Late Pleistocene osseous projectile point from the Manis site, Washington-Mastodon hunting in the Pacific Northwest 13,900 years ago.

Bone fragments embedded in a rib of a mastodon (Mammut americanum) from the Manis site, Washington, were digitally excavated and refit to reconstruct an object that is thin and broad, has smooth, shaped faces that converge to sharp lateral edges, and has a plano-convex cross section. These characteristics are consistent with the object being a human-made projectile point. The 13,900-year-old Manis projectile point is morphologically different from later cylindrical osseous points of the 13,000-year-old Clovis complex. The Manis point, which is made of mastodon bone, shows that people predating Clovis made and used osseous weapons to hunt megafauna in the Pacific Northwest during the Bølling-Allerød.

Defining Fatty Acid Changes Linked to Rumen Development, Weaning and Growth in Holstein-Friesian Heifers.

After birth, as effectively monogastric animals, calves undergo substantial physiological changes to become ruminants by 3 months of age and reach sexual maturity at approximately 15 months of age. Herein, we assess longitudinal metabolomic changes in Holstein-Friesian (HF) heifers from birth until sexual maturity during this developmental process. Sera from 20 healthy, HF heifers were sampled biweekly from 2 weeks of age until 13 months of age and then monthly until 19 months of age. Sera were assessed using flow infusion electrospray high-resolution mass spectrometry (FIE-HRMS) on a Q Exactive hybrid quadrupole-Orbitrap mass spectrometer for high-throughput, sensitive, non-targeted metabolite fingerprinting. Partial least squares discriminant analysis (PLS-DA) and unsupervised hierarchical clustering analysis (HCA) of the derived metabolomes indicated changes detectable in heifers' sera over time. Time series analyses identified 30 metabolites that could be related to rumen development and weaning at ~3 months of age. Further time series analysis identified 40 metabolites that could be correlated with growth. These findings highlight the role of acetic acid and 3-phenylpropionate (3-PP) in rumen development and growth, suggest that weaning induces elevated levels of fatty acyls in response to a post-weaning stress-induced innate immune response and demonstrate the utilization of fatty acyls in growth. The identified metabolites offer serum metabolites which could inform the nutrition and healthy development of heifers.

Defining key metabolic roles in osmotic adjustment and ROS homeostasis in the recretohalophyte Karelinia caspia under salt stress.

The recretohalophyte Karelinia caspia is of forage and medical value and can remediate saline soils. We here assess the contribution of primary/secondary metabolism to osmotic adjustment and ROS homeostasis in Karelinia caspia under salt stress using multi-omic approaches. Computerized phenomic assessments, tests for cellular osmotic changes and lipid peroxidation indicated that salt treatment had no detectable physical effect on K. caspia. Metabolomic analysis indicated that amino acids, saccharides, organic acids, polyamine, phenolic acids, and vitamins accumulated significantly with salt treatment. Transcriptomic assessment identified differentially expressed genes closely linked to the changes in above primary/secondary metabolites under salt stress. In particular, shifts in carbohydrate metabolism (TCA cycle, starch and sucrose metabolism, glycolysis) as well as arginine and proline metabolism were observed to maintain a low osmotic potential. Chlorogenic acid/vitamin E biosynthesis was also enhanced, which would aid in ROS scavenging in the response of K. caspia to salt. Overall, our findings define key changes in primary/secondary metabolism that are coordinated to modulate the osmotic balance and ROS homeostasis to contribute to the salt tolerance of K. caspia.

Elucidating drought responsive networks in tef (Eragrostis tef) using phenomic and metabolomic approaches.

Drought is a major abiotic stress that limits crop productivity and is driving the need to introduce new tolerant crops with better economic yield. Tef (Eragrostis tef) is a neglected (orphan) Ethiopian warm-season annual gluten-free cereal with high nutritional and health benefits. Further, tef is resilient to environmental challenges such as drought, but the adaptive mechanisms remain poorly understood. In this study, metabolic changes associated with drought response in 11 tef accessions were identified using phenomic and metabolomic approaches under controlled conditions. Computerized image analysis of droughted plants indicated reductions in leaf area and green pigments compared with controls. Metabolite profiling based on flow-infusion electrospray-high-resolution mass spectroscopy (FIE-HRMS) showed drought associated changes in flavonoid, phenylpropanoid biosynthesis, sugar metabolism, valine, leucine and isoleucine biosynthesis, and pentose phosphate pathways. Flavonoid associated metabolites and TCA intermediates were lower in the drought group, whereas most of the stress-responsive amino acids and sugars were elevated. Interestingly, after drought treatment, one accession Enatite (Ent) exhibited a significantly higher plant area than the others, and greater accumulation of flavonoids, amino acids (serine and glycine), sugars (ribose, myo-inositol), and fatty acids. The increased accumulation of these metabolites could explain the increased tolerance to drought in Ent compared with other accessions. This is the first time a non-targeted metabolomics approach has been applied in tef, and our results provide a framework for a better understanding of the tef metabolome during drought stress that will help to identify traits to improve this understudied potential crop.

