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The recent changes in policies in several countries regarding cannabis use has increased cannabis usage and research [1,2]. Cannabis is the second most used psychoactive substance word-wide [3]. Cannabis remains the subject of many research works. The cannabis can be classified into different classes according to their external features like colour, shape, and size using some computer vision and machine learning techniques. Precise classification or recognition is the unmet need of the agriculture business. This attracts many researchers to produce solutions with machine learning and deep learning techniques. Neat and clean dataset is the primary requirements to build accurate and robust machine learning model and minimize misclassification for the real-time environment. To achieve this objective, we have created an image dataset of cannabis seed. Accordingly, we have considered seventeen cannabis seeds to create dataset. The dataset contains 17 subfolders of cannabis seeds and folder is named with the category of seed. We strongly believe the cannabis seeds dataset will be very helpful for training, testing, and validation of cannabis classification or recognition with machine learning models.

Proso millet is a valuable short-term crop of universal use cultivated all over the world. However, due to the lack of genetic improvement, the yield of this crop does not provide stable in-come for farmers. The research is aimed to test proso millet germplasm of different geographical origin under different agro-climatic regions in Kazakhstan. 90 accessions of proso millet originated from 19 countries were tested in the conditions of the North (A.I. Baraev Scientific Production Centre of Grain Farming) and the West (Agricultural Experimental Station) Kazakhstan from 2022 to 2023. The main agronomic traits such as plant height, number of seeds per panicle, seed weight per panicle and productive tillering, 1000 seed weight and yield per m2 were measured. Correlation analysis was conducted based on the obtained data. High correlation was established between the SWPP and NSPP traits (r=0.73-0.92) in Northern and Western Kazakhstan conditions in 2022-2023 years. The world collection with higher values of 1000 seed weight showed a lower number of seeds per panicle, while the correlation was negative (r= - 0.48). The findings can be used in future proso millet breeding programs to develop new and improved genotypes with desirable productive traits adaptable to different environments.

Edible plant oils provide a crucial source of lipids for human nutrition. Owing to the complex processing of some high-quality variants, including Styrian pumpkin seed oil, edible plant oils have become susceptible to food fraud by adulteration with cheaper vegetable oils, compromising both authenticity and quality. To address this issue, a workflow was developed utilizing QTOF-MS/MS to search for triacylglycerol markers indicative of adulteration and subsequently adapted them for routine analysis using triple quadrupole MS/MS. By developing a transparent classification system utilizing a multi-feature triacylglycerol panel, reliable detection of adulteration down to 3 % (w/w) is possible. Calculating ratios of selected markers and establishing intervals derived from pure oils further enables easy scalability to adjust marker ratios and ensure robustness against permanent or seasonal changes. Our work aims to make advances towards a rapid and accurate detection of oil adulteration in food industry, crucial for maintaining customer trust and safety., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Andreas N. Schwarz, Franz S. Wagner reports financial support was provided by The Austrian Research Promotion Agency (FFG). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

For the Caatinga vegetation, it has not yet been definitively established which adaptive strategies best define the functional groups of woody plants and which syndromes emerge from the relationships between functional traits to achieve success in a semi-arid tropical region. To fill some of these gaps, we analyzed a specific set of characteristics that make up the LHS scheme of the plant ecological strategy (leaf-heigh-seed). The LHS scheme captures the functional niche of plants regarding the functional traits specific leaf area (SLA), plant height (HE), and seed mass (SM). We associate wood density (WD) to this scheme because this trait is a key feature for the identification of functional strategies in seasonally dry vegetation such as the Caatinga. We measured these characteristics in eight woody species and classified them according to their leaf phenology into deciduous and evergreen. The experiment was carried out between December 2017 and November 2018 in Caatinga areas located in the municipality of Barra de Santana, PB, a semiarid region of Brazil. Using cluster analysis, principal component analysis (PCA) and Pearson correlation analyses, we found significant relations between SLA and SM, and HE and WD. The SLA was the main predictor of plant strategy in the Caatinga. According to this characteristic, we identified two functional groups: species with a low SLA and species with a high SLA. We also recognized differences between deciduous and evergreen species based on the same trait. The traits measured, which represent the axes of the plant ecological strategy scheme LHS and wood density, are efficient in the discrimination of functional groups in the Brazilian semiarid. These groups relate to leaf phenology of woody species in this vegetation.

Com o objetivo de avaliar a influência de massa de sementes e profundidades de semeadura sobre o vigor e o desenvolvimento vegetativo de mudas de tamarindeiro (Tamarindus indica L.), conduziu-se um experimento em viveiro telado, de malha 0,38 mm², no Setor de Fruticultura da Fazenda Experimental Água Limpa, município de Uberlândia (MG), no período de 26 de dezembro de 2006 a 04 de junho de 2007. O delineamento experimental foi o inteiramente casualizado, com os tratamentos distribuídos em esquema fatorial 2 x 3, com 5 repetições e 5 mudas por parcela, sendo os fatores: duas massas de sementes, leves e pesadas (65,60 g/100 sementes; 94,54 g/100 sementes), respectivamente, e três profundidades de semeadura (1; 2 e 3 cm). Avaliaram-se o número de folhas, diâmetro do caule, altura da muda, comprimento da raiz principal, massas secas da parte aérea e de raízes. Os resultados demonstraram que sementes de maior massa proporcionam melhor desenvolvimento inicial das mudas. E quanto à profundidade de semeadura, não houve diferença significativa entre todas as características avaliadas.The effect of seeds weight and different sowing depths on tamarind (Tamarindus indica L.) seedling vigor and vegetative growth was evaluated in a trial done in a screened nursery, with 0.38 mm² opening, at the experimental farm Água Limpa, in a nursery with anti-aphid screens, in the county of Uberlândia. The farm is located at 18º55'33''S and 48º17'19''W, at 872 m altitude, Minas Gerais, from December 26 2006 to June 4 2007. The experimental design was randomized blocks, in a 2 x 3 factorial, with 5 repetitions and 5 plants per plot. The factors were two seeds weight, slight and weighty (65.60 g and 94.54 g respectively), defined according to the weight of 100 seeds and three sowing depths (1cm; 2cm or 3cm). The number of leaves, stem diameter, plant height, root length, fresh and dry weight of roots and above ground matter were evaluated. The results indicated that the weighty seeds yield the best seedlings initial development. There were no significant differences in the parameters evaluated as a function of sowing depth.

