Single Seeds Research Articles

Design and Parameter Optimization of a Finger Clip Plate Garlic Seed-Metering Device Based on EDEM

In present-day mechanized garlic seeding, high missing rates and low qualified percentages of single seeds are common problems; thus, a finger clip plate garlic seed-metering device was designed in this study. First, the structure and working principle of the seed-metering device were studied. Subsequently, the critical component parameters of the seed-metering device were determined using theoretical calculations; then, EDEM software was used in single-factor simulation experiments to analyze the effects of opening the diameter of the seed-collecting spoon, the operating speed of the seeding tray, and the population number on the seed-filling performance. Finally, a Box–Behnken center combination experiment was conducted with the population, opening the diameter of the seed-collecting spoon, and rotating the speed of the seeding tray as experiment factors, with the single-seed filling rate, qualified percent, and missing rate as evaluation indicators. A three-factor and three-level orthogonal test was conducted to establish the mathematic regression model of the experiment factors and evaluation indicators, as well as to realize the parameter optimization. After rounding, the laboratory validation test was carried out with 240~280 seeds, a 26 mm seed scoop-opening diameter, and a 28 r/min operating speed. The average qualified rate, missing rate, and reply rate of single seeds were 91.86%, 2.71%, and 5.43%, respectively, which is basically consistent with the forecast results of regression model.

Moisture detection of single corn seed based on hyperspectral imaging and deep learning

Precision seeding technology for corn puts forward higher quality requirements for single-kernel corn seed. Moisture is one of four mandatory inspection items of China's national crop seed quality standards. Therefore, accurate determination of the moisture content of a single corn seed is of great significance for corn precision seeding. However, traditional moisture detection methods for corn specified in the national standard, such as the oven-drying method, have the disadvantage of being time-consuming, destroying samples and inability to detect single-kernel samples. The study aimed to explore a rapid, non-destructive, high-precision method to detect the moisture content of single corn seeds based on hyperspectral imaging technology. The hyperspectral images of embryo and non-embryo surfaces of single-kernel samples were acquired with the rage of 968.05–2 575.05 nm. The spectra of each kernel were calculated by averaging the two sides' spectra. The moisture models of single kernels were established separately by PLS, CNN, LSTM and CNN-LSTM based on two sides' spectra. The comprehensive index (R/(1 + RMSE)) was proposed combined correlation coefficient (R) with root mean square error (RMSE) to evaluate the models. The results indicated that the CNN-LSTM model of the embryo-side was optimal for moisture content determination with the comprehensive index (RMSE/(1 + R)) of 0.141 in prediction sets. Therefore, hyperspectral imaging technology combined with deep learning can be considered a promising tool for non-destructive and high-throughput moisture detection in single corn seeds.

Single seeds exhibit transcriptional heterogeneity during secondary dormancy induction.

Seeds are highly resilient to the external environment, which allows plants to persist in unpredictable and unfavorable conditions. Some plant species have adopted a bet-hedging strategy to germinate a variable fraction of seeds in any given condition, and this could be explained by population-based threshold models. Here, in the model plant Arabidopsis (Arabidopsis thaliana), we induced secondary dormancy (SD) to address the transcriptional heterogeneity among seeds that leads to binary germination/nongermination outcomes. We developed a single-seed RNA-seq strategy that allowed us to observe a reduction in seed transcriptional heterogeneity as seeds enter stress conditions, followed by an increase during recovery. We identified groups of genes whose expression showed a specific pattern through a time course and used these groups to position the individual seeds along the transcriptional gradient of germination competence. In agreement, transcriptomes of dormancy-deficient seeds (mutant of DELAY OF GERMINATION 1) showed a shift toward higher values of the germination competence index. Interestingly, a significant fraction of genes with variable expression encoded translation-related factors. In summary, interrogating hundreds of single-seed transcriptomes during SD-inducing treatment revealed variability among the transcriptomes that could result from the distribution of population-based sensitivity thresholds. Our results also showed that single-seed RNA-seq is the method of choice for analyzing seed bet-hedging-related phenomena.

