Optimization of sweet basil harvest time and cultivar characterization using near-infrared spectroscopy, liquid and gas chromatography, and chemometric statistical methods.

BACKGROUND: Terpene, eugenol and polyphenolic contents of basil are major determinants of quality, which is affected by genetics, weather, growing practices, pests and diseases. Here, we aimed to develop a simple predictive analytical method for determining the polyphenol, eugenol and terpene content of the leaves of major Israeli sweet basil cultivars grown hydroponically, as a function of harvest time, through the use of near-infrared (NIR) spectroscopy, liquid/gas chromatography, and chemometric methods. We also wanted to identify the harvest time associated with the highest terpene, eugenol and polyphenol content. RESULTS: Six different cultivars and four different harvest times were analyzed. Partial least square regression (PLS-R) analysis yielded an accurate, predictive model that explained more than 93% of the population variance for all of the analyzed compounds. The model yielded good/excellent prediction (R2 > 0.90, R2 cv and R2 pre > 0.80) and very good residual predictive deviation (RPD > 2) for all of the analyzed compounds. Concentrations of rosmarinic acid, eugenol and terpenes increased steadily over the first 3 weeks, peaking in the fourth week in most of the cultivars. Our PLS-discriminant analysis (PLS-DA) model provided accurate harvest classification and prediction as compared to cultivar classification. The sensitivity, specificity and accuracy of harvest classification were larger than 0.82 for all harvest time points, whereas the cultivar classification, resulted in sensitivity values lower than 0.8 in three cultivars. CONCLUSION: The PLS-R model provided good predictions of rosmarinic acid, eugenol and terpene content. Our NIR coupled with a PLS-DA demonstrated reasonable solution for harvest and cultivar classification. © 2021 Society of Chemical Industry.

Microbiome dynamics during ensiling of corn with and without Lactobacillus plantarum inoculant.

Microbial population dynamics associated with corn silage, with and without Lactobacillus plantarum treatment, was studied. Whole crop corn was ensiled using laboratory silos and sampled at different times, up to 3 months. The dominant bacteria, before ensiling, were Acinetobacter (38.5%) and Klebsiella (16.3%), while the dominant fungi were Meyerozyma (53.5%) and Candida (27.7%). During ensiling, the microbial population shifted considerably, and Lactobacillus (> 94%) and Candida (> 74%) became the most dominant microbial genera in both treated and untreated silages. Yet, lactic acid content was higher in the treated silage, while the microbial diversity was lower than in the untreated silage. Upon aerobic exposure, spoilage occurred more rapidly in the treated silage, possibly due to the higher abundance of lactic acid-assimilating fungi, such as Candida. Our study is the first to describe microbial population dynamics during whole-crop corn ensiling and the results indicate that microbial diversity may be an indicator of aerobic stability.

Lithium salts: assessment of their chronic and acute toxicities to honey bees and their anti-Varroa field efficacy.

BACKGROUND: Varroa control is essential for the maintenance of healthy honey bee colonies. Overuse of acaricides has led to the evolution of resistance to those substances. Studies of the short-term acaricidal effects and safety of various lithium (Li) salts recently have been reported. This study examined the long-term in vitro and in vivo bee toxicities, short-term motor toxicity to bees and long-term anti-Varroa field efficacy of several Li salts. RESULTS: In an in vitro chronic-toxicity assay, lithium citrate (18.8 mm) was the most toxic of the examined salts, followed by lithium lactate (29.5 mm), and lithium formate (32.5 mm). In terms of acute locomotor toxicity to bees, all of the Li salts were well-tolerated and none of the treatment groups differed from the negative control group. In an in vitro survival study, all of the Li treatments significantly reduced bee life spans by a factor of 1.8-7.2, as compared to the control. In terms of life expectancy, lithium citrate was the most toxic salt, with no significant differences noted between lithium formate and lithium lactate. In the bee-mortality field study, none of the examined treatments differed from the negative control. Amitraz and lithium formate exhibited similar acaricide effects, which were significantly different from those observed for lithium lactate and the negative control. CONCLUSION: In light of lithium formate's honey bee safety and efficacy as an acaricide, additional sublethal toxicity studies in brood, drones and queens, as well as tests aimed at the optimization of administration frequency are warranted. © 2022 Society of Chemical Industry.