The recent changes in policies in several countries regarding cannabis use has increased cannabis usage and research [1,2]. Cannabis is the second most used psychoactive substance word-wide [3]. Cannabis remains the subject of many research works. The cannabis can be classified into different classes according to their external features like colour, shape, and size using some computer vision and machine learning techniques. Precise classification or recognition is the unmet need of the agriculture business. This attracts many researchers to produce solutions with machine learning and deep learning techniques. Neat and clean dataset is the primary requirements to build accurate and robust machine learning model and minimize misclassification for the real-time environment. To achieve this objective, we have created an image dataset of cannabis seed. Accordingly, we have considered seventeen cannabis seeds to create dataset. The dataset contains 17 subfolders of cannabis seeds and folder is named with the category of seed. We strongly believe the cannabis seeds dataset will be very helpful for training, testing, and validation of cannabis classification or recognition with machine learning models., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Background: Flaxseed is an economically important oilseed crop whose geographic origin is of significant interest to producers and consumers because every region may exhibit particular quality characteristics. The lipid/fatty acid method of determining the geographic origin of flaxseed has not been found to be adequate., Results: To improve the discrimination rate and the geographical traceability of this crop, the chemical profiles of the flaxseed samples were characterized via lipids/fatty acids, stable isotopes, and antioxidant capacity. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were also performed. A satisfactory discrimination rate of 98.6% was obtained after combining fatty acids, stable isotopes, and antioxidant capacity to trace the origin of flaxseed from five regions in northern China., Conclusion: This study provides an effective method for distinguishing the geographic origin of flaxseed. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)

The nutritional integrity of wheat is jeopardized by rapidly rising atmospheric carbon dioxide (CO 2 ) and the associated emergence and enhanced virulence of plant pathogens. To evaluate how disease resistance traits may impact wheat climate resilience, 15 wheat cultivars with varying levels of resistance to Fusarium Head Blight (FHB) were grown at ambient and elevated CO 2 . Although all wheat cultivars had increased yield when grown at elevated CO 2 , the nutritional contents of FHB moderately resistant (MR) cultivars were impacted more than susceptible cultivars . At elevated CO 2 , the MR cultivars had more significant differences in plant growth, grain protein, starch, fructan, and macro and micro-nutrient content compared with susceptible wheat. Furthermore, changes in protein, starch, phosphorus, and magnesium content were correlated with the cultivar FHB resistance rating, with more FHB resistant cultivars having greater changes in nutrient content. This is the first report of a correlation between the degree of plant pathogen resistance and grain nutritional content loss in response to elevated CO 2 . Our results demonstrate the importance of identifying wheat cultivars that can maintain nutritional integrity and FHB resistance in future atmospheric CO 2 conditions., (© 2022. The Author(s).)

Soil seed banks represent a critical but hidden stock for potential future plant diversity on Earth. Here we compiled and analyzed a global dataset consisting of 15,698 records of species diversity and density for soil seed banks in natural plant communities worldwide to quantify their environmental determinants and global patterns. Random forest models showed that absolute latitude was an important predictor for diversity of soil seed banks. Further, climate and soil were the major determinants of seed bank diversity, while net primary productivity and soil characteristics were the main predictors of seed bank density. Moreover, global mapping revealed clear spatial patterns for soil seed banks worldwide; for instance, low densities may render currently species-rich low latitude biomes (such as tropical rain-forests) less resilient to major disturbances. Our assessment provides quantitative evidence of how environmental conditions shape the distribution of soil seed banks, which enables a more accurate prediction of the resilience and vulnerabilities of plant communities and biomes under global changes., (© 2021. The Author(s).)

The geometric and color features of agricultural material along with related physical properties are critical to characterize and express its physical quality. The experiments were conducted to classify the physical characteristics like size, shape, color and texture and then workout the relationship between manual observations and using image processing techniques for weight and volume of the four wheat refractions i.e. sound, damaged, shriveled and broken grains of wheat variety PBW 725. A flatbed scanner was used to acquire the images and digital image processing method was used to process the images and output of image analysis was compared with the actual measurements data using digital vernier caliper. A linear relationship was observed between the axial dimensions of refractions between manual measurement and image processing method with R 2 in the range of 0.798-0.947. The individual kernel weight and thousand grain weight of the refractions were observed to be in the range of 0.021-0.045 and 12.56-46.32 g respectively. Another linear relationship was found between individual kernel weight and projected area estimated using image processing methodology with R 2 in the range of 0.841-0.920. The sphericity of the refractions varied in the range of 0.52-0.71. Analyses of the captured images suggest ellipsoid shape with convex geometry while the same observation was recorded by physical measurements also. A linear relationship was observed between the volume of refractions derived from measured dimensions and calculated from image with R 2 in the range of 0.845-0.945. Various color and grey level co-variance matrix texture features were extracted from acquired images using the open-source Python programming language and OpenCV library which can exploit different machine and deep learning algorithms to properly classify these refractions., (© 2021. The Author(s).)

Background: The resistance of proteins to gastrointestinal digestion contributes to their ability to act as allergens. Near-complete digestion of protein in wheat products is important with respect to avoiding the potential immunogenic effects of undigested peptides. Five modern US wheat classes (soft red winter, hard winter, hard red spring, club and durum) including 17 wheat varieties, as well as three ancient wheat classes (spelt, emmer and einkorn) including nine wheat varieties, were analyzed for kernel hardness (KH) and flour protein characteristics, in addition to in vitro protein digestibility (IVPD) of cooked flour, flour without albumins and globulins (FWOAG), gluten, albumins, and globulins, aiming to identify the factors influencing the protein digestibility of flour., Results: IVPDs of flour, FWOAG, gluten and albumins of wheat varieties ranged from 86.5% to 92.3%, 85.8% to 90.3%, 90.6% to 94.6% and 74.8% to 85.1%, respectively. The IVPD of gluten was significantly higher than the IVPDs of flour and FWOAG, indicating that non-protein components substantially affect protein digestibility. Significant differences were observed in IVPDs of flour and albumins among eight wheat classes, but not in the IVPDs of FWOAG, gluten and globulins. There were apparent differences in undigested protein bands and intensities of wheat classes with low and high flour IVPDs. KH and albumin proportion exhibited negative and positive relationships, respectively, with flour IVPD., Conclusion: The results of the present study demonstrate that KH, non-protein components and albumin proportion have a major influence on protein digestion and need to be considered when developing wheat cultivars with higher protein digestibility., (Published 2021. This article is a U.S. Government work and is in the public domain in the USA.)

Background: Maize is one of the most important food crops in the world. Many different varieties of maize seeds are similar in size and appearance, so distinguishing the varieties of maize seed is a significant research topic. This study used hyperspectral image processing coupled with convolutional neural network (CNN) and a subregional voting method to recognize different varieties of maize seed., Results: First, visible and near-infrared (NIR-visible) hyperspectral images were obtained. Savitzky-Golay (SG) smoothing and first derivative (FD) were used to pretreat the raw spectra and highlight the spectral differences of samples of different varieties. Second, the region of interest (ROI) of each sample was divided into several subregions according to the shape and the number of pixels. Then, a method was proposed for reshaping the images of pixel spectra for the CNN and the training model was established. Finally, using subregional voting, one prediction result was generated from the prediction results of several original subregions in one sample. The results showed that, for six varieties of normal maize seeds, the tests identified embryoid and non-embryoid forms with 93.33% and 95.56% accuracy, respectively. For six varieties of sweet maize seeds, the test accuracy in embryoid and non-embryoid forms was 97.78% and 98.15%, respectively., Conclusion: The maize seed was identified accurately. The present study demonstrated that the CNN model for spectral image coupled with subregional voting represents a new approach for the identification of varieties of maize seed. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)