Comparison of two Genomic DNA Extraction Protocols from Single Dray Seed of Barley Crop

Modern plant breeding studies are largely based on plant genetic engineering programs. Extraction of DNA with high quality plays as a key factor in most of plant genetic Studies, therefore two different DNA extraction protocols based on CTAB buffer and SDS buffer were tested for the purpose of selecting the best DNA extraction protocol from dry seeds of nine variety of barely plant . Barley seeds were taken from Libyan seeds gene bank .After Barely samples were prepared DNA was extracted directly using CTAB and SDS solutions .The quality of extracted DNA was assessed by spectrophotometric measurements and gel electrophoresis system. The results of this study showed that purity of extracted DNA by CTAB method was clearly batter compared with SDS method. CTAB method seemed to be more effective for extracting DNA from barely dry seeds. High quality DNA obtained through use of CTAB method, while CTAB had overall better A260/A280 ratio (1.736-1.932). SDS method seemed to be not suitable for DNA extraction from dry seeds of barely crop.

Investigation of seeded vertical gradient freeze (VGF) growth of CdZnTe bulk crystals

Due to the requirement for superheating above the melting point in the homogenization process of CdZnTe material, complete seed melting remains as a significant problem for the seeded vertical gradient freeze (VGF) growth of CdZnTe. In addition, due to the typical low single crystal yields in VGF growth of CdZnTe, obtaining single crystal seed material with desired geometries could be considered as a challenge. In this study, single crystal CdZnTe seeds of cylindrical geometry with 10 mm diameter and up to 30 mm length were successfully obtained using a Computer Numerical Control (CNC) cutting system. Moreover, to avoid complete seed melting, a novel design of the growth crucible and support system along with radiation shielding around seed region is employed. Temperature profiling and growth experiments were conducted to observe seed melting and seeded crystal growth of CdZnTe. Initial results of a seeded VGF growth using a single crystal CdZnTe seed is reported.

Identification of high-oleic peanut chemical mutants and functional analysis of mutated FAD2B gene

AbstractIt is generally accepted that high-oleic crops have at least 70% oleate. As compared to their normal-oleic counterparts, oil and food products made from high-oleic peanut have better keeping quality and are much healthier. Therefore, high-oleic peanut is well recognized by processors and consumers. However, owing to the limited availability of high-oleic donors, most present-day high-oleic peanut varietal releases merely have F435 type FAD2 mutations. Through screening of a mutagenized peanut population of 15L46, a high-yielding peanut line with desirable elliptical oblong large seeds, using near infrared model for predicting oleate content in individual single seeds, high-oleic peanut mutants were identified. Sequencing FAD2A and FAD2B of the mutants along with the wild type revealed that these mutants possessed G448A FAD2A (F435 type FAD2A mutation) and G558A FAD2B (non-F435 type FAD2B mutation). Expression of the wild and mutated type FAD2B in yeast verified that the functional mutation contributed to the high-oleic phenotype in these mutants. The mutants provided additional high-oleic donors to peanut quality improvement.

Detection Method of Damaged Camellia Oleifera Seeds Based on YOLOv5-CB

To solve the problems that the existing sorting equipment cannot effectively identify and sort damaged Camellia oleifera seeds and traditional manual sorting of damaged Camellia oleifera seeds is inefficient and slow, in this paper, a damaged Camellia oleifera seeds detection method based on YOLOv5, coordinate attention, and weighted bidirectional feature pyramid network was designed. In this study, according to the actual requirements, firstly, the Coordinate Attention module (CA) was added to the YOLOv5 algorithm to improve the detection precision of damaged Camellia oleifera seeds in stacked Camellia oleifera seeds. Secondly, the network structure was optimized and the weighted bi-directional feature pyramid network (BiFPN) was added. The module integrates multi-scale features from top to bottom to reduce the missed detection of slightly damaged Camellia seeds. The final experimental results show that compared with the original YOLOv5 model, the detection precision of the improved model YOLOV5-CB is improved by 6.1%, reaching 92.4%, and the mean Average Precision (mAP) is also improved from 87.7% to 93.4%, the average detection time of a single Camellia seeds image is 6.4ms, which meet the requirements of precision and real-time in practical application.

Spatial-temporal distribution and sequence diversity of group a human respiratory syncytial viruses in Kenya preceding the emergence of ON1 genotype.