Use of near-infrared spectroscopy for the classification of medicinal cannabis cultivars and the prediction of their cannabinoid and terpene contents.

Cannabis sativa L. is used to treat a wide variety of medical conditions, in light of its beneficial pharmacological properties of its cannabinoids and terpenes. At present, the quantitative chemical analysis of these active compounds is achieved through the use of laborious, expensive, and time-consuming technologies, such as high-pressure liquid-chromatography- photodiode arrays, mass spectrometer detectors (HPLC-PDA or MS), or gas chromatography-mass spectroscopy (GC-MS). Hence, we aimed to develop a simple, accurate, fast, and cheap technique for the quantification of major cannabinoids and terpenes using Fourier transform near infra-red spectroscopy (FT-NIRS). FT-NIRS was coupled with multivariate classification and regression models, namely partial least square-discriminant analysis (PLS-DA) and partial least squares regression (PLS-R) models. The PLS-DA model yielded an absolute major class separation (high-THC, high-CBD, hybrid, and high-CBG) and perfect class prediction. Using only three latent variables (LVs), the cross-validation and prediction model errors indicated a low probability of over-fitting the data. In addition, the PLS-DA model enabled the classification of chemovars with genetic-chemical similarities. The classification of high-THCA chemovars was more sensitive and more specific than the classifications of the remaining chemovars. The prediction of cannabinoid and terpene concentrations by PLS-R yielded 11 robust models with high predictive capabilities (R2CV and R2pred > 0.8, RPD >2.5 and RPIQ >3, RMSECV/RMSEC ratio <1.2) and additional 15 models whose performance was acceptable for initial screening purposes (R2CV > 0.7 and R2pred < 0.8, RPD >2 and RPIQ <3, 1.2 < RMSECV/RMSEC ratio <2). Our results confirm that there is sufficient information in the FT-NIRS to develop cannabinoid and terpene prediction models and major-cultivar classification models.

Multivariate classification of cannabis chemovars based on their terpene and cannabinoid profiles.

Cannabis is used to treat various medical conditions, and lines are commonly classified according to their total concentrations of Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD). Based on their ratio of total THC to total CBD, cannabis cultivars are commonly classified into high-THC, high-CBD, and hybrid classes. While cultivars from the same class have similar compositions of major cannabinoids, their levels of other cannabinoids and their terpene compositions may differ substantially. Therefore, a more comprehensive and accurate classification of medicinal cannabis cultivars, based on a large number of cannabinoids and terpenes is needed. For this purpose, three different chemometric-based classification models were constructed using three sets of chemical profiles. We examined those models to determine which provides the most accurate "chemovar" classification. This was done by analyzing profiles of cannabinoids, terpenes, and the combination of these substances using the partial least square-discriminant analysis multivariate (PLS-DA) technique. The chemical profiles were selected from the three major classes of medicinal cannabis that are most commonly prescribed to patients in Israel: high-THC, high-cannabigerol (CBG), and hybrid. We studied the correlations between cannabinoids and terpenes to identify major bio-indicators representing the plant's terpene and cannabinoid content. All three PLS-DA models provided highly accurate classifications, utilizing six to nine latent variables with an overall accuracy ranging from 2 to 11% CV. The PLS-DA model applied to the combined cannabinoid-and-terpene profile did the best job of differentiating between the chemovars in terms of misclassification error, sensitivity, specificity, and accuracy. The combined cannabinoid-and-terpene PLS-DA profile had cross-validation and prediction misclassification errors of 4% and 0%, respectively. This is the first study to demonstrate the highly accurate classification of samples of medicinal cannabis based on their cannabinoid and terpene profiles, as compared to cannabinoid profiles alone. Furthermore, our correlation analysis indicated that 11 cannabinoids and terpenes might serve as bio-indicators for 32 different active compounds. These findings suggest that the use of multivariate statistics could assist in breeding studies and serve as a tool for minimizing the mislabeling of cannabis inflorescences.

Depletion kinetics and concentration- and time-dependent toxicity of a tertiary mixture of amitraz and its major hydrolysis products in honeybees.