Geographical indications may stimulate collective actions of governance for quality control, trade and marketing as well as innovation based on the use of local resources and regional biodiversity. Cocoa production, however, dominated by small family agriculture in tropical regions, has rarely made use of such strategies. This review is aimed at understanding major research interests and emerging technologies helpful for the origin differentiation of cocoa quality. Results from literature search and cited references of publications on cocoa research were imported into VOSviewer for data analysis, which aided in visualizing major research hotpots. Co-occurrence analysis yielded major research clusters which guided the discussion of this review. Observed was a consensus recognizing cocoa quality resulting from the interaction of genotype, fermentation variables and geographical origin. A classic view of cocoa genetics based on the dichotomy of 'fine versus bulk' has been reexamined by a broader perspective of human selection and cocoa genotype evolution. This new approach to cocoa genetic diversity, together with the understanding of complex microbiome interactions through fermentation, as well as quality reproducibility challenged by geographical conditions, have demonstrated the importance of terroir in the production of special attributes. Cocoa growing communities around the tropics have been clearly enabled by new omics and chemometrics to systematize producing conditions and practices in the designation of specifications for the differentiation of origin quality. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)

Background: Rice eating quality largely dictates consumer preference, and the demand for new rice varieties with excellent eating quality from farmers is increasing. Identification of factors contributing to eating quality is helpful for developing high-quality rice varieties., Results: Two groups of rice with different apparent amylose content (AACs) were used in this study. One group contained four varieties with low AACs (8.8-9.4%), whereas the other contained four traditional varieties with medium AACs (17.2-17.5%). The physicochemical properties, starch fine structure and crystallinity and storage protein composition of the two groups were analyzed. We found that, in both groups, the rice varieties with high eating quality had more short-chain amylopectin, lower glutelin and prolamin content, and a higher albumin content. In addition, the low-AAC varieties produced opaque endosperms, which may result from an increased number of pores in the center of starch granules., Conclusions: Both the fine structure of starch and the storage protein composition were closely related to rice eating quality. In both groups, short branch-chain amylopectin, short-chain amylopectin [degree of polymerization (DP) 6-12], and albumin had positive effects on eating quality. By contrast, long branch-chain amylopectin, long-chain amylopectin (DP 35-60), glutelin and prolamin had adverse effects on eating quality of rice. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)

Aims: The principal chaparral species in California, Adenostoma fasciculatum, an evergreen, sclerophyllous shrub, is broadly distributed and provides habitat and food resources for a large and diverse animal community. The effects of climate change, including elevated temperatures, fire frequency and severity, along with increased urban encroachment, have placed pressure on chaparral habitats in California. Our goal is to investigate aspects of reproductive ecology as a measure of the potential resiliency of A. fasciculatum. We focus on seed rain (all seed falling into the seed traps regardless of origin) and seed banks in the context of plant-animal interactions and regeneration., Methods: Stand recovery following disturbance is achieved through both resprouting and germination from established persistent soil seed banks. In this study we focus on seed ecology using a series of experiments to document the length and quantity of seed rain, seed predation, parsing the importance of the community of granivores, and evaluating the connection between stand age and germination rate from soil seed banks., Important Findings: Our research documented an 8-month seed rain duration with over 1 million seeds per m2, multiple seed predators including passerines (songbirds) and rodents, and points to the possibility of native ants playing a role in the seed dispersal process. This is important given the recent advancement of the invasive Argentine ant (Linepthema humile) into Californian chaparral. This research demonstrates a clear relationship between A. fasciculatum and both resident and migratory granivores in the chaparral. We documented that a 39-year-old stand had higher germination rates than those which were 16, 20, 41 and 71 years old and how seed banks play a major role in assuring resiliency following fire. These findings are important for wildland managers to assure the continued resiliency of A. fasciculatum., Competing Interests: Joanna M. Garaventa, the primary researcher in this matter, has a commercial affiliation with Garaventa Consulting and Research. Garaventa Consulting and Research did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of the authors’ salary and/or research materials. V. Thomas Parker has no affiliation with this organization. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Understanding the relationship between physiological traits with yield and yield components is an essential step towards developing high-yielding and high-quality canola (Brassica napus L.) cultivars. This study aimed to explore further the relationship between some physiological features, including radiation use efficiency (RUE), and seed yield in canola., Results: Significant differences were found among cultivars regarding maximum leaf area index (LAI max ) and required days to achieve maximum LAI (DLAI max ). All cultivars obtained the minimum LAI required to intercept 90% of the incident radiation, but at different times. Some cultivars like SW102 and Shirali had the same fraction of intercepted photosynthetically active radiation (IPAR) when LAI was maximal, but SW102 had higher IPAR. This indicated that SW102 was more efficient in irradiation capacity and may have a higher photosynthesis rate when exposed to the high irradiation conditions. The average canola RUE in the current study was 3.80 and 3.63 g MJ -1 m -2 in 2014 and 2015, respectively. In general, the crop growth rate was higher in the first year than in the second year due to the fewer cloudy days and more incident radiation., Conclusion: Results indicated that duration of growth, crop growth rate, and harvest index were crucial for enhancing biomass and seed yield. Also, a relatively high correlation was found between the RUE and DLAI max . The cultivars that reached their maximum LAI later demonstrated higher RUE, and consequently had higher biological and seed yield. The results obtained could be used to develop an improved canola crop growth model and breeding programs. © 2021 Society of Chemical Industry., (© 2021 Society of Chemical Industry.)

Spectroscopy and machine learning (ML) algorithms have provided significant advances to the modern food industry. Instruments focusing on near-infrared spectroscopy allow obtaining information about seed and grain chemical composition, which can be related to changes caused by field pesticides. We investigated the potential of FT-NIR spectroscopy combined with Linear Discriminant Analysis (LDA) to discriminate chickpea seeds produced using different desiccant herbicides at harvest anticipation. Five herbicides applied at three moments of the plant reproductive stage were utilized. The NIR spectra obtained from individual seeds were used to build ML models based on LDA algorithm. The models developed to identify the herbicide and the plant phenological stage at which it was applied reached 94% in the independent validation set. Thus, the LDA models developed using near-infrared spectral data provided to be efficient, quick, non-destructive, and accurate to identify differences between seeds due to pre-harvest herbicides application., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

High-throughput phenotyping systems are powerful, dramatically changing our ability to document, measure, and detect biological phenomena. Here, we describe a cost-effective combination of a custom-built imaging platform and deep-learning-based computer vision pipeline. A minimal version of the maize (Zea mays) ear scanner was built with low-cost and readily available parts. The scanner rotates a maize ear while a digital camera captures a video of the surface of the ear, which is then digitally flattened into a two-dimensional projection. Segregating GFP and anthocyanin kernel phenotypes are clearly distinguishable in ear projections and can be manually annotated and analyzed using image analysis software. Increased throughput was attained by designing and implementing an automated kernel counting system using transfer learning and a deep learning object detection model. The computer vision model was able to rapidly assess over 390 000 kernels, identifying male-specific transmission defects across a wide range of GFP-marked mutant alleles. This includes a previously undescribed defect putatively associated with mutation of Zm00001d002824, a gene predicted to encode a vacuolar processing enzyme. Thus, by using this system, the quantification of transmission data and other ear and kernel phenotypes can be accelerated and scaled to generate large datasets for robust analyses., (© 2021 Society for Experimental Biology and John Wiley & Sons Ltd.)