Methodology for performing biomechanical push-out tests for evaluating the osseointegration of calvarial defect repair in small animal models.

Push-out tests are frequently used to evaluate the bone-implant interfacial strength of orthopedic implants, particularly dental and craniomaxillofacial applications. There currently is no standard method for performing push-out tests on calvarial models, leading to a variety of inconsistent approaches. In this study, fixtures and methods were developed to perform push-out tests in accordance with the following design objectives: (i) the system rigidly fixes the explanted calvarial sample, (ii) it minimizes lateral bending, (iii) it positions the defect accurately, and (iv) it permits verification of the coaxial alignment of the defect with the push-out rod. The fixture and method was first validated by completing push-out experiments on 30 explanted murine cranial caps and two explanted leporine cranial caps, all induced with bilateral sub-critical defects (5.0 mm and 8.0 mm nominal diameter for the murine and leporine models, respectively). Defects were treated with an autograft (i.e., excised tissue flap), a shape memory polymer (SMP) scaffold, or a PEEK implant. Additional validation was performed on 24 murine cranial caps induced with a single, unilateral critically-sized defect (8.0 mm nominal diameter) and treated with an autograft or a SMP scaffold.•A novel fixture was developed for performing push-out mechanical tests to characterize the strength of a bone-implant interface in calvarial defect repair.•The fixture uses a 3D printed vertical clamp with mating alignment component to fix the sample in place without inducing lateral bending and verify coaxial alignment of push-out rod with the defect.•The fixture can be scaled to different calvarial defect geometries as validated with 5.0 mm bilateral and 8.0 mm single diameter murine calvarial defect model and 8.0 mm bilateral leporine calvarial defect model.

Multi-omic dissection of the drought resistance traits of soybean landrace LX.

With diverse genetic backgrounds, soybean landraces are valuable resource for breeding programs. Herein, we apply multi-omic approaches to extensively characterize the molecular basis of drought tolerance in the soybean landrace LX. Initial screens established that LX performed better with PEG6000 treatment than control cultivars. LX germinated better than William 82 under drought conditions and accumulated more anthocyanin and flavonoids. Untargeted mass spectrometry in combination with transcriptomic analyses revealed the chemical diversity and genetic basis underlying the overall performance of LX landrace. Under control and drought conditions, significant differences in the expression of a suite of secondary metabolism genes, particularly those involved in the general phenylpropanoid pathway and flavonoid but not lignin biosynthesis, were seen in LX and William 82. The expression of these genes correlated with the corresponding metabolites in LX plants. Further correlation analysis between metabolites and transcripts identified pathway structural genes and transcription factors likely are responsible for the LX agronomic traits. The activities of some key biosynthetic genes or regulators were confirmed through heterologous expression in transgenic Arabidopsis and hairy root transformation in soybean. We propose a regulatory mechanism based on flavonoid secondary metabolism and adaptive traits of this landrace which could be of relevance to cultivated soybean.

Genetic and Methylome Variation in Turkish Brachypodium Distachyon Accessions Differentiate Two Geographically Distinct Subpopulations.

Brachypodium distachyon (Brachypodium) is a non-domesticated model grass species that can be used to test if variation in genetic sequence or methylation are linked to environmental differences. To assess this, we collected seeds from 12 sites within five climatically distinct regions of Turkey. Seeds from each region were grown under standardized growth conditions in the UK to preserve methylated sequence variation. At six weeks following germination, leaves were sampled and assessed for genomic and DNA methylation variation. In a follow-up experiment, phenomic approaches were used to describe plant growth and drought responses. Genome sequencing and population structure analysis suggested three ancestral clusters across the Mediterranean, two of which were geographically separated in Turkey into coastal and central subpopulations. Phenotypic analyses showed that the coastal subpopulation tended to exhibit relatively delayed flowering and the central, increased drought tolerance as indicated by reduced yellowing. Genome-wide methylation analyses in GpC, CHG and CHH contexts also showed variation which aligned with the separation into coastal and central subpopulations. The climate niche modelling of both subpopulations showed a significant influence from the "Precipitation in the Driest Quarter" on the central subpopulation and "Temperature of the Coldest Month" on the coastal subpopulation. Our work demonstrates genetic diversity and variation in DNA methylation in Turkish accessions of Brachypodium that may be associated with climate variables and the molecular basis of which will feature in ongoing analyses.

Automatic kernel counting on maize ear using RGB images.

