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There is a demand from the scientific, beekeeping and consumer sectors to characterize honey based on its botanical origin, as it provides unique and distinctive properties. Nevertheless, existing studies on the physicochemical properties and the sensorial profile of honey in relation to botanical origin remain insufficient. This study aimed to understand the relationships between sensory profile and various chemical compounds (minerals, sugars, water content and volatiles) of three monofloral honeys (Atractylis serratuloides, Retama sphaerocarpa and Eruca sativa) produced in Algeria using principal component analysis. Crystallization was detected as a distinctive attribute of Eruca and Atractylis honey. A candy aroma and odor with floral nuances, light color, crystallized state and the volatile compounds Alpha-Bisabolol and Beta-eudesmol characterized the Atractylis honey. Eruca honeys were distinguished by an animal and degraded odor, bitter taste, light color and the presence of Dimethyl trisulfide and Dimethyl tetrasulfide. Finally, a vegetal aroma, some saltiness and sourness, dark amber color, lower sugar content, higher K content and Lilac aldehyde and Lilac aldehyde D characterized Retama honeys. [ABSTRACT FROM AUTHOR]

The use of pesticides is an efficient approach for pest management. However, their increasing application in recent decades has come under the spotlight of world policies. In this context, this study addresses the usefulness of a forecasting model (TOMCAST) combined with aerobiological information and a plant development model (physiological days, PDays) for the control of early blight in potatoes in Northwest Spain. Control plots were compared to treated plots, according to the original TOMCAST model and the daily Alternaria spp. concentration, meteorological factors, and phenological and epidemiological observations were monitored for better adjustment of the TOMCAST model to the weather conditions of the geographical area during three crop seasons. The results of the linear regression analysis showed a strong relationship between the parameters included in TOMCAST (leaf wetness and temperature) and the Alternaria spp. conidia concentration. In addition, an unbalanced pattern of trapped conidia was detected throughout the growing season, with an increase near the flowering stage. The epidemiological parameters (infection period, r-AUDPC, maximum severity value, and total and commercial yields) showed significant differences between the cultivars in the control and the TOMCAST plots in terms of r-AUDPC and the maximum severity value. Given the study's results, the original TOMCAST model was improved with aerobiological and phenological information. The improved model recommends a first spray on a day when the following three requirements are met: Ten accumulated disease severity values (DSVs) according to the TOMCAST model, two days with an aerobiological level greater than 10 conidia/m3, and a PDays value greater than 200. This will reduce the number of fungicide treatments used to control early blight in potato crops, promoting the principles of sustainable agriculture. [ABSTRACT FROM AUTHOR]

This document, titled "Authenticity of Honey: Characterization, Bioactivities and Sensorial Properties Series II," explores the various aspects of honey, including its composition, bioactive compounds, and sensory attributes. The authors highlight the importance of identifying the botanical origin of honey and the need for improved methods of authentication. The research papers included in this special issue cover topics such as the characterization of organic honeys from Morocco, the antioxidant activities of stingless bee honeys, the multi-element profile of Latvian honeys, the use of chemometric techniques to analyze honey from Spain, the parameters that influence honey agitation, and the sensory properties and consumer acceptance of different types of honey. The authors emphasize the significance of these studies in enhancing the commercial value of honey and providing valuable information for beekeepers and the food industry. They also call for further research to expand our understanding of honey's characteristics and applications. [Extracted from the article]

The NEGFRY system is presented in this research work as a novelty strategy for the control of potato late blight in A Limia (NW Spain). The aim was to analyse the number of fungicide applications established by NEGFRY (Decision Support System, DSS) with respect to the routine calendars of this potato production area. This approach is in accordance with the requirements imposed by European policies, participating in more profitable and environmentally friendly agriculture. For this purpose, the relationships between the pathogen and the environmental conditions and epidemiological parameters were analysed in different plots compared to late blight infection in both Routine and DSS strategies. In addition, economic and environmental impacts of fungicide sprays were also analysed to check the adaptability of the decision support system to late blight in the area. Results confirmed that it is possible to reduce sprays following the NEGFRY model by more than 50% compared with Routine applications. Therefore, NEGFRY is a promising strategy to achieve lower footprint potato yields through a reduction in applied pesticides and water, lower gas emissions and less soil compaction due to a reduction in the number of tractor passes over the soil. The commitment to this strategy contributes to improving the economy of farmers, the health of the biodiversity, the environment and consumers, as well as to comply with demands of global economies in terms of more sustainable and resilient agriculture. [ABSTRACT FROM AUTHOR]