Background: Edamame is a vegetable soybean (Glycine max) rich in protein with well-balanced amino acid profiles, including all the essential amino acids. It is also relatively high in oil consisting of five fatty acids. In this study, fatty and amino acid contents in oven-dried edamame and mature seeds in 54 genotypes were analyzed to help edamame breeding and relevant research., Results: Significant differences (P < 0.01) between dried edamame and mature soybeans were found for all traits, suggesting that the contents of seed fatty and amino acids varied with drying method and/or growth stage. The genotypic effects were significant for amino acids in all cases and mostly for fatty acids. Fatty acid content was more variable than amino acids in both edamame and mature soybeans. The broad-sense heritability estimates of traits in mature soybeans (51.89-90.37%) were larger than those in edamame seeds (13.10-81.83%), and the estimates for amino acids were larger than those for fatty acids. Correlations between the two edamame drying methods or between the edamame and mature soybeans were significant for all fatty and amino acids with few exceptions, and the correlation coefficients for amino acids (0.36-0.89) were larger than those for fatty acids (0.29-0.81)., Conclusions: Selection for both fatty and amino acids in edamame seems less effective than that in mature soybeans, and the improvement of amino acids would be more achievable than fatty acid improvement. Indirect selection through mature soybeans may benefit the edamame improvement for most of the amino acids. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)

Background: Low adoption of maize varieties bred to address the nutritional needs of the growing African population limits their impact. Aroma is essential in consumer preference, but has hitherto hardly been studied. We analysed the volatile organic compounds of flours and porridges of 22 maize varieties belonging to four nutritionally distinct groups, namely provitamin A maize, quality protein maize, yellow and white maize., Results: Proton-transfer-reaction quadrupole ion time-of-flight mass spectrometry (PTR-QiTOF-MS) analysis generated 524 mass peaks ranging from 16.007 to 448.089 m/z. Principal component analysis separated the varieties belonging to the four groups. With headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME GC-MS), 48 volatile compounds were identified in maize flour and 21 in maize porridge, including hexane, nonane, pentanoic acid, 1-octen-3-ol, 1-hexanol, hexanal, nonanal, 2-pentylfuran and 2-heptanone. Volatile compounds such as 1,2,4-trimethyl benzene, associated with thermal degradation of carotenoids, increased in the porridge of yellow and provitamin A maize., Conclusion: The results indicate that PTR-QiTOF-MS and HS-SPME GC-MS combined with multivariate analysis are instrumental to study the volatile aroma compounds of different maize varieties., (© 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

The introduction of alien species represents one of the greatest threats to biodiversity worldwide. Highway construction increases the dispersal and invasion of exotic plant species. This study examined the assembly process of the plant communities to determine whether the roadsides of the Patagonian steppe represent a reservoir and dispersal source of invasive exotic species. We analyzed the composition of exotic and native species and functional groups present in the established vegetation and seed banks of roadsides and reference areas nearby. The type of dispersal of exotic and native species at the roadsides was also evaluated. Total cover and that of exotic and native species was lower at the roadsides than in the reference areas; however, at the roadsides the cover and seed abundance of exotic species was higher than that of native species. In the roadsides vegetation, native shrubs such as Acaena splendens predominated, along with exotic perennial herbs and grasses which were mainly represented by Rumex acetosella. In the seed bank the predominant species were exotic perennial herbs, also represented by R. acetosella, annual exotic species such as Epilobium brachycarpum and Verbascum thapsus, and annual native species such as Heliotropium paronychioides. No exotic shrubs were found either at the roadsides or in the reference areas. The species at the roadsides did not present a dominant type of dispersal. The abundance of exotic species at the roadsides, both in the aboveground vegetation and the seed bank, may be due to the stressful environment and the characteristics of the species themselves, such as the ability to form seed banks. This work revealed that the roadsides of the Patagonian steppe constitute reservoirs of invasive exotic species, highlighting the importance of identifying them and controlling their spread, with a view to generating ecosystem management programs., Competing Interests: The authors have declared that no competing interests exist.

Seed macro- and micro-morphology were analyzed to evaluate their capacity to discriminate species in the genus Vicia (Fabaceae). To assess the interspecific variation of the taxa in the genus Vicia, 41 accessions were obtained from the USDA-ARS germplasm collection in the USA and 19 accessions were collected from Korea. Seed morphological characteristics such as shape, color, mottling, finish, length, width, diameter, hilum shape, hilum color, hilum length, and lens distance from the hilum were examined under a stereomicroscope. Testa texture characteristics such as testa pattern, papillae type, density, height, ribbing, surface deposits, and peaks topped with wax were examined under scanning electron microscopy. Various gross-morphological traits of seeds of Vicia species have been analyzed and compared. The present study revealed significant variation in testa traits. Testa were papillose and papillose with mounds, the latter being observed only in Vicia lathyroides. The present study revealed 20 key traits that could be used to diagnose Vicia species and classify them., (© 2020 Wiley Periodicals LLC.)

In response to the need from the food industry for new analytical solutions, a fit-for-purpose quantitative 1 H NMR methodology was developed to authenticate pure coffee (100% arabica or robusta) as well as predict the percentage of robusta in blends through the study of 292 roasted coffee samples in triplicate. Methanol was chosen as the extraction solvent, which led to the quantitation of 12 coffee constituents: caffeine, trigonelline, 3- and 5-caffeoylquinic acid, lipids, cafestol, nicotinic acid, N -methylpyridinium, formic acid, acetic acid, kahweol, and 16- O -methylcafestol. To overcome the chemical complexity of the methanolic extract, quantitative analysis was performed using a combination of traditional integration and spectral deconvolution methods. As a result, the proposed methodology provides a systematic methodology and a linear regression model to support the classification of known and unknown roasted coffees and their blends.

Molecular markers are considered powerful tools to identify the potential genetic variation. Forty-two RAPD, ISSR and SSR markers were employed to characterize 21 mungbean genotypes. RAPD primers produced 79 polymorphic bands while ISSR and SSR markers amplified 21 and 6 polymorphic bands, respectively. The range for minimum and maximum number of bands was 3-13, 3-9 and 1-2 and average alleles per loci were 8.17, 4.3 and 1 for RAPD, ISSR and SSR, respectively. Highest polymorphism percentage was 100% for both ISSR and SSR while 80% for RAPD markers. The SSR-VR-303 and ISSR-UBC-810 had highest PIC values (0.44, 0.72) indicating the more discriminating power of these primers for diversity analysis. RAPD primer OPA-7 with maximum PIC value (0.26) resulted in good amplification. Jaccard's similarity coefficient ranged between 0.50 to 1, 0.64 to 1 and 0.75 to 1 for SSR, ISSR and RAPD primers, respectively, indicating less genetic divergence among studied material. Dendrogram based on Unweighted Pair Group Method of Arithmetic Means (UPGMA) grouped mungbean genotypes into two to three major clusters for different marker system with up to 100% genetic relatedness among different cultivars. Molecular genetic divergence identified can be utilized to widen the genetic base in mungbean breeding programs.

