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Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R2 = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities. [ABSTRACT FROM AUTHOR]

Atmospheric CO2 concentrations are predicted to double by the end of this century. Although the effects of CO2 fertilisation in crop systems have been well studied, little is known about the specific interactions among plants, pests and pathogens under a changing climate. This growth chamber study focuses on the interactions among Barley yellow dwarf virus (BYDV), its aphid vector (Rhopalosiphum padi) and wheat (Triticum aestivum L. cv. Yitpi) under ambient (aCO2; 400 μmol mol-1) or elevated (eCO2; 650 μmol mol-1) CO2 concentrations. eCO2 increased the tiller number and biomass of uninoculated plants and advanced the yellowing symptoms of infected plants. Total foliar C content (percentage of the total DW) increased with eCO2 and with sham inoculation (exposed to early herbivory), whereas total N content decreased with eCO2. Liquid chromatography-mass spectrometry approaches were used to quantify the products of primary plant metabolism. eCO2 significantly increased sugars (fructose, mannitol and trehalose), irrespective of disease status, whereas virus infection significantly increased the amino acids essential to aphid diet (histidine, lysine, phenylalanine and tryptophan) irrespective of CO2 concentration. Citric acid was reduced by both eCO2 and virus infection. Both the potential positive and negative biochemical impacts on wheat, aphid and BYDV interactions are discussed. [ABSTRACT FROM AUTHOR]

The rapid identification and quantitation of alkaloids produced by Epichloë endophyte-infected pasture grass is important for the agricultural industry. Beneficial alkaloids, such as peramine, provide the grass with enhanced insect protection. Conversely, ergovaline and lolitrem B can negatively impact livestock. Currently, a single validated method to measure these combined alkaloids in planta does not exist. Here, a simple two-step extraction method was developed for Epichloë-infected perennial ryegrass (Lolium perenne L.). Peramine, ergovaline and lolitrem B were quantified using liquid chromatography–mass spectrometry (LC–MS). Alkaloid linearity, limit of detection (LOD), limit of quantitation (LOQ), accuracy, precision, selectivity, recovery, matrix effect and robustness were all established. The validated method was applied to eight different ryegrass-endophyte symbiota. Robustness was established by comparing quantitation results across two additional instruments; a triple quadruple mass spectrometer (QQQ MS) and by fluorescence detection (FLD). Quantitation results were similar across all three instruments, indicating good reproducibility. LOQ values ranged from 0.8 ng/mL to 6 ng/mL, approximately one hundred times lower than those established by previous work using FLD (for ergovaline and lolitrem B), and LC–MS (for peramine). This work provides the first highly sensitive quantitative LC–MS method for the accurate and reproducible quantitation of important endophyte-derived alkaloids. [ABSTRACT FROM AUTHOR]

Indole-diterpenes are an important class of chemical compounds which can be unique to different fungal species. The highly complex lolitrem compounds are confined to Epichloë species, whilst penitrem production is confined to Penicillium spp. and Aspergillus spp. These fungal species are often present in association with pasture grasses, and the indole-diterpenes produced may cause toxicity in grazing animals. In this review, we highlight the unique structural variations of indole-diterpenes that are characterised into subgroups, including paspaline, paxilline, shearinines, paspalitrems, terpendoles, penitrems, lolitrems, janthitrems, and sulpinines. A detailed description of the unique biological activities has been documented where even structurally related compounds have displayed unique biological activities. Indole-diterpene production has been reported in two classes of ascomycete fungi, namely Eurotiomycetes (e.g., Aspergillus and Penicillium) and Sordariomycetes (e.g., Claviceps and Epichloë). These compounds all have a common structural core comprised of a cyclic diterpene skeleton derived from geranylgeranyl diphosphate (GGPP) and an indole moiety derived from tryptophan. Structure diversity is generated from the enzymatic conversion of different sites on the basic indole-diterpene structure. This review highlights the wide-ranging biological versatility presented by the indole-diterpene group of compounds and their role in an agricultural and pharmaceutical setting. [ABSTRACT FROM AUTHOR]

Introduction: The aphid Rhopalosiphum padi L. is a vector of Barley yellow dwarf virus (BYDV) in wheat and other economically important cereal crops. Increased atmospheric CO2 has been shown to alter plant growth and metabolism, enhancing BYDV disease in wheat. However, the biochemical influences on aphid metabolism are not known.Objectives: This work aims to determine whether altered host-plant quality, influenced by virus infection and elevated CO2, impacts aphid weight and metabolism.Methods: Untargeted 1H NMR metabolomics coupled with multivariate statistics were employed to profile the metabolism of R. padi reared on virus-infected and non-infected (sham-inoculated) wheat grown under ambient CO2 (aCO2, 400 µmol mol−1) and future, predicted elevated CO2 (eCO2, 650 µmol mol−1) concentrations. Un-colonised wheat was also profiled to observe changes to host-plant quality (i.e., amino acids and sugars).Results: The direct impacts of virus or eCO2 were compared. Virus presence increased aphid weight under aCO2 but decreased weight under eCO2; whilst eCO2 increased non-viruliferous (sham) aphid weight but decreased viruliferous aphid weight. Discriminatory metabolites due to eCO2 were succinate and sucrose (in sham wheat), glucose, choline and betaine (in infected wheat), and threonine, lactate, alanine, GABA, glutamine, glutamate and asparagine (in aphids), irrespective of virus presence. Discriminatory metabolites due to virus presence were alanine, GABA, succinate and betaine (in wheat) and threonine and lactate (in aphids), irrespective of CO2 treatment.Conclusion: This study confirms that virus and eCO2 alter host-plant quality, and these differences are reflected by aphid weight and metabolism. [ABSTRACT FROM AUTHOR]

Atmospheric CO2 concentrations are predicted to double by the end of this century. Although the effects of CO2 fertilisation in crop systems have been well studied, little is known about the specific interactions among plants, pests and pathogens under a changing climate. This growth chamber study focuses on the interactions among Barley yellow dwarf virus (BYDV), its aphid vector (Rhopalosiphum padi) and wheat (Triticum aestivum L. cv. Yitpi) under ambient (aCO2; 400µmolmol-1) or elevated (eCO2; 650µmolmol-1) CO2 concentrations. eCO2 increased the tiller number and biomass of uninoculated plants and advanced the yellowing symptoms of infected plants. Total foliar C content (percentage of the total DW) increased with eCO2 and with sham inoculation (exposed to early herbivory), whereas total N content decreased with eCO2. Liquid chromatography-mass spectrometry approaches were used to quantify the products of primary plant metabolism. eCO2 significantly increased sugars (fructose, mannitol and trehalose), irrespective of disease status, whereas virus infection significantly increased the amino acids essential to aphid diet (histidine, lysine, phenylalanine and tryptophan) irrespective of CO2 concentration. Citric acid was reduced by both eCO2 and virus infection. Both the potential positive and negative biochemical impacts on wheat, aphid and BYDV interactions are discussed.