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.

Synergistic effects of abiotic stresses in plants: a case study of nitrogen limitation and saturating light intensity in Arabidopsis thaliana.

Under natural conditions, plants are regularly exposed to combinations of stress factors. A common example is the conjunction between nitrogen (N) deficiency and excess light. The combined effect of stress factors is often ignored in studies using controlled conditions, possibly resulting in misleading conclusions. To address this issue, the present study examined the physiological behavior of Arabidopsis thaliana under the effect of varying nitrogen levels and light intensities. The joint influence of low N and excess light had an adverse effect on plant growth, chlorophyll and anthocyanin concentrations, photochemical capacity and the abundance of proteins involved in carbon assimilation and antioxidative metabolism. In contrast, no adverse physiological responses were observed for plants under either nitrogen limitation or high light (HL) intensity conditions (i.e. single stress). The underlying mechanisms for the increased growth in conditions of HL and sufficient nitrogen were a combination of chlorophyll accumulation and an increased number of proteins involved in C3 carbon assimilation, amino acids biosynthesis and chloroplast development. In contrast, combined stress conditions shifts plants from growth to survival by displaying anthocyanin accumulation and an increased number of proteins involved in catabolism of lipids and amino acids as energy substrates. Ultimately switching plants development from growth to survival. Our results suggest that an assessment of the physiological response to the combined effect of multiple stresses cannot be directly extrapolated from the physiological response to a single stress. Specifically, the synergistic interaction between N deficiency and saturating light in Arabidopsis plants could not have been modeled via only one of the stress factors.

The effects of elevated CO2 and nitrogen nutrition on root dynamics.

Ambient CO2 concentration is currently 400 µmol mol-1, and projections forecast an increase up to 970 µmol mol-1 by century's end. Elevated CO2 can stimulate C3 plant growth, whereas nitrogen is the main nutrient plants acquire from soils and often limits growth. Plants primarily obtain two nitrogen sources from the soil, ammonium (NH4+) and nitrate (NO3-). At elevated CO2 levels, plant growth and nitrogen metabolism is affected by the nitrogen source. Most research has focused on shoot traits, while neglecting the plants' hidden half, the root. We studied the effects of elevated CO2 and nitrogen source on hydroponically grown tomato plants, a C3 model and crop plant. Our main objective was to determine how the nitrogen source and elevated CO2 affect root development. Our results indicate they affect development in terms of the size and anatomy of different root orders. Specifically, root xylem development was found sensitive to the nitrogen source, whereas NO3--supplied plants displayed greater xylem development compared to their NH4+ counterparts, and also to a lesser extent, to elevated CO2, which we found inhibits this development. Additionally, elevated CO2 decreased root respiration in different root orders exclusively in plants supplied with NH4+as the sole nitrogen source.

The potential of the spectral 'water balance index' (WABI) for crop irrigation scheduling.

Hyperspectral sensing can detect slight changes in plant physiology, and may offer a faster and nondestructive alternative for water status monitoring. This premise was tested in the current study using a narrow-band 'water balance index' (WABI), which is based on independent changes in leaf water content (1500 nm) and the efficiency of the nonphotochemical quenching (NPQ) photo-protective mechanism (531 nm). The hydraulic, photo-protective and spectral behaviors of five important crops - grapevine, corn, tomato, pea and sunflower - were evaluated under water deficit conditions in order to associate the differences in stress physiology with WABI suitability. Rapid alterations in both leaf water content and NPQ were observed in grapevine, pea and sunflower, and were effectively captured by WABI. Apart from water status monitoring, the index was also successful in scheduling the irrigation of a vineyard, despite phenological and environmental variability. Conversely, corn and tomato displayed a relatively strict stomatal regime and/or mild NPQ responses and were, thus, unsuitable for WABI-based monitoring. WABI shows great potential for irrigation scheduling of various crops, and has a clear advantage over spectral models that focus on either of the abovementioned physiological mechanisms.

Recognition of Orobanche cumana Below-Ground Parasitism Through Physiological and Hyper Spectral Measurements in Sunflower (Helianthus annuus L.).

Broomrape (Orobanche and Phelipanche spp.) parasitism is a severe problem in many crops worldwide, including in the Mediterranean basin. Most of the damage occurs during the sub-soil developmental stage of the parasite, by the time the parasite emerges from the ground, damage to the crop has already been done. One feasible method for sensing early, below-ground parasitism is through physiological measurements, which provide preliminary indications of slight changes in plant vitality and productivity. However, a complete physiological field survey is slow, costly and requires skilled manpower. In recent decades, visible to-shortwave infrared (VIS-SWIR) hyperspectral tools have exhibited great potential for faster, cheaper, simpler and non-destructive tracking of physiological changes. The advantage of VIS-SWIR is even greater when narrow-band signatures are analyzed with an advanced statistical technique, like a partial least squares regression (PLS-R). The technique can pinpoint the most physiologically sensitive wavebands across an entire spectrum, even in the presence of high levels of noise and collinearity. The current study evaluated a method for early detection of Orobanche cumana parasitism in sunflower that combines plant physiology, hyperspectral readings and PLS-R. Seeds of susceptible and resistant O. cumana sunflower varieties were planted in infested (15 mg kg-1 seeds) and non-infested soil. The plants were examined weekly to detect any physiological or structural changes; the examinations were accompanied by hyperspectral readings. During the early stage of the parasitism, significant differences between infected and non-infected sunflower plants were found in the reflectance of near and shortwave infrared areas. Physiological measurements revealed no differences between treatments until O. cumana inflorescences emerged. However, levels of several macro- and microelements tended to decrease during the early stage of O. cumana parasitism. Analysis of leaf cross-sections revealed differences in range and in mesophyll structure as a result of different levels of nutrients in sunflower plants, manifesting the presence of O. cumana infections. The findings of an advanced PLS-R analysis emphasized the correlation between specific reflectance changes in the SWIR range and levels of various nutrients in sunflower plants. This work demonstrates potential for the early detection of O. cumana parasitism on sunflower roots using hyperspectral tools.

The effect of differential growth rates across plants on spectral predictions of physiological parameters.

Leaves of various ages and positions in a plant's canopy can present distinct physiological, morphological and anatomical characteristics, leading to complexities in selecting a single leaf for spectral representation of an entire plant. A fortiori, as growth rates between canopies differ, spectral-based comparisons across multiple plants--often based on leaves' position but not age--becomes an even more challenging mission. This study explores the effect of differential growth rates on the reflectance variability between leaves of different canopies, and its implication on physiological predictions made by widely-used spectral indices. Two distinct irrigation treatments were applied for one month, in order to trigger the formation of different growth rates between two groups of grapevines. Throughout the experiment, the plants were physiologically and morphologically monitored, while leaves from every part of their canopies were spectrally and histologically sampled. As the control vines were constantly developing new leaves, the water deficit plants were experiencing growth inhibition, resulting in leaves of different age at similar nodal position across the treatments. This modification of the age-position correlation was characterized by a near infrared reflectance difference between younger and older leaves, which was found to be exponentially correlated (R(2) = 0.98) to the age-dependent area of intercellular air spaces within the spongy parenchyma. Overall, the foliage of the control plant became more spectrally variable, creating complications for intra- and inter-treatment leaf-based comparisons. Of the derived indices, the Structure-Insensitive Pigment Index (SIPI) was found indifferent to the age-position effect, allowing the treatments to be compared at any nodal position, while a Normalized Difference Vegetation Index (NDVI)-based stomatal conductance prediction was substantially affected by differential growth rates. As various biotic and abiotic factors may form distinctions in growth, future precision agriculture studies should consider its spectral effect on physiological predictions.