Rapid and accurate discrimination of alfalfa cultivars is crucial for producers, consumers, and market regulators. However, the conventional routine of alfalfa cultivars discrimination is time-consuming and labor-intensive. In this study, the potential of a new method was evaluated that used multispectral imaging combined with object-wise multivariate image analysis to distinguish alfalfa cultivars with a single seed. Three multivariate analysis methods including principal component analysis (PCA), linear discrimination analysis (LDA), and support vector machines (SVM) were applied to distinguish seeds of 12 alfalfa cultivars based on their morphological and spectral traits. The results showed that the combination of morphological features and spectral data could provide an exceedingly concise process to classify alfalfa seeds of different cultivars with multivariate analysis, while it failed to make the classification with only seed morphological features. Seed classification accuracy of the testing sets was 91.53% for LDA, and 93.47% for SVM. Thus, multispectral imaging combined with multivariate analysis could provide a simple, robust and nondestructive method to distinguish alfalfa seed cultivars.

Background: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are hampered by the scarcity of morphological data sets. Thus, horse gram cultivars considered for this study is classified based on prevailing growth factors showing homogenous genotype in various agro ecological zones. Nowadays, several machine learning (ML) methods are used in the field of plant phenotyping., Results: We adopted unsupervised learning techniques from the K-means clustering algorithm to analyze important morphological traits: plant shoot length, total plant height, flowering percentage, number of pods per plant, pod length, number of seeds per plant, and seed length variants between germplasm. Unsupervised clustering revealed that 20 germplasm accessions were grouped in four clusters in which high-yielding traits were predominantly observed in cluster 2., Conclusion: These findings could guide ML-based classification to characterize suitable germplasms on the basis of high-yielding varieties for different agro-ecological zones. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)

Five fatty acids comprise the bulk of the lipid content in pecans: palmitic acid, stearic acid, oleic acid, linoleic acid, and linolenic acid. Understanding the profiles of these fatty acids and how they relate to sensory characteristics may offer an explanation for flavor and flavor defects that may exist in certain cultivars of pecans. The objective of this study was to examine and compare fatty acid profiles of three cultivars of pecans (Major, Lakota, and Chetopa), over two crop years, under raw and roasted preparation methods, and understand the fatty acids association with sensory attributes. Percentages of palmitic, stearic, oleic, linoleic, and linolenic acids to total fatty acid content were determined using gas chromatography, and sensory profiles were generated using descriptive sensory analysis. Similar trends were seen across samples, with oleic acid comprising the majority of the total fatty acids and linolenic acid comprising the smallest percentage. There were significant differences in fatty acid content among cultivars and between pecans in the first and second crop year. Few associations were found between the fatty acids and sensory attributes, which suggest that combinations of the fatty acids contribute to certain pleasant or undesirable flavor attributes in the pecans. Subtle differences in fatty acid composition may lead to variation in flavor and flavor intensity or draw attention to or from certain attributes during consumption. Differences in crop year indicated that fatty acid content and therefore flavor are variable year to year. PRACTICAL APPLICATION: This study will help understand how fatty acid content of pecans varies from year to year. This should be taken into account when manufacturing products with pecans as the nutritional content of the product may change as the result., (© 2020 Institute of Food Technologists®.)

Background: Interest in alternatives to the traditional wheat Triticum aestivum among farmers, millers, bakers, and consumers is increasing. The Altergrain project aimed to compare the Belgian-soil cultivated Einkorn (1K), Emmer (EMM), Khorasan (KH), and modern wheat (MW) with respect to nutritional values of kernels, breads made from these cereals, and population-level nutrient intake implications., Results: Ancient wheats 1K, EMM, and KH contain lower total carbohydrate content than MW. Further, ancient wheats are higher in both protein and crude ash content. Vitamin E levels in breads prepared using 1K and EMM were higher than those in MW, but those prepared from KH had lower vitamin E levels than MW. Breads prepared using ancient wheats have higher total phenol content (TPC) than those from MW. Baking caused a decrease in vitamin E and TPC in bread prepared from ancient wheat, the exception being the one prepared using KH, which had a higher TPC than MW. When replacing bread made from MW with those made from ancient grains, no differences were observed with respect to conformance with the Belgian Recommend Daily Requirements., Conclusion: Ancient wheats from Belgian soil are as nutritive as MWs even after being processed into bread. At the kernel level, nutritional differences are present, but only small differences are present in terms of nutritional intake when nutrition parameters are calculated for consumed bread. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)

Heavy-metal-associated (HMA) isoprenylated plant proteins (HIPPs) only exist in vascular plants. They play important roles in responses to biotic/abiotic stresses, heavy-metal homeostasis, and detoxification. However, research on the distribution, diversification, and function of HIPPs in Triticeae species is limited. In this study, a total of 278 HIPPs were identified from a database from five Triticeae species, and 13 were cloned from Haynaldia villosa . These genes were classified into five groups by phylogenetic analysis. Most HIPPs had one HMA domain, while 51 from Clade I had two, and all HIPPs had good collinear relationships between species or subgenomes. In silico expression profiling revealed that 44 of the 114 wheat HIPPs were dominantly expressed in roots, 43 were upregulated under biotic stresses, and 29 were upregulated upon drought or heat treatment. Subcellular localization analysis of the cloned HIPPs from H. villosa showed that they were expressed on the plasma membrane. HIPP1-V was upregulated in H. villosa after Cd treatment, and transgenic wheat plants overexpressing HIPP1-V showed enhanced Cd tolerance, as shown by the recovery of seed-germination and root-growth inhibition by supplementary Cd. This research provides a genome-wide overview of the Triticeae HIPP genes and proved that HIPP1-V positively regulates Cd tolerance in common wheat.

Background: Multi-elements have been widely used to identify the geographical origins of various agricultural products. The objective of this study was to investigate the feasibility of identifying the geographical origins of peanut kernels at different regional scales by using the multi-element fingerprinting technique. The concentrations of 20 elements [boron (B), magnesium (Mg), phosphorus (P), potassium (K), calcium (Ca), etc.] were determined in 135 peanut samples from Jilin Province, Jiangsu Province, and Shandong Province of China. Data obtained were processed by one-way analysis of variance (ANOVA), principal components analysis (PCA), k nearest neighbors (k-NN), linear discriminant analysis (LDA), and support vector machine (SVM)., Results: Peanut kernels from different regions had their own element fingerprints. The k-NN, LDA, and SVM were all suitable to predict peanut kernels according to their grown provinces with the total correct classification rates of 91.2%, 91.1%, and 91.1%, respectively. While SVM was the best to identify different grown cities of peanut kernels with the prediction accuracy of 91.3%, compared to 72.2% and 78.3% for k-NN and LDA, respectively., Conclusion: It was an effective method to identify producing areas of peanut kernels at different regional scales using multi-element fingerprinting combined with SVM to enhance regional capabilities for quality assurance and control. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)