BackgroundHuman respiratory syncytial virus (HRSV) is a major cause of severe viral acute respiratory illness and contributes significantly to severe pneumonia cases in Africa. Little is known about its spatial–temporal distribution as defined by its genetic diversity.MethodsA retrospective study conducted utilizing archived nasopharyngeal specimens from patients attending outpatient clinics in hospitals located in five demographically and climatically distinct regions of Kenya; Coast, Western, Highlands, Eastern and Nairobi. The viral total RNA was extracted and tested using multiplex real time RT‐PCR (reverse transcriptase polymerase chain reaction). A segment of the G‐gene was amplified using one‐step RT‐PCR and sequenced by Sanger di‐deoxy method. Bayesian analysis of phylogeny was utilized and subsequently median joining methods for haplotype network reconstruction.ResultsThree genotypes of HRSVA were detected; GA5 (14.0%), GA2 (33.1%), and NA1 (52.9%). HRSVA prevalence varied by location from 33% to 13.2% in the Highlands and the Eastern regions respectively. The mean nucleotide diversity (Pi[π]) varied by genotype: highest of 0.018 for GA5 and lowest of 0.005 for NA1. A total of 58 haplotypes were identified (GA5 10; GA2 20; NA1 28). These haplotypes were introduced into the population locally by single haplotypes and additional subsidiary seeds amongst the GA2 and the NA1 haplotypes.ConclusionsHRSVA was found across all the regions throughout the study period and comprised three genotypes; GA5, GA2, and NA1 genotypes. The genotypes were disproportionately distributed across the regions with GA5 gradually increasing toward the Western zones and decreasing toward the Eastern zones of the country.

Applicability of Near Infrared Reflectance Spectroscopy to Predict Amylose Contents of Single-Grain Maize

Near infrared reflectance spectroscopy (NIRS) and reference data were used to determine the amylose contents of single maize seeds to enable rapid, effective selection of individual seeds with desired traits. To predict the amylose contents of a single seed, a total of 1069 (865 as calibration set, 204 as validation set) single seeds representing 120 maize varieties were analyzed using chemical methods and performed calibration and external validation of the 150 single seeds set in parallel. Compared to various spectral pretreatments, the regression of partial least squares (PLS) with mathematical treatment of Harmonization showed the final optimization. The single-seed amylose contents showed the root mean square error of calibration (RMSEC) of 2.899, coefficient of determination for calibration (R2) of 0.902, and root mean square error of validation (RMSEV) of 2.948. In external validations, the coefficient of determination in cross-validation (r2), root mean square error of the prediction (RMSEP) and ratio of the standard deviation to SEP (RPD) were 0.892, 2.975 and 3.086 in the range of 20–30%, respectively. Therefore, NIRS will be helpful to breeders for determining the amylose contents of single-grain maize.

Does spatial region of interest (ROI) matter in multispectral and hyperspectral imaging of segmented wheat kernels?

Advances in optics technology and computational processing have brought multispectral and hyperspectral imaging to commercial sorting of fruits and vegetables, yet the application of imaging to single cereal seeds has lagged due to the enormity in numbers of seeds and challenges posed by lighting, shadowing, and seed curvature that are less problematic with larger objects. This study examined the effect of region of interest (ROI) size on the seed surface with respect to the ability to sort seed into accept and reject categories. Regions of interest (ROI) size ranged from 5 centrally located pixels arranged in a cross to all pixels (typically 100) contained in the viewed surface of a kernel. Two modeling structures were used; the first involving all 87 samples, with approximately 220 kernels per sample, in which mixture level of sound and fusarium-damaged kernels is known, but individual kernel class is unknown; and the second involving 5 samples, of which an equal number of 287 known sound and known fusarium-damaged kernels were used. Accordingly, the larger set model characterised the dispersion (by standard deviation) of kernel-to-kernel reflectance at a single representative wavelength, while the smaller set was used to develop linear discriminant analysis classification models using one to three wavelengths. With either case, it was found that the smaller ROIs should be sufficient for a two-class (accepts, rejects) structure. • Hyperspectral imaging of cereal seeds for sorting is gaining popularity. • Seed curvature poses challenges to reflection measurements. • For accept/reject sorting, region of interest may be smaller than the viewed seed.

Non-Destructive Assessment of Edible Seed Chemical Content by Near-Infrared Hyperspectral Imaging for the Improvement of Nutritional Traits in Bottle Gourd (Lagenaria Siceraria)

The edible seeds of bottle gourd [Lagenaria siceraria (Molina) Standl.] are rich in oils, proteins and minerals of high nutritional quality. They are highly prized in pan tropical regions where they constitute valuable resources for food and nutrition security. In this study, near-infrared hyperspectral imaging (NIR-HSI) was combined with chemometrics to assess the variability of seed chemical content of African cultivars for the selection of nutritional traits. Six hundred seeds of four accessions belonging to two cultivars were collected from the Ivory Coast (West Africa) and analysed. The NIR-HSI spectra collected on whole seeds in the 1100-2400 nm range revealed that the main absorption bands of the seed chemical content were associated with water, lipids and proteins. The absorbance values between seeds of the same accession in these spectral regions varied up to 1.8 folds. Among the two chemometric tools used, principal component analysis (PCA) did not separate the accessions while Partial Least Squares Discriminant Analysis (PLS-DA) discriminated the accessions with 87.33 % to 94.67 %, and the cultivars with 90 % to 92 % correct classification. Seed oils from bottle gourd are for instance rich in linoleic acid which is an essential fatty acid for human health. The non-destructive and qualitative determination of the content of single seeds was demonstrated in the study and provides the opportunity to select superior seeds for the improvement of key nutritional traits in bottle gourd. Lagenaria siceraria, near-infrared hyperspectral imaging, seed chemical content, PCA, PLS-DA, nutrition security