Although amitraz is one of the acaricides most commonly applied within beehives, to date, its time-dependent oral toxicity in honeybees has not been investigated, due to amitraz's instability in aqueous media. In aqueous media such as honey, amitraz rapidly forms a continuously changing tertiary mixture with two of its major hydrolysis products, DMF and DMPF. The contribution of each hydrolysis product to the overall oral toxicity of this acaricide is not known. Therefore, we aimed to characterize the depletion and formation kinetics of amitraz and its hydrolysis products in 50% sucrose solution provided to caged honeybees, including the calculation of the 50% lethal oral concentration (LC50) of amitraz. We sought to determine the contribution of each component of the mixture to the overall observed toxicity. We also investigated the time- and concentration-dependent toxicity of the amitraz mixture and its hydrolysis products. A novel approach based on the analysis of the areas under the depletion and formation curves of amitraz and its hydrolysis products revealed that DMPF, amitraz and DMF accounted for 92%, 7% and 1% (respectively) of the overall toxicity of the mixture. The chronic oral LC50 of amitraz was 3300 µmol/L, of similar magnitude as that of the non-toxic hydrolysis product DMF. The toxicity of DMPF and the mixture decreased over time; whereas the toxicity of DMF increased over time. Amitraz's instability in aqueous media and the highly toxic profile of DMPF, suggest that DMPF is the actual toxic entity responsible for amitraz's toxicity toward honeybees.

Concentration- and time-dependent toxicity of commonly encountered pesticides and pesticide mixtures to honeybees (Apis mellifera L.).

Honeybees are exposed to a wide range of pesticides for long periods via contaminated water, pollen and nectar. Some of those pesticides might constitute health hazards in a time- and dose-dependent manner. Time-dependent toxicity profiles for many applied pesticides are lacking, despite the fact that such profiles are crucial for toxicological evaluations. Therefore, we sought to determine the time-dependent toxicities of pesticides/pesticide metabolites frequently found in Israeli beehives, namely, amitraz metabolites, N'-(2,4-dimethylphenyl)-N-methylformamidine (DMPF) and N-(2,4-dimethylphenyl)-formamide (DMF), coumaphos, imidacloprid, thiacloprid, acetamiprid and dimethoate (toxic reference). By applying accepted methodological approaches such as the modified Haber's rule (product of concentration and exposure duration leads to a constant effect) and comparisons between cumulative doses at different time points, we determined the time-dependent toxicities of these pesticides. We also studied the mixture toxicities of frequently occurring pesticide combinations and estimated their potential contributions to the overall toxicities of neonicotinoids. Thiacloprid was the only pesticide that complied with Haber's rule. DMPF, dimethoate and imidacloprid exhibited time-diminished -toxicities. In contrast, DMF and acetamiprid exhibited time-reinforced toxicities. Neither the binary mixtures nor the tertiary mixtures of DMF, DMPF and coumaphos at 10 times their environmentally relevant concentrations potentiated the neonicotinoids' toxicities. DMPF and imidacloprid were found to present the greatest hazard to honeybees, based on their 50% lethal cumulative dose and 50% lethal time. Amitraz's instability, its low detection frequency and high toxicity profile of its metabolite, DMPF, lead us to the conclusion that DMPF constitutes the actual toxic entity responsible for amitraz's toxic effect.

Human pharmaceutical and pesticide residues in Israeli dairy milk in association with dietary risk assessment.

Throughout the world, more than six billion people consume milk and milk products yearly. The safety and quality of dairy milk are regularly monitored in most countries worldwide. The Israeli monitoring program of chemical residues in milk has not changed in the last decades, focusing only on major veterinary drugs and few selected environmental contaminants such as heavy metals and persistent organic pollutants. Consequently, a knowledge gap exists regarding the potential occurrence of other chemicals such as human pharmaceuticals and non-monitored pesticides in milk. In this survey, 51 commercial bovine and goat milk samples were analysed by LC-MS/MS and pharmaceutical and pesticide residues are reported in the range of 0.1-93 µg/L. Israeli milk samples revealed at least one and up to five chemical residues simultaneously. The pesticides found in milk were below the European maximum residue limit values. The risk assessment performed, indicated negligible risk.