Accurate identification of crop varieties grown by farmers is crucial, among others, for crop management, food security and varietal development and dissemination purposes. One may expect varietal identification to be more challenging in the context of developing countries where literacy and education are limited and informal seed systems and seed recycling are common. This paper evaluates the extent to which smallholder farmers misidentify their wheat varieties in Ethiopia and explores the associated factors and their implications. The study uses data from a nationally representative wheat growing sample household survey and DNA fingerprinting of seed samples from 3,884 wheat plots in major wheat growing zones of Ethiopia. 28-34% of the farmers correctly identified their wheat varieties. Correct identification was positively associated with farmer education and seed purchases from trusted sources (cooperatives or known farmers) and negatively associated with seed recycling. Farmers' varietal identification thereby is problematic and leads to erroneous results in adoption and impact assessments. DNA fingerprinting can enhance varietal identification but remains mute in the identification of contextual and explanatory factors. Thus, combining household survey and DNA fingerprinting approaches is needed for reliable varietal adoption and impact assessments, and generate useful knowledge to inform policy recommendations related to varietal replacement and seed systems development., Competing Interests: Diversity Arrays Technology is a commercial entity and Andrzej Kilian is the CEO of this company. The funder provided support in the form of salaries for authors [MJ, KT, OE], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. DArT does not alter our adherence to PLOS ONE policies on sharing data and materials.

Humans cultivate thousands of economic plants (i.e. plants with economic value) outside their native ranges. To analyze how this contributes to naturalization success, we combine global databases on economic uses and naturalization success of the world's seed plants. Here we show that naturalization likelihood is 18 times higher for economic than non-economic plants. Naturalization success is highest for plants grown as animal food or for environmental uses (e.g. ornamentals), and increases with number of uses. Taxa from the Northern Hemisphere are disproportionately over-represented among economic plants, and economic plants from Asia have the greatest naturalization success. In regional naturalized floras, the percentage of economic plants exceeds the global percentage and increases towards the equator. Phylogenetic patterns in the naturalized flora partly result from phylogenetic patterns in the plants we cultivate. Our study illustrates that accounting for the intentional introduction of economic plants is key to unravelling drivers of plant naturalization.

The establishment of transgenic plants has greatly promoted the progress of plant research. However, traditional selection methods using antibiotics or herbicides may miss any positive transformants with growth defects. Additionally, screening with antibiotics/herbicides requires a huge amount of seeds, sterile work conditions and a large amount of space to germinate plants, making the selection process time- and labor-consuming. In this study, we constructed a novel stable transformation vector, plasmid of OLE1-GFP T-DNA vector (pOGT), which can shorten the steps of cloning foreign genes into expression vectors by using TA cloning. Additionally, selection of transformed seeds with fluorescence overcomes the difficulties of conventional selection with antibiotics/herbicides and simplifies the screening process for transgenic plants.

Aims: Pseudomonas spp. have been widely studied for their plant growth-promoting effects. However, their capacity to promote lipid accumulation in oilseed crops is not well characterized. In this study, we evaluated the effect of Pseudomonas fluorescens LBUM677 on lipid accumulation in three oilseed crops: soybean (Glycine max), canola (Brassica napus) and corn gromwell (Buglossoides arvensis), a plant of high nutraceutical interest for its accumulation of the omega-3 stearidonic acid., Methods and Results: Pot experiments were conducted under controlled conditions where seeds were inoculated or not with LBUM677 and plants were harvested at 4, 8 and 12 weeks. A qPCR assay specifically targeting LBUM677 was used in parallel to correlate LBUM677 soil rhizosphere competency to growth promotion and seed lipid accumulation. Total oil seed content and fatty acid composition were analysed at seed maturity. Results showed that LBUM677 was able to establish itself in the rhizosphere of the three plant species at similar levels, but it differentially increased plant biomass, total oil content and lipid composition in a plant-specific manner., Conclusions: Despite some species-specific differences observed in P. fluorescens LBUM677's effect on different crops, the strain appears to be a generalist plant growth-promoting rhizobacteria of oilseed crops., Significance and Impact of the Study: LBUM677 shows great potential to be used as an inoculum to promote oil yield and fatty acid accumulation in oilseed crops., (© 2019 The Society for Applied Microbiology.)

Common bean variety choice by farmers in Uganda is driven by seed yield plus end-use quality traits like market class and cooking time. Limited genotype by environment information is available for traits valued by consumers. This research evaluated yield, seed size, hydration properties, and cooking time of 15 common bean genotypes within market classes recognized by consumers along with three farmers' checks at nine on-farm locations in Uganda for two seasons. Yield ranged from 71 to 3,216 kg ha -1 and was largely controlled by location (21.5% of Total Sums of Squares [TSS]), plus the interaction between location and season (48.6% of TSS). Cooking time varied from 19 to 271 minutes with the genotypes Cebo Cela and Ervilha consistently cooking fastest in 24 and 27 minutes respectively. Comparatively, the local checks (NABE-4, NABE-15, and Masindi yellow) took 35 to 45 minutes to cook. Cooking time was largely controlled by genotype (40.6% of TSS). A GGE biplot analysis uncovered the presence of two mega-environments for yield and one mega-environment for cooking time. Identification of mega-environments for these traits will help expedite common bean breeding, evaluation, and variety selection through reduction of number of test environments needed for phenotype evaluations. The high yielding and fast cooking genotypes from this study can be targeted as parental materials to improve existing common bean germplasm for these important traits.

Background: There is renewed interest in quinoa as a potential source of vegetable oils; however, there is no information about how environmental conditions affect its fatty acid composition, a critical indicator of its oil quality. The fatty acid concentrations of four cultivars adapted to temperate environments were compared at three sowing dates to evaluate the effect of environmental conditions during the seed-filling period on the variation in oil quality., Results: The interaction between cultivar and sowing date was the main source of variation explaining the changes in the lipid content and fatty acid concentrations in quinoa. Most of the variation in the concentration of unsaturated fatty acids was attributed to the temperature and solar radiation during the seed-filling period; cultivar-specific responses to photo-thermal conditions were observed among the sea-level quinoa cultivars evaluated., Conclusion: The lipid content and concentration of fatty acids in quinoa are affected by sowing date. This effect is exerted through changes in temperature and solar radiation conditions. This managing practice can therefore be used to achieve quinoa oil with different qualities. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

Background: In this study, artificial intelligence models that identify sunn pest-damaged wheat grains (SDG) and healthy wheat grains (HWG) are presented. Svevo durum wheat cultivated in Konya province, Turkey is used for the process, with 150 HWG and 150 SDG being used for classification. Thanks to the constructed imaging setup, photos of the 300 wheat grains are obtained. Seventeen visual features of each wheat grain are extracted by image-processing techniques and evaluated in three different groups of dimension, texture and pattern as visual parameters. Artificial bee colony (ABC) optimization-based artificial neural network (ANN) and extreme learning machine (ELM) algorithms are implemented to classify the damaged wheat grains., Results: A correlation-based feature selection (CFS) technique is also utilized to find the most effective among the 17 features. In the classification process using five selected features, the mean absolute error (MAE) and root mean square error (RMSE) values for ABC-based ANN are calculated as 0.00174 and 0.00433 respectively. The proposed technique is integrated into graphical user interface (GUI) software to construct an effective detection system for practical use., Conclusion: The results indicate that, thanks to the modified ANN algorithm and implemented CFS algorithm, the detection accuracy of damaged wheat grains is considerably increased. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

The present study aims to evaluate the effect of the growth conditions and the cultivar on the total and water-extractable (W-E) arabinoxylan (AX) in barley. For this purpose, nine barley varieties from two different years were analyzed. The total AX content ranged from 5.97 to 8.98 wt % d.m., while the W-E AX ranged from 0.06 to 0.35 wt % d.m. The W-E AX molecular properties were characterized by high-pressure size exclusion chromatography (HPSEC)-triple detector array (TDA). The molecular weight was between 2.3 × 10 5 and 12.6 × 10 5 Da, the polydispersity was between moderate and broad (1.1 < M w / M n < 4.3), and the conformation was a stiff semiflexible coil (0.5 < α < 1.3). The results indicate that the year influences the content of total AX and W-E AX and some molecular characteristics of W-E AX, such as its polydispersity and its conformation. Finally, the results demonstrated that the W-E AX can be used as an index of the malting attitude of barley because it positively correlates with germinative energy and kernel dimension.