BACKGROUND: The number of kernels per ear is one of the major agronomic yield indicators for maize. Manual assessment of kernel traits can be time consuming and laborious. Moreover, manually acquired data can be influenced by subjective bias of the observer. Existing methods for counting of kernel number are often unstable and costly. Machine vision technology allows objective extraction of features from image sensor data, offering high-throughput and low-cost advantages. RESULTS: Here, we propose an automatic kernel recognition method which has been applied to count the kernel number based on digital colour photos of the maize ears. Images were acquired under both LED diffuse (indoors) and natural light (outdoor) conditions. Field trials were carried out at two sites in China using 8 maize varieties. This method comprises five steps: (1) a Gaussian Pyramid for image compression to improve the processing efficiency, (2) separating the maize fruit from the background by Mean Shift Filtering algorithm, (3) a Colour Deconvolution (CD) algorithm to enhance the kernel edges, (4) segmentation of kernel zones using a local adaptive threshold, (5) an improved Find-Local-Maxima to recognize the local grayscale peaks and determine the maize kernel number within the image. The results showed good agreement (> 93%) in terms of accuracy and precision between ground truth (manual counting) and the image-based counting. CONCLUSIONS: The proposed algorithm has robust and superior performance in maize ear kernel counting under various illumination conditions. In addition, the approach is highly-efficient and low-cost. The performance of this method makes it applicable and satisfactory for real-world breeding programs.

The estimation of crop emergence in potatoes by UAV RGB imagery.

BACKGROUND: Crop emergence and canopy cover are important physiological traits for potato (Solanum tuberosum L.) cultivar evaluation and nutrients management. They play important roles in variety screening, field management and yield prediction. Traditional manual assessment of these traits is not only laborious but often subjective. RESULTS: In this study, semi-automated image analysis software was developed to estimate crop emergence from high-resolution RGB ortho-images captured from an unmanned aerial vehicle (UAV). Potato plant objects were extracted from bare soil using Excess Green Index and Otsu thresholding methods. Six morphological features were calculated from the images to be variables of a Random Forest classifier for estimating the number of potato plants at emergence stage. The outputs were then used to estimate crop emergence in three field experiments that were designed to investigate the effects of cultivars, levels of potassium (K) fertiliser input, and new compound fertilisers on potato growth. The results indicated that RGB UAV image analysis can accurately estimate potato crop emergence rate in comparison to manual assessment, with correlation coefficient ( r 2 ) of 0.96 and provide an efficient tool to evaluate emergence uniformity. CONCLUSIONS: The proposed UAV image analysis method is a promising tool for use as a high throughput phenotyping method for assessing potato crop development at emergence stage. It can also facilitate future studies on optimizing fertiliser management and improving emergence consistency.

Nutrient and drought stress: implications for phenology and biomass quality in miscanthus.

BACKGROUND AND AIMS: The cultivation of dedicated biomass crops, including miscanthus, on marginal land provides a promising approach to the reduction of dependency on fossil fuels. However, little is known about the impact of environmental stresses often experienced on lower-grade agricultural land on cell-wall quality traits in miscanthus biomass crops. In this study, three different miscanthus genotypes were exposed to drought stress and nutrient stress, both separately and in combination, with the aim of evaluating their impact on plant growth and cell-wall properties. METHODS: Automated imaging facilities at the National Plant Phenomics Centre (NPPC-Aberystwyth) were used for dynamic phenotyping to identify plant responses to separate and combinatorial stresses. Harvested leaf and stem samples of the three miscanthus genotypes (Miscanthus sinensis, Miscanthus sacchariflorus and Miscanthus × giganteus) were separately subjected to saccharification assays, to measure sugar release, and cell-wall composition analyses. KEY RESULTS: Phenotyping showed that the M. sacchariflorus genotype Sac-5 and particularly the M. sinensis genotype Sin-11 coped better than the M. × giganteus genotype Gig-311 with drought stress when grown in nutrient-poor compost. Sugar release by enzymatic hydrolysis, used as a biomass quality measure, was significantly affected by the different environmental conditions in a stress-, genotype- and organ-dependent manner. A combination of abundant water and low nutrients resulted in the highest sugar release from leaves, while for stems this was generally associated with the combination of drought and nutrient-rich conditions. Cell-wall composition analyses suggest that changes in fine structure of cell-wall polysaccharides, including heteroxylans and pectins, possibly in association with lignin, contribute to the observed differences in cell-wall biomass sugar release. CONCLUSIONS: The results highlight the importance of the assessment of miscanthus biomass quality measures in addition to biomass yield determinations and the requirement for selecting suitable miscanthus genotypes for different environmental conditions.

A novel chemical sensor with multiple all-solid-state electrodes and its application in freshwater environmental monitoring.