Honeys from different regions of Algeria were analyzed to determine their pollen characteristics and physicochemical properties (humidity, pH, electrical conductivity, diastase content, color, phenols, flavonoids and antioxidant activity). The antioxidant activity was investigated using the free radical scavenging and Ferric reducing/antioxidant power assays. The melissopalynological analysis revealed 129 pollen types from 53 botanical families. The pollen types found as dominant were Coriandrum, Bupleurum, Brassica napus type, Hedysarum coronarium, Ceratonia siliqua, Eucalyptus, Peganum harmala, Ziziphus lotus and Tamarix. Principal component analysis and cluster analysis were used to analyze significant relationships between the physicochemical variables and the botanical origin of the honeys and establish groupings based on the similarities of their physicochemical and antioxidant properties. The results showed that Ceratonia siliqua, Eucalyptus, Arbutus and honeydew honeys had a higher antioxidant contribution and higher phenolic and flavonoid contents than the rest of the honeys. In addition, the contributions of Mediterranean vegetation such as Myrtus and Phyllirea angustifolia were significant in this honey group. This paper demonstrates the diverse botanical variability for honey production in Algeria. However, there is a gap in its characterization based on its botanical origin. Therefore, these studies contribute positively to the needs of the beekeeping sector and the commercial valorization of the country's honey. [ABSTRACT FROM AUTHOR]

Simple Summary: The yellow-legged hornet is an invasive species from southeast Asia that has turned the European beekeeping sector upside down. The spread of this species has been advancing in recent years, and today, several European countries are threatened by Vespa velutina. The need to study its behavior is urgent given the increasingly evident economic and environmental impacts. In this regard, there is little information about the feeding habits and the resources it uses during the life cycle. Like other Hymenoptera, hornets require carbohydrates and proteins as their primary nutrients. Sugary secretions such as floral nectar, honeydew, or fruit juices are the main sources of carbohydrates but the protein intake is provided by the consumption of a diverse diet of insects such as the honey bee. There is scarce information on the presence of pollen grains in the gastrointestinal content of larvae other than secondary contamination from hunting. This content could represent the surrounding flora of its habitat that is used as a resource. Therefore, the objective of this study was to describe the main pollen types present in the gastrointestinal system of larvae taken from V. velutina nests. Vespa velutina is an invasive species that exhibits flexible social behavior, which may have contributed to its introduction in several European countries. It is important to understand its behavior in order to combat the effects of its introduction in different areas. This implies knowing the resources that it uses during its biological cycle. Hornets require protein resources taken from insects and organic matter as well as carbohydrates as an energy source to fly and also to forage for food and nest-building materials. The gastrointestinal tract of adults and larvae contains a wide variety of pollen types. The identification of this pollen in larvae collected from nests could offer information about the plant species that V. velutina visits as a foraging place. The main objective of this research was to study the pollen content in the gastrointestinal tract of larvae. Patterns of pollen content and pollen diversity were established according to the nest type, altitude, season, and location in the nest comb. The abundance of pollen types such as Eucalyptus, Castanea, Foeniculum vulgare, Hedera helix, Taraxacum officinale, Echium, or Cytisus pollen type stands out in many of the samples. [ABSTRACT FROM AUTHOR]