We compared the characteristics of seeds within faeces between semi-terrestrial Japanese macaques (Macaca fuscata) and sympatric arboreal Japanese martens (Martes melampus) in Shiga Heights, central Japan. We collected faecal samples of the two mammalian species for 1 year (n = 229 for macaques and n = 22 for martens). We then compared the proportion of seed occurrence, life-form composition, number of seeds and species richness within single faecal samples, and the seed intact ratio between the two mammalian species. We detected seeds from 20 and 7 species from macaque and marten faeces, respectively. Macaque faeces contained seeds of multiple strata, while marten faeces contained no herbaceous plant seeds. Seed sizes within faeces showed no interspecific difference. For macaques, seeds were found within faecal samples collected in late spring to late fall, while for martens, seeds were found between summer and winter. The proportion of seed occurrence was greater in summer (both species) and fall (macaques), which implied that the seed dispersal roles of macaques and martens was greater in these seasons. The mean seed number (across species), intact ratio of seeds (high for both species) and seed species richness within single faecal samples of macaques and martens showed no significant differences, but for several species, martens defecated more seeds than macaques and showed higher intact ratio. Our study indicates that sympatric mammals in the temperate regions of Japan contribute differently to seed dispersal in forest ecosystems., (© 2020 The Author(s) Published by S. Karger AG, Basel.)

The effect of exogenous amylase on the in vitro rumen digestion kinetics of whole-crop maize silage made from dent (RB9004) or flint grain type (RB9308) was evaluated at different phenological stages: soft dough (SOD), early dent (EAD), ½ milkline (½M) and ¾ milkline (¾M). Forage was harvested from 70 to 110 days after sowing. Two rumen-cannulated cows receiving or not exogenous amylase (0.7 g/kg dry matter-DM, provided to achieve 396 kilo Novo units of amylase activity/kg of TMR DM) were used as donor of ruminal fluid. The in vitro gas production kinetics was evaluated according to a dual-pool logistic model. The chemical composition and gas production kinetics were affected by the hybrid and phenological stages. The flint hybrid had lower range for chemical analysis among physiological stages. Harvesting at ½M and ¾M improved DM content, bromatological composition and silage quality parameters compared to dent or flint types. Amylase (i) increased methane (CH 4 ) production and in vitro dry matter digestibility (IVDMD) in ½M stage, (ii) improved digestion kinetics by reducing lag time and increasing total gas production and fermentation rates of non-fibrous carbohydrates (NFC) and fibrous carbohydrates (FC), and (iii) increased extent and fermentation rate of NFC and increased fermentation rate of FC fraction in whole-crop maize silages produced from dent or flint types in all phenological stages. Harvesting between ½M and ¾M is the best phenological stage to improve chemical composition and silage quality parameters. Exogenous amylase showed improvements on fibre digestion of silages at ½M and ¾M phenological stages in both grain types of corn., (© 2019 Blackwell Verlag GmbH.)

Convolutional neural network (CNN) can be used to quickly identify crop seed varieties. 1200 seeds of ten soybean varieties were selected, hyperspectral images of both the front and the back of the seeds were collected, and the reflectance of soybean was derived from the hyperspectral images. A total of 9600 images were obtained after data augmentation, and the images were divided into a training set, validation set, and test set with a 3:1:1 ratio. Pretrained models (AlexNet, ResNet18, Xception, InceptionV3, DenseNet201, and NASNetLarge) after fine-tuning were used for transfer training. The optimal CNN model for soybean seed variety identification was selected. Furthermore, the traditional machine learning models for soybean seed variety identification were established by using reflectance as input. The results show that the six models all achieved 91% accuracy in the validation set and achieved accuracy values of 90.6%, 94.5%, 95.4%, 95.6%, 96.8%, and 97.2%, respectively, in the test set. This method is better than the identification of soybean seed varieties based on hyperspectral reflectance. The experimental results support a novel method for identifying soybean seeds rapidly and accurately, and this method also provides a good reference for the identification of other crop seeds.

Proper diet and nutrition are essential for maintaining the health of captive birds, but specific nutritional requirements can vary by species. Our knowledge of avian nutrition is predominantly based on data collected from gallinaceous birds, which is the primary basis for the dietary recommendations for companion birds, such as budgerigars ( Melopsittacus undulatus ) and other psittacine birds, potentially leading to a higher risk of malnutrition. In the wild, budgerigars eat predominantly Australian grass seed of the Astrebla genus, which may not be similar to the commercially available food fed to captive budgerigars, both in nutrient content and in their physiologic effects. In this study, we examined the relationship between diet type and immune function by separating 36 budgerigars into 3 dietary treatments: 1) Roudybush formulated pellet diet (Roudybush BirdFood Inc, Woodland, CA, USA), 2) Kaytee Forti-Diet Pro Health seed mix (Kaytee Products Inc, Chilton, WI, USA), and 3) a natural seed diet containing fresh canary grass, flax, nyger, oat groats, and white millet seeds. We monitored body weight, measured the microbial killing ability of whole blood by Escherichia coli and Candida albicans , and collected blood smears to assess white blood cell counts during a period of 8 weeks. Overall, we observed no significant effects of the 3 different diets on bird microbial killing ability or on white blood cell counts, suggesting similar health outcomes for budgerigars that consume mixed seed and those that receive pellet-based diets during this relatively short-term study.

Background: Domestication and improvement processes, accompanied by selections and adaptations, have generated genome-wide divergence and stratification in soybean populations. Simultaneously, soybean populations, which comprise diverse subpopulations, have developed their own adaptive characteristics enhancing fitness, resistance, agronomic traits, and morphological features. The genetic traits underlying these characteristics play a fundamental role in improving other soybean populations., Results: This study focused on identifying the selection signatures and adaptive characteristics in soybean populations. A core set of 245 accessions (112 wild-type, 79 landrace, and 54 improvement soybeans) selected from 4,234 soybean accessions was re-sequenced. Their genomic architectures were examined according to the domestication and improvement, and accessions were then classified into 3 wild-type, 2 landrace, and 2 improvement subgroups based on various population analyses. Selection and gene set enrichment analyses revealed that the landrace subgroups have selection signals for soybean-cyst nematode HG type 0 and seed development with germination, and that the improvement subgroups have selection signals for plant development with viability and seed development with embryo development, respectively. The adaptive characteristic for soybean-cyst nematode was partially underpinned by multiple resistance accessions, and the characteristics related to seed development were supported by our phenotypic findings for seed weights. Furthermore, their adaptive characteristics were also confirmed as genome-based evidence, and unique genomic regions that exhibit distinct selection and selective sweep patterns were revealed for 13 candidate genes., Conclusions: Although our findings require further biological validation, they provide valuable information about soybean breeding strategies and present new options for breeders seeking donor lines to improve soybean populations., (© The Author(s) 2019. Published by Oxford University Press.)