Freshwater quality detection is important for pollution control. Three important components of water quality are pH, ammonia and dissolved H2S and there is an urgent need for a high-precision sensor for simultaneous and continuous measurement. In this study, all-solid-state electrodes of Eh, pH, NH4 + and S2- were manufactured and mounted to a wireless chemical sensor with multiple parameters. Calibration indicated that the pH electrode had a Nernst response with slope of 53.174 mV; the NH4 + electrode had a detection limit of 10-5 mol/L (Nernst response slope of 53.56 mV between 10-1 to 10-4 mol/L). Ag/Ag2S has a detection limit of 10-7 mol/L (Nernst response slope of 28.439 mV). The sensor was cylindrical and small with low power consumption and low storage demand to achieve continuous in-situ monitoring for long periods. The sensor was tested for 10 days in streams at Trawsgoed Dairy farm in Aberystwyth, UK. At the intensively farmed Trawsgoed, the concentration of NH4 + in the stream rose sharply after the application of slurry to adjacent fields. Further, the stream was overhung with extensive vegetation and exhibited changes in pH, which correlated with photosynthetic activity. Measurements of S2- were stable throughout the week. Our data demonstrate the applicability of our multiple electrode sensor.

Functional Mapping of Quantitative Trait Loci (QTLs) Associated With Plant Performance in a Wheat MAGIC Mapping Population.

In crop genetic studies, the mapping of longitudinal data describing the spatio-temporal nature of agronomic traits can elucidate the factors influencing their formation and development. Here, we combine the mapping power and precision of a MAGIC wheat population with robust computational methods to track the spatio- temporal dynamics of traits associated with wheat performance. NIAB MAGIC lines were phenotyped throughout their lifecycle under smart house conditions. Growth models were fitted to the data describing growth trajectories of plant area, height, water use and senescence and fitted parameters were mapped as quantitative traits. Trait data from single time points were also mapped to determine when and how markers became and ceased to be significant. Assessment of temporal dynamics allowed the identification of marker-trait associations and tracking of trait development against the genetic contribution of key markers. We establish a data-driven approach for understanding complex agronomic traits and accelerate research in plant breeding.

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions.

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.

Adaptive measurement method for miniature spectrometers used in cold environments.

Adaptive measurement is a major concern when using miniature spectrometers in extreme environments, especially when the ambient temperatures and incident light intensities vary greatly. In this study, parameters, including the signal output and the relevant noise and signal-to-noise ratio (SNR) of a fiber optic spectrometry system composed of a photodiode array miniature spectrometer and external driver electronics were examined at multiple integration times from -50°C to 30°C, well below the specified operating temperature of this spectrometer. The relationships between those parameters and incident light level were also examined, at a single temperature of 0°C. Based on these examinations, temperature-induced biases in the linear operating range of the spectrometer were identified. Signal output and the relevant noise and SNR in response to different integration times, temperatures, and incident light levels were assessed separately. These assessments were then used to develop an adaptive measurement method for estimating the incident light level and setting up an optimal integration time for this spectrometer, while autonomously adapting the variation in the ambient temperature and incident light level simultaneously. This approach provides a general framework for developing an adaptive measurement algorithm for miniature spectrometers, which face tremendous variations in ambient temperature and incident light level.

Linking Dynamic Phenotyping with Metabolite Analysis to Study Natural Variation in Drought Responses of Brachypodium distachyon.

Drought is an important environmental stress limiting the productivity of major crops worldwide. Understanding drought tolerance and possible mechanisms for improving drought resistance is therefore a prerequisite to develop drought-tolerant crops that produce significant yields with reduced amounts of water. Brachypodium distachyon (Brachypodium) is a key model species for cereals, forage grasses, and energy grasses. In this study, initial screening of a Brachypodium germplasm collection consisting of 138 different ecotypes exposed to progressive drought, highlighted the natural variation in morphology, biomass accumulation, and responses to drought stress. A core set of ten ecotypes, classified as being either tolerant, susceptible or intermediate, in response to drought stress, were exposed to mild or severe (respectively, 15 and 0% soil water content) drought stress and phenomic parameters linked to growth and color changes were assessed. When exposed to severe drought stress, phenotypic data and metabolite profiling combined with multivariate analysis revealed a remarkable consistency in separating the selected ecotypes into their different pre-defined drought tolerance groups. Increases in several metabolites, including for the phytohormones jasmonic acid and salicylic acid, and TCA-cycle intermediates, were positively correlated with biomass yield and with reduced yellow pixel counts; suggestive of delayed senescence, both key target traits for crop improvement to drought stress. While metabolite analysis also separated ecotypes into the distinct tolerance groupings after exposure to mild drought stress, similar analysis of the phenotypic data failed to do so, confirming the value of metabolomics to investigate early responses to drought stress. The results highlight the potential of combining the analyses of phenotypic and metabolic responses to identify key mechanisms and markers associated with drought tolerance in both the Brachypodium model plant as well as agronomically important crops.