Late blight, caused by Phytophthora infestans, is a major disease of the potato crop with a strong negative impact on tuber yield and tuber quality. The control of late blight in conventional potato production systems is often through weekly application of prophylactic fungicides, moving away from a sustainable production system. In support of integrated pest management practices, machine learning algorithms were proposed as tools to forecast aerobiological risk level (ARL) of Phytophthora infestans (>10 sporangia/m3) as inoculum to new infections. For this, meteorological and aerobiological data were monitored during five potato crop seasons in Galicia (northwest Spain). Mild temperatures (T) and high relative humidity (RH) were predominant during the foliar development (FD), coinciding with higher presence of sporangia in this phenological stage. The infection pressure (IP), wind, escape or leaf wetness (LW) of the same day also were significantly correlated with sporangia according to Spearman's correlation test. ML algorithms such as random forest (RF) and C5.0 decision tree (C5.0) were successfully used to predict daily sporangia levels, with an accuracy of the models of 87% and 85%, respectively. Currently, existing late blight forecasting systems assume a constant presence of critical inoculum. Therefore, ML algorithms offer the possibility of predicting critical levels of Phytophthora infestans concentration. The inclusion of this type of information in forecasting systems would increase the exactitude in the estimation of the sporangia of this potato pathogen. [ABSTRACT FROM AUTHOR]

Bee pollen is a rich bee product, from the point of view of its nutritional and functional chemical characteristics. The chemical composition of bee pollen and its properties make this product an excellent food supplement for the human diet, due to its various functional bioactivities, such as having antioxidant, antibacterial, antifungal, and anti-inflammatory properties. These properties depend on the botanical origin of the bee pollen. Castanea sativa bee pollen is one of the most important types of pollen collected in the northwest of the Iberian Peninsula. Thus, the phenolic profile of Castanea bee pollen was featured in this study. For this, 11 samples of Castanea were selected through prior colorimetric separation using the CIELab* scale and verified with palynological analysis. Identification of the main phenol compounds was performed through LC/DAD/ESI-MSn analysis. The phenols compounds were quantified using calibration curves for caffeic acid, quercetin, and naringenin. The main results showed a profile formed of 19 compounds for all samples, although quantitative differences were found. Most of these compounds were phenolamides, with N1, N5, and N10-tricaffeoylspermidine being significantly (p < 0.05) the most abundant. Three isorhamnetin glycoside derivatives and one naringenin were also identified. The richness in phenolamides of Castanea bee pollen identified in this study suggests Castanea bee pollen as a functional food, owing to its healthy properties. [ABSTRACT FROM AUTHOR]

Raw honey is a food with a close relation to the territory in which it is produced because of factors such as soil conditions, weather patterns, and plant communities living in the area together. Furthermore, beekeeping management affects the properties of honey. Protected Geographical Indication Miel de Galicia protects the honey produced in Galicia (Northwest Spain). Various types of honeys (362 samples) from this geographical area were analyzed using chemometric techniques. Principal component analysis was favorable to analyzing the physicochemical and pollen variables with the greatest weight in the differentiation of honey. The linear discriminant analysis correctly classified 89.8% of the samples according to the botanical origin using main pollen spectra and physicochemical attributes (moisture, pH, electrical conductivity, diastase content, phenols, flavonoids, and color). Regarding unifloral honey, blackberry, eucalyptus, and heather honeys were correctly grouped, while five chestnut honeys and fourteen samples of honeydew honeys were misclassified. The chestnut and honeydew honeys have similar physicochemical properties and frequently similar pollen spectra profiles complicating the differentiation. Experimental evidence suggests the potential of multivariate statistics in the characterization of honey of the same geographical origin. Therefore, the classification results were good, with electrical conductivity, total phenol content, total flavonoid content and dominant pollens Eucalyptus, Erica, Rubus and Castanea sativa as the variables of higher importance in the differentiation of botanical origin of honeys. [ABSTRACT FROM AUTHOR]