Postharvest Fungicide for Avocado Fruits: Antifungal Efficacy and Peel to Pulp Distribution Kinetics.

Postharvest application of fungicides is commonly applied in order to reduce food loss. Prochloraz is currently the only postharvest fungicide registered in Israel and Europe in avocado fruits. Due to its unfavorable toxicological properties, prochloraz will be banned from the end of 2020 for future postharvest usage and therefore a substitute candidate is urgently warranted. Fludioxonil, a relatively safe, wide spectrum fungicide, is approved in Europe and Israel for postharvest use in various fruits, but not avocado. Hence, fludioxonil has been evaluated in the present study as a potential substitute for prochloraz in avocado. The objectives of the present study were to determine fludioxonil efficacy against common fungal infestations in avocado and distribution kinetics between peel and pulp in comparison to prochloraz. At the same concentration range (75-300 µg/L), fludioxonil was as effective as prochloraz in inhibiting postharvest decay, while in the early season cultivars, suffering mainly from stem-end rot, it exhibited a better decay control than prochloraz. Fludioxonil and prochloraz displayed negligible and undetected pulp levels, respectively, due to low peel penetrability. Taken altogether, fludioxonil was found to be a suitable candidate for replacing prochloraz as a postharvest fungicide in avocado.

Pesticide and trace element residues in honey and beeswax combs from Israel in association with human risk assessment and honey adulteration.

Beehive products are considered sentinels for environmental pollutants. The presence of trace elements and pesticides in honey and beeswax may pose a health hazard to consumers. The study's aim was to determine the profile of pesticides and trace elements in Israeli honey and beeswax samples in relation to human risk assessment. At least two pesticides contaminated the honey and beeswax samples simultaneously, in which, amitraz metabolites and coumaphos were frequently detected. The neonicotinoid insecticides and 2,4-dichlorophenoxyacetic acid, were found only in honey samples, whereas the more lipophilic pesticides were predominantly found in beeswax. In honey, chromium displayed the highest mean concentration, followed by zinc, whereas lead and molybdene occurred only in beeswax. Our findings indicate that the daily consumption of honey and beeswax together may compromise children's health. Sucrose-syrup fed honey could not be distinguished from floral honey based on sugar profile, rather by its trace elements levels.

Bacterial Dynamics of Wheat Silage.

Knowledge regarding bacterial dynamics during crop ensiling is important for understanding of the fermentation process and may facilitate the production of nutritious and stable silage. The objective of this study was to analyze the bacterial dynamics associated with whole crop wheat silage with and without inoculants. Whole crop wheat was ensiled in laboratory silos, with and without Lactobacillus inoculants (L. plantarum, L. buchneri), for 3 months. Untreated and L. plantarum-treated silages were sampled at several times during ensiling, while L. buchneri-treated silage was sampled only at 3 months. Bacterial composition was studied using next generation sequencing approach. Dominant bacteria, before ensiling, were Pantoea (34.7%), Weissella (28.4%) and Pseudomonas (10.4%), Exiguobacterium (7.8%), and Paenibacillus (3.4%). Exogenous inoculants significantly affected bacterial composition and dynamics during ensiling. At 3 months of ensiling, Lactobacillus dominated the silage bacterial population and reached an abundance of 59.5, 92.5, and 98.2% in untreated, L. plantarum- and L. buchneri-treated silages, respectively. The bacterial diversity of the mature silage was lower in both treated silages compared to untreated silage. Functional profiling of the bacterial communities associated with the wheat ensiling demonstrated that the abundant pathways of membrane transporters, carbohydrate and amino acids metabolisms followed different pattern of relative abundance in untreated and L. plantarum-treated silages. Only three pathways, namely base-excision repair, pyruvate metabolism and transcription machinery, were significantly different between untreated and L. buchneri-treated silages upon maturation. Lactic acid content was higher in L. plantarum-treated silage compared to untreated and L. buchneri-treated silage. Still, the pH of both treated silages was lower in the two Lactobacillus-treated silages compared to untreated silage. Aerobic stability test demonstrated that L. plantarum-, but not L. buchneri-supplement, facilitated silage deterioration. The lower aerobic stability of the L. plantarum-treated silage may be attributed to lower content of acetic acid and other volatile fatty acids which inhibit aerobic yeasts and molds. Indeed, high yeast count was recorded, following exposure to air, only in L. plantarum-treated silage, supporting this notion. Analysis of bacterial community of crop silage can be used for optimization of the ensiling process and the selection of appropriate inoculants for improving aerobic stability.