Classification of weed seeds based on visual images and deep learning

Weeds are mainly spread by weed seeds being mixed with agricultural and forestry crop seeds, grain, animal hair, and other plant products, and disturb the growing environment of target plants such as crops and wild native plants. The accurate and efficient classification of weed seeds is important for the effective management and control of weeds. However, classification remains mainly dependent on destructive sampling-based manual inspection, which has a high cost and rather low flux. We considered that this problem could be solved using a nondestructive intelligent image recognition method. First, on the basis of the establishment of the image acquisition system for weed seeds, images of single weed seeds were rapidly and completely segmented, and a total of 47 696 samples of 140 species of weed seeds and foreign materials remained. Then, six popular and novel deep Convolutional Neural Network (CNN) models are compared to identify the best method for intelligently identifying 140 species of weed seeds. Of these samples, 33 600 samples are randomly selected as the training dataset for model training, and the remaining 14 096 samples are used as the testing dataset for model testing. AlexNet and GoogLeNet emerged from the quantitative evaluation as the best methods. AlexNet has strong classification accuracy and efficiency (low time consumption), and GoogLeNet has the best classification accuracy. A suitable CNN model for weed seed classification could be selected according to specific identification accuracy requirements and time costs of applications. This research is beneficial for developing a detection system for weed seeds in various applications. The resolution of taxonomic issues and problems associated with the identification of these weed seeds may allow for more effective management and control.

Combining ability for main quality traits in peanut (Arachis hypogaea L.)

High-oleic peanuts has been recognized by processing sectors, seed sellers and consumers for their longer shelf life, longer seed life and mutiple healthe benefits. High oleate is becoming a requisite ​for varietal releases in many peanut breeding programs at present. To select desirable parents for high-oleic peanut breeding, the study was conducted to evaluate the combining ability of 5 high-oleic donors from our research team, based on quality of individual single seeds. General combining ability was significant for oleic, linoleic, stearic and palmitic acid, oil and protein, while specific combining ability was significant for the traits except oil. Among them, oil content was found to be conditioned solely by additive gene actions, and for other quality traits, additive gene effects were more important than non-additive gene effects. High-oleic CTW and normal-oleic Xiaojingsheng were selected as the best general combiners for peanut oleic acid improvement. Narrow-sense heritability was high for quality traits other than protein, suggesting that there was high potential for genetic improvement in these traits.

Effects of I-125 seeds combined with anlotinib on tumor growth and bone metabolism in A549 tumor-bearing mice

Purpose This study aimed to investigate the therapeutic potential of tumor suppression and mechanism for different implantation modes of iodine-125 (I-125) seeds irradiation in a mice xenograft model, and its skeletal complications. Materials and methods A total of 24 mice carrying A549 lung tumor-derived xenografts were randomly assigned to four groups, including non-radioactive (sham) seeds implantation, I-125 seeds fractional implantation, I-125 seeds single implantation and I-125 seeds single implantation combined with anlotinib. Ki67 immunohistochemistry, TUNEL immunofluorescence and CD31 morphometric analysis were used to determine the proliferation index, rate of apoptotic cells and microvessel density, respectively. Additionally, the side effects on the skeletal system in mice treated with I-125 seeds implantation were evaluated by histomorphometric staining with tartrate-resistant acid phosphate (TRAP) and alkaline phosphatase (ALP) expression in femur, tartrate-resistant acid phosphatase 5b (TRACP-5b) and procollagen type I N-terminal propeptide (PINP) levels in serum were evaluated by enzyme-linked immunosorbent assay (ELISA). Results The I-125 seeds single and fractionated implantation had similar therapeutic effects and complications when the total number of I-125 seeds was the same. A single implantation of I-125 seeds with or without anlotinib could analogously inhibit the tumor growth in xenografts mice, while the single implantation combined with anlotinib had more effective in tumor inhibition. The results of Ki67, TUNEL and CD31 staining confirmed an evident reduction in tumor cell proliferation and angiogenesis, as well as an increase in apoptosis. A relatively integrated bone metabolism was indicated after I-125 seeds single implantation with or without anlotinib, and the results were similar in I-125 seeds fractional implantation, including a reduction in the number of TRAP-positive cells and an increase in ALP expression level. Additionally, the serum TRACP-5b activity was decreased and the serum PINP concentration was increased following I-125 seeds implantation. Conclusions Single and fractionated implantation pattern of I-125 radioactive seeds had similar therapeutic efficacy against tumor growth, while brachytherapy with I-125 seeds implantation may be an effective and safe treatment strategy for its potential protection against cancer treatment-induced bone loss.