Bee pollen is considered a natural product, relevant for its nutritional and antioxidant properties. Its composition varies widely depending on its botanical and geographical origins. In this study, the botanical characteristics of 31 bee pollen samples from Galicia (Northwest Spain) were analyzed; samples have not been studied until now from this geographical area. The study focused on the evaluation of the influence of plant origin on total phenol and flavonoid contents and antioxidant activity measured by radical scavenging methods. The multivariate statistical treatment showed the contribution of certain pollen types in the extract of bee pollen as to phenols, flavonoids and antioxidant capacity. Specifically, the bee pollen samples with higher presence of Castanea, Erica, Lythrum and Campanula type indicated higher total phenol and flavonoid contents and antioxidant activities according to the principal component analysis. On the contrary, Plantago and Taraxacum officinale type contributed a lower content of these compounds and radical scavenging activity. The cluster analysis classified the bee pollen samples into three groups with significant differences (p > 0.05) for the main pollen types, total phenol and flavonoid contents and antioxidant capacities. These results demonstrate the richness and botanical diversity in the pollen spectrum of bee pollen and enhance the possible beneficial nutraceutical properties of this beekeeping product. [ABSTRACT FROM AUTHOR]

Simple Summary: Vespa velutina nigrithorax is an invasive species established in the European Union since 2004. Galicia (NW Spain) is one of the areas strongly affected by the invasion, with around 28,000 nests identified per year. In the area, when the weather conditions are suitable, the queen starts the life cycle by building the embryo nest and laying the firsts eggs. This first stage of the colony is composed of the queen, a few small workers and sometimes males, living in a fragile nest usually situated in a protected place. After this, the nest continues to develop to a larger size, which leaves the nest more exposed in places such as tree canopy. The period of decline begins in autumn with the appearance of breeding individuals (males and gynes) and ends with the fecundation of new queens that will form the future colony in the next cycle. The high reproduction rate of this species has led to the successful expansion of this species into many regions, such as Galicia. Vespa velutina is established in Galicia since 2012, causing significant losses in agriculture, beekeeping and being a risk for human health. Invasive species become established in non-native areas due to their intrinsic characteristics and the ability to adapt to new environments. This work describes the characteristics of the nesting behavior of the invasive yellow-legged hornet (Vespa velutina nigrithorax) in Galicia (Northwest Spain). The first nest was detected in the area in 2012 and after that, the distribution pattern shows a species-invasion curve with slow progress at first but followed by rapid expansion. The nesting places for this hornet differ between the kinds of nests, while embryo nests are mainly found in buildings in spring, secondary nests are observed in vegetation in summer, autumn, and winter. The annual life cycle starts when the queen builds the embryo nests and starts to lay eggs. This leads to the emergence of the first workers, usually small in size, and sometimes a few males. After this stage, large nests called secondary nests are normally observed in most exposed sites. Relocation nests can also be observed; these are nests in the first stage of development presenting adults insects but without brood or meconium. The period of decline is characterized by the emergence of new queens and males, that are distinguishable even in the pupal stage, the appearance of two eggs per cell, and an irregular brood pattern. [ABSTRACT FROM AUTHOR]

Secondary infections of early blight during potato crop season are conditioned by aerial inoculum. However, although aerobiological studies have focused on understanding the key factors that influence the spore concentration in the air, less work has been carried out to predict when critical concentrations of conidia occur. Therefore, the goals of this study were to understand the key weather variables that affect the hourly and daily conidia dispersal of Alternaria solani and A. alternata in a potato field, and to use these weather factors in different machine learning (ML) algorithms to predict the daily conidia levels. This study showed that conidia per hour in a day is influenced by the weather conditions that characterize the hour, but not the hour of the day. Specifically, the relative humidity and solar radiation were the most relevant weather parameters influencing the conidia concentration in the air and both in a linear model explained 98% of the variation of this concentration per hour. Moreover, the dew point temperature three days before was the weather variable with the strongest effect on conidia per day. An improved prediction of Alternaria conidia level was achieved via ML algorithms when the conidia of previous days is considered in the analysis. Among the ML algorithms applied, the CART model with an accuracy of 86% were the best to predict daily conidia level. [ABSTRACT FROM AUTHOR]