Antibiotics can induce adverse effects on plants. Brassica crop seeds, for their advantages, are used widely in seed germination test to investigate phytotoxicity of substances. However, their performances on evaluating antibiotics remain to be studied to select sensitive species for control of potential risks. In this work, common species of Chinese cabbage (Brassica rapa L.), edible rape (Brassica napus L.), and cabbage (Brassica oleracea L.) with three cultivars each were selected to compare and analyze the sensitivity difference of their seeds to tetracycline (TC) stress. Results showed that the ratio of axis to cotyledon (RAC) by fresh weight was an alternative endpoint besides radicle length (RL) in the test. The species sensitivity distribution (SSD) based on the effective concentrations causing x% inhibition (EC x ) in RL of seeds exposed to TC was applied to compare the sensitivity of seeds and estimate the hazardous concentration for x% species (HC x ). From the species-dependent sensitivity and the sensitivity difference of cultivars in the same species of seeds to TC, the performance of Chinese cabbage was the best in the study. The sensitivity of seeds to TC could be evaluated by EC 20 related to seed physical traits and germination indices, while the extent of seeds affected by TC could be evaluated by EC 50 related to the composition of seed storage reserves. We recommended that it was a new idea to analyze responses of different seeds to TC at large scale according to seed innate characteristics., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The germination process activates amylolytic enzymes that can produce rice syrup through mashing, however the factors affecting enzyme activities and soluble saccharides have not been investigated. This study characterized amylolytic enzymes activities, including α-amylase, β-amylase, and α-glucosidase, and soluble saccharides from germinated rice cultivars of four rice cultivars, including waxy, short grain, medium grain, and long grain, under aerobic and anaerobic germination conditions over 4 days and then mashed at 55, 65, 75, and 85 °C. The results showed that the long-grain rice had higher activities of all three enzymes, whereas the waxy rice exhibited lower activities. Glucose and maltose were the predominant saccharides at low mashing temperatures of 55 °C and 65 °C; saccharides of degree of polymerization 3 to 7 became significant at mashing temperatures of 75 °C and 85 °C. The amount and composition of saccharides were strongly influenced by rice cultivar, and germination and mashing conditions. The findings highlight the importance of rice components and starch structure on the amount and composition of soluble saccharides from germinated brown rice. PRACTICAL APPLICATION: Rice syrup is commercially produced by the addition of external bacterial enzymes to brown or milled rice. Germinated brown rice is naturally rich in nutrients and amylases, both are produced during the germination process. Because of the presence of naturally activated amylases, germinated brown rice could be used to produce rice syrup without the addition of external enzymes while preserving the nutrients from germination of brown rice., (© 2019 Institute of Food Technologists®.)

Background: Colombia is known for its production of fine and aromatic cocoa; however, the lack of homogeneity in the ripeness stage of cocoa fruit affects the final quality of cocoa beans. Therefore, the aim of this work was to identify parameters that can be use as indicators of ripeness in cocoa fruit in order to homogenize the characteristics of raw cocoa used in the production of cocoa-products industry. The parameters evaluated were fruit, seed and pod weight, firmness, color, polar and equatorial diameters of the fruit, seed moisture content, total titratable acidity, pH, and total soluble solids of pulp., Results: Factors such as seed weight, firmness, diameters, total soluble solids, pH, and acidity were affected by the clone factor, whereas seed weight, pH, and total titratable acidity were affected by ripeness stage., Conclusion: Identification of indicators of ripeness for cocoa fruit is a complex task due to the influence of the clone on the evolution of the physicochemical characteristics of cocoa fruit during its maturation process. Thus, indicators must be developed for each clone, and at least two parameters among color, pH, and total titratable acidity should be used to determine the ripeness stage of cocoa fruit. © 2019 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2019 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

Cotton seed purity is a critical factor influencing the cotton yield. In this study, near-infrared hyperspectral imaging was used to identify seven varieties of cotton seeds. Score images formed by pixel-wise principal component analysis (PCA) showed that there were differences among different varieties of cotton seeds. Effective wavelengths were selected according to PCA loadings. A self-design convolution neural network (CNN) and a Residual Network (ResNet) were used to establish classification models. Partial least squares discriminant analysis (PLS-DA), logistic regression (LR) and support vector machine (SVM) were used as direct classifiers based on full spectra and effective wavelengths for comparison. Furthermore, PLS-DA, LR and SVM models were used for cotton seeds classification based on deep features extracted by self-design CNN and ResNet models. LR and PLS-DA models using deep features as input performed slightly better than those using full spectra and effective wavelengths directly. Self-design CNN based models performed slightly better than ResNet based models. Classification models using full spectra performed better than those using effective wavelengths, with classification accuracy of calibration, validation and prediction sets all over 80% for most models. The overall results illustrated that near-infrared hyperspectral imaging with deep learning was feasible to identify cotton seed varieties., Competing Interests: The authors declare no conflict of interest.

Volatile profiles of oat-based foods are mainly analyzed on the oat flakes and porridge as snack or breakfast, whereas the volatile characteristics of the traditional Chinese oat meal (TCOM), a popular main food in some regions of northern China, with special strong aroma, are not known. Here, we compared the volatile profiles from headspace solid phase microextraction gas chromatography-mass spectrometry analysis of oat porridge (OP) and TCOM, which were of different processing and cooking methods, from those of different cultivars, and analyzed the effect of cultivation locations on oat volatile features. Apart from the 35 volatiles shared by OP and TCOM, there were 23 and 24 volatiles specific to OP and TCOM, respectively, with the later showing more toasting and frying-related volatiles due to the dry frying process of the grains before milling. Principle component analysis of the volatiles of OP and TCOM from 16 cultivars showed that they were clustered into two groups, and four cultivars were clustered together, independent of processing and cooking methods. The oat volatile profiles of cultivars grown in three regions of north China were dependent on the cultivation locations rather than cultivars, regardless of OP or TCOM, with those from Datong of Shanxi Province and Zhangjiakou of Hebei Province clustered together. The location effect could be due to significant less precipitation in the two regions above than the other region Ulanqab of Inner Mongolia. PRACTICAL APPLICATION: The volatile compounds in oat are closely related to cultivation regions, which could be applied as a key factor by oat producers for marketing. The four cultivars showed similar and stable volatile profiles, which could be used as reference cultivars for breeding of high-quality oat with better flavor., (© 2019 Institute of Food Technologists®.)