight the need for parameters such as t₁, t₁*, and the bud ABA content for the physiological modeling of ‘Summit’ blossom. To the best of our knowledge, this is the first study to provide a pathway towards a physiologically based modeling approach. Full article

Phenological shifts in peaches have been observed over the last few years due to the fluctuation of the seasonal climate conditions experienced during dormancy, affecting orchard management practices and influencing production and harvest dates. This study aimed to model the vegetative and floral budbreak of selected peach cultivars. Three peach cultivars, including “Rubyprince”, “Harvester”, and “Red Globe”, were considered in this study based on the representation of the early, early-mid, and mid-seasons. The prediction of the budbreak in peaches was assessed using different models that integrate the combination of chill and heat requirements. Models used include the Weinberger model, the modified Weinberger model, Utah, the dynamic model, and the growing degree model. The accumulation of chill varies according to the season evaluated. A model that considers both chill and heat accumulation is presented for each cultivar. Budbreak as an indicator of dormancy completion was established for each cultivar. The outcome of this study is to determine the amount of chilling accumulation and thermal time required to mark the beginning of the budbreak in selected cultivars with a model that predicts the duration of the dormancy. These results are valuable information that can be used for crop management practices and support the mitigation of cold damage during this critical period of crop development. Full article

With global warming, mean winter temperatures are predicted to increase. Therefore, understanding how warmer winters will affect the levels of olive flower induction is essential for predicting the future sustainability of olive oil production under different climactic scenarios. Here, we studied the effect of fruit load, forced drought in winter, and different winter temperature regimes on olive flower induction using several cultivars. We show the necessity of studying trees with no previous fruit load as well as provide evidence that soil water content during winter does not significantly affect the expression of an FT-encoding gene in leaves and the subsequent rate of flower induction. We collected yearly flowering data for 5 cultivars for 9 to 11 winters, altogether 48 data sets. Analyzing hourly temperatures from these winters, we made initial attempts to provide an efficient method to calculate accumulated chill units that are then correlated with the level of flower induction in olives. While the new models tested here appear to predict the positive contribution of cold temperatures, they lack in accurately predicting the reduction in cold units caused by warm temperatures occurring during winter. Full article

Flowering in temperate fruit trees depends on the temperatures during the previous months; chill is required to overcome endodormancy, and then heat exposure is needed. These agroclimatic requirements are cultivar-specific and determine their adaptability to the growing area and their response to climate change. We aim to estimate the agroclimatic requirements of 16 traditional cultivars of European pears grown in Zaragoza (Spain). We used Partial Least Squares regression analysis to relate 20-year records of flowering dates to the temperatures of the 8 previous months. This approach allowed us to establish the chilling and forcing periods, through which we quantified temperatures with three models for chill accumulation (Chilling Hours, Utah model, and Dynamic model) and one model for heat accumulation (Growing Degree Hours). The results indicated very little difference in the chilling and forcing periods. Chill requirements ranged from 43.9 to 49.2 Chill Portions; from 1027 to 1163 Chilling Units; and from 719 to 774 Chilling Hours. Heat requirements ranged from 6514 to 7509 Growing Degree Hours. Flowering dates were mainly determined by the temperatures during the chilling period. This means that reductions in winter chill caused by global warming in many regions could cause flowering delays or even failures in the fulfillment of chill requirements. Full article

The present study aims to generalize cultivar-specific tree phenology responses to winter and spring temperatures and assess the effectiveness of the Tabuenca test and various chill and heat accumulation models in predicting bloom dates for a wide range of climatic conditions and years. To this end, we estimated the dates of rest completion and blooming and correlated them with observed bloom dates for 14 peach and nectarine cultivars that were evaluated in 11 locations across Europe (Greece, France, Italy, Romania and Spain), within the EUFRIN cultivar testing trial network. Chill accumulation varied considerably among the studied sites, ranging from 45 Chill Portions (CP) in Murcia-Torre Pacheco (Spain) to 97–98 CP in Cuneo (Italy) and Bucharest (Romania). Rest completion occurred latest or was not achieved at all for some cultivars in the southern sites in Murcia. Dormancy release happened earliest in Bucharest and Cuneo, sites where heat accumulation had a strong influence on the regulation of bloom time. Blooming occurred earliest in the moderately cold regions of Lleida (Spain) and Bellegarde (France), and 7–11 days later in the warmer locations of Rome (Italy) and Naoussa (Greece), suggesting that bloom timing is strongly influenced by delayed rest completion in these locations. The Dynamic Model resulted in both more homogeneous chill accumulation across years and better predictions of bloom dates, compared with the Utah, Positive Utah and Chilling Hours models. Prediction of bloom dates was less successful for low-chill cultivars than for medium- and high-chill cultivars. Further climatic and experimental data are needed to make estimates of the climatic needs of peach cultivars more robust and to generate reliable advice for enhancing the resilience of peach production under varying and changing climatic conditions. Full article

One of the most important tasks in the food industry is the search for alternative biochemical markers of radiation treatment in dietary, chilled meat products such as chicken and turkey. Major organic volatile chemicals found in meat products can be precisely identified using gas chromatography coupled with mass spectrometry. In the response to the needs of the food industry, our research team conducted a series of experiments involving the irradiation of chilled poultry meat using an electron accelerator. The experiments showed that the concentration of pure volatile organic compounds in saline solution dropped exponentially with an increase in the irradiation dose, which proves that these chemicals decomposed when exposed to ionizing radiation. However, when turkey meat was exposed to an electron beam with doses up to 1 kGy, the concentration of alcohols, aldehydes, and ketones peaked, only to decrease with an increase in the irradiation dose up to 2 kGy, and then went up slightly when the irradiation dose was within the range from 2 kGy to 10 kGy. To determine the reason behind the nonlinear dependencies of organic compound concentrations in turkey meat on the irradiation dose, we developed a mathematical model that acknowledges the presence of two opposing processes, those of decomposition and accumulation of organic compounds as a result of the decomposition of other compounds that can be found in turkey meat. Full article

The present study investigates the influence of temperature on the development of Eurytoma maslovskii after a diapause break up until adulthood. The insect development rate was fitted to both linear and nonlinear models to estimate thermal bioparameters, which served as the basis for constructing prediction models. Chilled apricot seeds collected in November were used for the experiments in March. Experiment 1 used intact seeds, while experiment 2 used overwintered larvae obtained by cracking the endocarp cover. Both larvae and intact seeds were subjected to seven constant temperatures (14.5, 18.8, 21.3, 24.0, 27.0, 30.2, and 34.3 °C). The post-diapause larvae of E. maslovskii developed into adults at a temperature range of 14.5–30.2 °C, and no larvae pupated at 34.3 °C. The lower temperature thresholds (LTs) for post-diapause larva and pupa and the total post-diapause period until adult emergence and until adult exit were 8.1, 8.2, 8.2, and 7.3 °C, respectively, whose thermal constants (DD) were 66.2, 180.2, 246.9, and 336.7 degree days, respectively. The distribution of E. maslovskii at all post-diapause stages was described using a two-parameter Weibull function. The data predicted by the model using accumulated degree days starting from January 1 did not differ by more than three days from the observed field emergence of E. maslovskii. Our data provide insights into the development of E. maslovskii after diapause. Temperature-dependent development supports the use of a degree day model to predict field emergence for pest timing control. Full article