In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later. [ABSTRACT FROM AUTHOR]

At the same time, with this method, the authors detected a mixture of I A. mellifera i honey with I A. dorsata i and I A. cerana i honey. Studies about the composition, properties, and botanical and geographical origins of different honey types are relevant in society; they are especially relevant in the honey market, as they provide knowledge to guarantee honey authenticity. I A. dorsata i honey and I A. cerana i honey are vulnerable to adulteration (as a result of false geographical and botanical origin, or from mixing their composition with sugars or syrups), due to the higher price in the market compared to I A. mellifera i honey [[12]]. I Apis mellifera i honey, I A. cerana i honey and I A. dorsata i honey are the three dominant honey types in the Asian market. [Extracted from the article]

Vespa velutina is an invasive species that is currently the main concern for beekeeping in some areas of northern Spain. The hornet hunts honeybees to feed its larvae, stressing and weakening the honeybee colonies. To avoid losses of honeybee colonies, it is essential to investigate the pressure that is exerted by the yellow-legged hornet on apiaries and its consequences. In the present study, hives were monitored in an apiary that was situated in a high-pressure area of V. velutina during the years 2020 and 2021. The monitoring of environmental conditions of the apiary, the internal conditions of the colonies, and a hunting camera were used to relate the presence of hornets in front of the hives to the weather conditions in the apiary and the consequences caused on the colonies. The relationships between weather conditions and the hornet's activity showed two types of hornet behavior. In the months of July and August, the maximum number of hornets appeared in non-central hours of the day. Meanwhile, in the months of September and October, the highest pressure in the apiary occurred in the central hours of the day, coinciding with temperatures between 15 °C and 25 °C and a relative humidity that was higher than 60%. The honeybee colony with the highest thermoregulatory capacity was the strongest and it was the key factor for the colony survival even when the hornet pressure was high too. Therefore, strengthening the hives and improving beehive health status is essential to avoid colonies decline. [ABSTRACT FROM AUTHOR]

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption. [ABSTRACT FROM AUTHOR]

The aim of the present work was to determine the main quality parameters on tuber potato using a portable near-infrared spectroscopy device (MicroNIR). Potato tubers protected by the Protected Geographical Indication (PGI "Patata de Galicia", Spain) were analyzed both using chemical methods of reference and also using the NIR methodology for the determination of important parameters for tuber commercialization, such as dry matter and reducing sugars. MicroNIR technology allows for the attainment/estimation of dry matter and reducing sugars in the warehouses by directly measuring the tubers without a chemical treatment and destruction of samples. The principal component analysis and modified partial least squares regression method were used to develop the NIR calibration model. The best determination coefficients obtained for dry matter and reducing sugars were of 0.72 and 0.55, respectively, and with acceptable standard errors of cross-validation. Near-infrared spectroscopy was established as an effective tool to obtain prediction equations of these potato quality parameters. At the same time, the efficiency of portable devices for taking instantaneous measurements of crucial quality parameters is useful for potato processors. [ABSTRACT FROM AUTHOR]

Vespa velutina has been rapidly expanding throughout Galicia since 2012. It is causing human health risks and well-known losses in the beekeeping sector. Control methods are scarce, unspecific, and ineffective. Semiochemicals are insect-derived chemicals that play a role in communication and they could be used an integrated pest management tool alternative to conventional pesticides. A previous determination of the organic chemical profile should be the first step in the study of these semiochemicals. HS-SPME in living individuals and the sting apparatus extraction followed by GC-MS spectrometry were combined to extract a possible profile of these compounds in 43 hornets from Galicia. The identified compounds were hydrocarbons, ketones, terpenes, and fatty acid, and fatty acid esters. Nonanal aldehyde appeared in important concentrations in living individuals. While pentadecane, 8-hexyl- and ethyl oleate were mainly extracted from the venom apparatus. Ketones 2-nonanone, 2-undecanone and 7-nonen-2-one, 4,8-dimethyl- were identified by both procedures, as was 1,7-Nonadiene, 4,8-dimethyl-. Some compounds were detected for the first time in V. velutina such as naphthalene, 1,6-dimethyl-4-(1-methylethyl). The chemical profile by caste was also characterized. [ABSTRACT FROM AUTHOR]