A 13.96‐kb chromosomal deletion of two genes is responsible for the tomato seed size in watermelon (Citrullus lanatus)

AbstractSeed size is an important agronomic trait in watermelon, but the candidate genes and underlying molecular mechanism are not fully known. In the present study, genetic analysis of the BC1 population derived from two parental lines revealed that watermelon seed size is controlled by a single locus and medium seeds are dominant to tomato seeds. In addition, we constructed a genetic linkage map. The total length of the linkage map was 1629.92 cM, with an average distance of .16 cM. QTL mapping and resequencing analysis identified a 13.96‐kb chromosomal deletion on chromosome 2. There were only two genes (Cla97C02G045390 and Cla97C02G045400) present in the corresponding region. Transcriptome data of tomato seed and medium seed watermelons showed that the two genes were always highly expressed in medium seed plants but expressed at low or no levels in tomato seed plants. Moreover, two markers indicated that the genes were related to watermelon seed size. Our present study provides key genetic variation and potential candidate gene of watermelon seed size and lays the foundation for the molecular mechanism of seed size.

Dimensions controllable synthesis of silver Nano-morphologies via moderate one step methodology

The common polyol techniques were used for the synthesis of solo metallic morphology. Here we reported the single-step polyol-solvothermal strategy for the synthesis of zero, one, two, and three-dimension silver structure by simply switching the reaction pressure with the help of silver amount and halide ions. Silver seeds in the presence of Cl- ion, at 74.1 mmHg grow in [111] and at 97.4 mmHg grow in [110] direction for the formation of 0D-Ag and 1D-Ag respectively, by protecting (100) facet. Extra halide (Br-) presence at 93.2 mmHg imposes the seeds to grow [110], [100] direction for 2D-Ag, while at 97.4 mmHg grow only in [100] direction for 3D-Ag, due to etching and formation of single crystal seeds. This closed reaction system doesn’t need any kind of oxygen scavengers, inert gases, nor need to tune injection speed and stirring speed. This switching strategy can be implemented for the synthesis of other metallic morphologies.

A Comparative Study of Self-Expandable Metallic Stent Combined with Double 125I Seeds Strands or Single 125I Seeds Strand in the Treatment of Advanced Perihilar Cholangiocarcinoma with Malignant Obstructive Jaundice.

PurposeThe purpose of this study was to compare the safety and effectiveness of a self-expandable metallic stent (SEMs) with a novel brachytherapy biliary drainage catheter (BBDC, double 125I seeds strands) or a single 125I seeds strand in the treatment of advanced perihilar cholangiocarcinoma (pCCA) with malignant obstructive jaundice (MOJ).MethodsFrom September 2016 to December 2018, we retrospectively enrolled patients with biliary stent implantation after receiving either BBDC loaded with 125I seeds (double-strands irradiation group) or an 125I seed strand treatment (single-strand irradiation group, control group). The outcomes were analyzed regarding the relief of obstructive jaundice, and interventional-related complications. Moreover, the Kaplan–Meier method was used to analyze stent patency and survival.ResultsThe success rate of interventional therapy in both groups was 100%, and all patients with MOJ were alleviated. According to the Common Terminology Criteria for Adverse Events (CTCAE 4.02), the grade 3 or 4 complications in the BBDC group and in the control group were 6/34 (17.65%) and 7/39 (17.95%), respectively (P > 0.05). The median and mean overall stent patency of the BBDC group and the control group were 207 days versus 180 days, 204.212 days versus 186.278 days (P = 0.043). The median and mean overall survivals in the BBDC group were higher than those in the control group (245 days versus 212 days, 244.883 days versus 221.844 days, P = 0.030).ConclusionThis interim analysis showed that BBDC (double-stranded irradiation) can prolong the stent patency time compared with 125I seed strand treatment (single-stranded irradiation) and had the advantage of reducing jaundice, which seemed to extend the survival period of advanced pCCA.