Pesticide distribution and depletion kinetic determination in honey and beeswax: Model for pesticide occurrence and distribution in beehive products.

Beehive products such as honey, beeswax and recently pollen have been regarded for many years as appropriate sentinels for environmental pesticide pollutions. However, despite yearly application of hundreds of approved pesticides in agricultural fields, only a minor fraction of these organic compounds were actually detected in honey and beeswax samples. This observation has led us to question the general suitability of beehive products as a sentinel for synthetic organic pesticides applied in the field. The aim of the present study was to experimentally determine the distribution (logarithmic ratio of beeswax to honey pesticide concentration, LogD) and depletion kinetics (half-life) of selected pesticides in honey and beeswax as a measure of the latter matrixes to serve as a pesticide sentinel. The obtained parameters were used to extrapolate to pesticide burden in honey and beeswax samples collected from German and Israeli apiaries. In addition, we aimed to establish a mathematical model, enabling us to predict distribution of selected pesticides between honey to beeswax, by utilizing simple substance descriptors, namely, octanol/water partitioning coefficient, molar weight and Henry coefficient. Based on the present results, it appears that pesticides with LogD values > 1 and half-life in beeswax > 1 day, were likely to accumulate and detected in beeswax samples, and less likely to be found in honey. On the other hand, pesticides with negative LogD values were highly likely to be found in honey and less so in beeswax samples. Finally, pesticides with LogD values between 0-1 were expected to be found in both matrixes. The developed model was successfully applied to predict LogD values, thereby identifying octanol/water partitioning and molar weight as the most prominent substance descriptors, which affect pesticide distribution between honey and beeswax.

Lactic acid bacteria used in inoculants for silage as probiotics for ruminants.

Many studies have shown the beneficial effects on ruminant performance of feeding them with silages inoculated with lactic acid bacteria (LAB). These benefits might derive from probiotic effects. The purpose of the current study was to determine whether LAB included in inoculants for silage can survive in rumen fluid (RF), as the first step in studying their probiotic effects. Experiments were conducted in the United States and Israel with clarified (CRF) and strained RF (SRF) that were inoculated at 10(6)-10(8) microorganisms/mL with and without glucose at 5 g/L. RF with no inoculants served as control. Ten commercial inoculants were used. The RF was incubated at 39 degrees C and sampled in duplicates at 6, 12, 24, 48, 72, and 96 h for pH and LAB counts. The results indicate that with glucose the pH of the RF decreased during the incubation period. In the SRF, the pH of the inoculated samples was higher than that of the controls in most cases. This might be a clue to the mechanism by which LAB elicit the enhancement in animal performance. LAB counts revealed that the inoculants survived in the RF during the incubation period. The addition of glucose resulted in higher LAB counts.

Nutritive and antioxidative potential of fresh and stored pomegranate industrial byproduct as a novel beef cattle feed.

Pomegranate peel is a nutritive-rich byproduct whose amounts are extensively growing due to the exponential increase in the production of pomegranate juice and "ready to eat" arils. Pomegranate peel is a rich source for antioxidants and thus may serve in the prevention of cattle diseases and in the improvement of beef products, making it an attractive component in beef cattle diets. The present study aims to evaluate the effect of commonly used storage practices on the nutritive and antioxidative properties of pomegranate peel. In general, storage conditions preserved most antioxidant capacity. Ensiling ambivalently affected the nutritive values of the peel and promoted increased levels of antioxidative components. In addition to polyphenols, nonphenolic components, such as alpha- and gamma-tocopherols, contributed to the total antioxidative capacity, and several minerals found in the peel added to its nutritional value. Dietary supplementation with fresh peels promoted significant increases in feed intake and alpha-tocopherol concentration in the plasma, with positive tendency toward increased weight gain of bull calves. All in all, the nutritive value and the antioxidant capacity of pomegranate peel turn it into a favorable health-promoting constituent of feedlot beef cattle diet.