Siliceous marine microfossils were unexpectedly discovered during the analysis of flower honey samples from Poland and Tunisia. The microfossils were represented by protist with siliceous skeletons: silicoflagellates, diatoms, and endoskeletal dinoflagellates. This is the first record of such microfossils in honeys. Based on the high percent of anemophilous pollen grains and spores in the sample, it was hypothesized that silicoflagellates were deposited from the air onto the nectariferous flowers, then bees harvested them with the nectar. Based on the comparison of pollen content of honeys and flowering calendar of Tunisia, the harvest time of honey was identified as a period between 1 April and 31 May 2011. Trajectory analysis of air masses in this period confirmed that siliceous microfossils could be aerosolized by wind from the rocks of the so-called Tripoli Formation of Messinian age (6–7 Ma). Similar to the Tunisian case, the Polish trajectory simulation also supports the hypothesis of atmospheric transport of silicoflagellates from outcrops of Oligocene age in the Polish Outer Carpathians. In the case of diatom content of honey, however, the source can be both natural (wind) and artificial (diatomaceous earth filters). For a correct determination, natural sources of siliceous bioparticles, such as wind transport from nearby outcrops should be also considered. Silicoflagellates could be used as complementary indicators of the geographical origin of honeys collected in areas characterized by diatomite outcrops, supporting the results obtained with other methods; thus, such indicators merit further studies within the area of honey authenticity. [ABSTRACT FROM AUTHOR]

There is an increase in the consumption of natural foods with healthy benefits such as honey. The physicochemical composition contributes to the particularities of honey that differ depending on the botanical origin. Botanical and geographical declaration protects consumers from possible fraud and ensures the quality of the product. The objective of this study was to develop prediction models using a portable near-Infrared (MicroNIR) Spectroscopy to contribute to authenticate honeys from Northwest Spain. Based on reference physicochemical analyses of honey, prediction equations using principal components analysis and partial least square regression were developed. Statistical descriptors were good for moisture, hydroxymethylfurfural (HMF), color (Pfund, L and b* coordinates of CIELab) and flavonoids (RSQ > 0.75; RPD > 2.0), and acceptable for electrical conductivity (EC), pH and phenols (RSQ > 0.61; RDP > 1.5). Linear discriminant analysis correctly classified the 88.1% of honeys based on physicochemical parameters and botanical origin (heather, chestnut, eucalyptus, blackberry, honeydew, multifloral). Estimation of quality and physicochemical properties of honey with NIR-spectra data and chemometrics proves to be a powerful tool to fulfil quality goals of this bee product. Results supported that the portable spectroscopy devices provided an effective tool for the apicultural sector to rapid in-situ classification and authentication of honey. [ABSTRACT FROM AUTHOR]

This study aimed to characterize the honeys of Babors Kabylia through sensory, melissopalynological and physico-chemical parameters. Thirty samples of honey produced in this region were collected over a period of two years and analyzed. All the samples presented physico-chemical parameters in conformity with legislation on honey quality, with few exceptions, linked mainly to beekeeping management. The pollen spectrum revealed a great diversity with 96 pollen types. The main pollen types were spontaneous species as Fabaceae (Hedysarum, Trifolium, Genisteae plants), Asteraceae plants, Ericaceae (Erica arborea L.) or Myrtus and Pistacia. The sensory properties of samples showed a high tendency to crystallization, the colors were from white to brown, but most of them had gold color. Smell and odor corresponded mainly to vegetal and fruity families and in taste perceptions besides sweetness highlighted sourness and saltiness notes. Seventeen samples were polyfloral, one was from honeydew and twelve were monofloral from heather, genista plants, sulla, blackberry or Asteraceae. Heather and the honeydew samples showed the darkest color, the highest electrical conductivity and phenol and flavonoid content. A statistical analysis based on the most representative pollen types, sensory properties and some physico-chemical components allowed the differentiation of honey samples in terms of botanical origin. [ABSTRACT FROM AUTHOR]