Proteomics Variation in Nigella Sativa L. (Rananculaceae) Germplasm

Study revealed a first report of proteomics variation in Nigella sativa L. based on analyzing 32 accessions through SDS-PAGE. Three prominent regions along eight subunits were identified. Intra specific variation was observed low whereas the sharpness of bands was high between first and second regions. It was noted that in second region there was no clear evidence of band formation in N. sativa. Prominent and sharp protein peptide bands were recorded in four accessions, namely PK-020561, PK-020609, PK-020620 and PK-020646. Further investigation of single seeds showed almost similar genetic pattern within the single accession. Five clusters were formed on the basis of Euclidean distance. Cluster-I & II contain 1, 1 accession each, likewise Cluster-III and C-IV contain 2, 2 accessions whereas Cluster-V was found diversified as consisted of 26 accessions. Two accessions PK-020878 and PK-020877 were recommended for polymorphism and crop improvement programs.
 Bangladesh J. Bot. 50(2): 289-294, 2021 (June)

Multichannel imaging for monitoring chemical composition and germination capacity of cowpea (Vigna unguiculata) seeds during development and maturation

This study aimed to set a computer-integrated multichannel spectral imaging system as a high-throughput phenotyping tool for the analysis of individual cowpea seeds harvested at different developmental stages. The changes in germination capacity and variations in moisture, protein and different sugars during twelve stages of seed development from 10 to 32 days after anthesis were non-destructively monitored. Multispectral data at 20 discrete wavelengths in the ultraviolet, visible and near infrared regions were extracted from individual seeds and then modelled using partial least squares regression and linear discriminant analysis (LDA) models. The developed multivariate models were accurate enough for monitoring all possible changes occurred in moisture, protein and sugar contents with coefficients of determination in prediction Rp2 of 0.93, 0.80 and 0.78 and root mean square errors in prediction (RMSEP) of 6.045%, 2.236% and 0.890%, respectively. The accuracy of PLS models in predicting individual sugars such as verbascose and stachyose was reasonable with Rp2 of 0.87 and 0.87 and RMSEP of 0.071% and 0.485%, respectively; but for the prediction of sucrose and raffinose the accuracy was relatively limited with Rp2 of 0.24 and 0.66 and RMSEP of 0.567% and 0.045%, respectively. The developed LDA model was robust in classifying the seeds based on their germination capacity with overall correct classification of 96.33% and 95.67% in the training and validation datasets, respectively. With these levels of accuracy, the proposed multichannel spectral imaging system designed for single seeds could be an effective choice as a rapid screening and non-destructive technique for identifying the ideal harvesting time of cowpea seeds based on their chemical composition and germination capacity. Moreover, the development of chemical images of the major constituents along with classification images confirmed the usefulness of the proposed technique as a non-destructive tool for estimating the concentrations and spatial distributions of moisture, protein and sugars during different developmental stages of cowpea seeds.

An Assessment of the Lolium perenne (Perennial Ryegrass) Seedborne Microbiome across Cultivars, Time, and Biogeography: Implications for Microbiome Breeding.

Research into the bacterial component of the seed microbiome has been intensifying, with the aim of understanding its structure and potential for exploitation. We previously studied the intergenerational seed microbiome of one cultivar of perennial ryegrass with and without one strain of the commercially deployed fungal endophyte Epichloë festucae var. lolii. The work described here expands on our previous study by exploring the bacterial seed microbiome of different commercial cultivar/Epichloë festucae var. lolii combinations in collections of single seeds from the harvest year 2016. In this dataset, a cultivar effect could be seen between the seed microbiomes from cultivars Alto and Trojan. The bacterial component of the seed microbiome from pooled seeds from a single cultivar/E. festucae var. lolii combination harvested from 13 seed production farms around Canterbury in the year 2018 was also studied. This dataset allows the effect of different production locations on the bacterial seed microbiome to be examined. By comparing the two sets of data, bacteria from the genera Pantoea, Pseudomonas, Duganella, Massilia, and an unknown Enterobacteriaceae were observed to be in common. This core bacterial microbiome was stable over time but could be affected by supplemental taxa derived from the growth environment of the parental plant; differing microbiomes were seen between different seed production farms. By comparison to a collection of bacterial isolates, we demonstrated that many of the members of the core microbiome were culturable. This allows for the possibility of exploiting these microbes in the future.