The present study focuses on establishing thresholds of weather variables for predict early blight in potato crops. For this, the TOMCAST model was adjusted using weather variables and Alternaria conidia levels (mainly A. solani and A. alternata) during six growing seasons in A Limia (Northwest Spain). TOMCAST for the effective management of early blight considers leaf wetness and air temperature to calculate daily severity values (DSVs). Spearman correlations between temperature (minimum and average), mean temperature during leaf wetness period and Alternaria concentration showed the highest positive significant coefficients (0.386, 0.230 and 0.372, respectively; p < 0.01). Specifically, Alternaria levels higher than 50 spores/m3 were found the days with air mean temperature above 18 °C, more than 7 h of leaf wetness. Leaf wetness was decisive to estimate the concentration of Alternaria, resulting in a significant linear regression model (R2 = 0.41; p < 0.001). TOMCAST was adapted to the area, considering 10 °C the minimum threshold for the mean value of temperature during the wet period and 10–15 accumulated disease severity values (DSV). Using TOMCAST, it was possible to predict the first Alternaria peak in most of potato growing seasons. Combining aerobiological and meteorological data to control fungal diseases during crops are a useful tool for sustainable agriculture. [ABSTRACT FROM AUTHOR]

The palynological and physicochemical analysis of 62 honey samples produced in different biogeographical areas of Algeria was conducted. Results showed high variety in the botanical origin of samples and their physicochemical profile. Twenty-six samples were polyfloral honey, 30 were unifloral honey from different botanical sources such as Eucalyptus, Citrus, Apiaceae, Punica, Erica, Rosmarinus, Eriobotrya, or Hedysarum, and 6 were characterized as honeydew honey. Pollen analysis allowed the identification of 104 pollen types belonging to 51 botanical families, whereas the physicochemical profile showed important variations between samples. Multivariate techniques were used to compare the characteristics of samples from different biogeographical areas, showing significant differences between humid-area samples, located in the northeast of the country, and samples taken in semiarid, subhumid, and arid zones. Principal-component analysis (PCA) extracted nine components explaining 72% of data variance, being 30%, the sum of Component 1 and Component 2. The plot of both components showed samples grouped upon botanical and geographical origin. The results of this paper highlighted the great variability in honey production of Algeria, evidencing the importance of honey characterization to guarantee authenticity and to valorize local production. [ABSTRACT FROM AUTHOR]

The development of a potato crop differs according to the environmental conditions and growing season of an area. Periods of high temperatures and drought have been frequent in recent years, and this has affected crops worldwide. The effect of meteorological factors on the plant morphology of potato cultivars growing in A Limia was analyzed for three consecutive years. The crop cycle with the highest temperatures and least accumulated rainfall (2016) showed plants with a higher number of leaflets, which were shorter in length. The crop cycle (2014) with a lower temperature and more rainfall had the tallest plants, the highest degree of flowering, fewer pairs of leaflets and the highest length of the floral peduncle. Kennebec and Fontane were the varieties that showed the least variability in morphological characteristics during the seasons analyzed. Considering the meteorological and morphological data, a principal component analysis was carried out, which explained 80.1% of the variance of the data. Spearman rank correlations showed higher significant coefficients between the temperature and foliar characteristics. The leaf size of plants was estimated using a multiple linear regression analysis, which included the mean temperature, explaining 64% of the variability of the data. [ABSTRACT FROM AUTHOR]

This Special Issue contains innovative research papers on the characterization, chemical composition and physical properties of honey. This constitutes very useful information to avoid frauds and to guarantee the authenticity of this food product. The knowledge of the particularities of honey is increasingly demanded by beekeepers and consumers, and also by labs to typify honeys according to their botanical origin and to check their quality. Melissopalynological, sensorial and physicochemical techniques are being used to study the characteristics of honeys samples from different plant sources and geographical areas. The combination of these analytical techniques with mathematical and statistical methods or chemometrics allows researchers to identify a set of variables or individual parameters that define independent samples, providing a practical solution to classify honey according to the geographical or the botanical origin. [ABSTRACT FROM AUTHOR]

Potato early blight caused by Alternaria solani generates significant economic losses in crops worldwide. Forecasting the risk of infection on crops is indispensable for the management of the fungal disease, ensuring maximum economic benefit but with minimal environmental impact. This work aimed to calculate the interrupted wet periods (IWP) according to the climate conditions of A Limia (Northwest of Spain) to optimize the prediction against early blight in potatoes. The study was performed during nine crop cycles. The relative hourly humidity and Alternaria concentration in the crop environment were taken into account. Alternaria levels were monitored by aerobiological techniques using a LANZONI VPPS-2000 volumetric trap. The relationships between weather conditions and airborne Alternaria concentration were statistically analyzed using Spearman correlations. To establish the effectiveness of wetness periods, the first important Alternaria peak was taken into account in each crop cycle (with a concentration greater than 70 spores/m3). Considering the six interrupted wet periods of the system, it was possible to predict the first peak of Alternaria several days in advance (between 6 and 38 days), except in 2007 and 2018. Automated systems to predict the initiation of early blight in potato crop, such as interrupted wet periods, could be an effective basis for developing decision support systems. The incorporation of aerobiological data for the calculation of interrupted wet periods improved the results of this system. [ABSTRACT FROM AUTHOR]

Honey color and other physicochemical characteristics depend mainly on the botanical and geographical origin. The study of these properties could make easier a correct classification of unifloral honey. This work determined the palynological characteristics and some physicochemical properties such as pH, electrical conductivity, and color (Pfund scale and the CIELa*b* coordinates), as well as the total content of the bioactive compounds phenols and flavonoids of ninety-three honey samples. Samples were classified as chestnut, blackberry, heather, eucalyptus, and honeydew honey. The study showed a close relationship between the physicochemical variables and the botanical origin. The five types of honey presented different physicochemical properties among them. A principal component analysis showed that Hue, lightness, b*, and Chroma variables were important for the honey types classification, followed by Erica pollen, pH, Cytisus, and Castanea variables. A forward stepwise regression analysis was performed introducing as dependent variables the color (mm Pfund) and the Chroma and the Hue variables. The regression models obtained explained 86%, 74%, and 86% of the variance of the data, respectively. The combination of the chromatic and physicochemical and pollen variables through the use of multivariable methods was optimal to characterize and group the honey samples studied. [ABSTRACT FROM AUTHOR]

This work investigates the similarities and differences of oak honeydew (Quercus pyrenaica Willd.) and evergreen honeydew (Quercus ilex L.) honey produced in Spain. For this purpose, the physicochemical characteristics of 17 samples from oak honeydew and 11 samples from evergreen honeydew collected in different geographical regions were analyzed. All the samples accomplished European Union requirements for honey consumption. Both honey types had amber dark color; however, the evergreen oak honey was clearer than oak honey, having higher mean values in a* and b* coordinates of CIELab scale. In general, both honey types exhibited high electrical conductivity, a moderate value of pH, medium to low water content, and high diastase activity. The reducing sugar content was significantly lower and maltose content was significantly higher in evergreen honeydew. In addition, total phenols and total flavonoid contents, the antioxidant activity and the melissopalynological analysis was performed. The oak honeydew honey had a higher abundance of Castanea, Rubus and Erica pollen grains, while the evergreen oak honeydew honey had a higher abundance of Lavandula, Olea europaea or Anthyllis cytisoides. A multivariate analysis using the most representative pollen types and physicochemical components facilitated the differentiation of the honey samples, thus this information can be useful for the honey characterization. [ABSTRACT FROM AUTHOR]

The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption.