This study was conducted to evaluate the Al3+ tolerance of sixteen camelina genotypes and to use melatonin or nano-selenium to alleviate Al3+-induced stress. A Petri dish study indicated seedling root length was suitable for describing the dose–response of seedling growth with increased Al3+ concentrations. Based on GR50 (Al3+ concentration causing a 50% reduction in the seedling root length), CamK6 (232.0 mg L−1) and CamK2 (97.0 mg L−1) were the most Al3+-tolerant and -sensitive genotypes, respectively. Under Al3+ stress, CamK6 and CamK2 treated by melatonin (50 μM) or nano-Se (0.4 mg L−1) showed a similar plant height and seed yield plant−1 (CamK6: 123.6 ± 9.8 cm and 0.562 ± 0.62 g; CamK2: 109.2 ± 8.7 cm and 0.49 ± 0.5 g) as the controls (CamK6: 121.1 ± 10.2 cm and 0.554 ± 0.4 g; CamK2: 110.0 ± 9.8 cm and 0.5 ± 0.4 g), and the values were greater than for the Al3+-treated plants (CamK6: 96.4 ± 9.2 cm and 0.48 ± 0.34 g; CamK2: 97.3 ± 8.1 cm and 0.42 ± 0.31 g). The results showed that melatonin or nano-Se through modulating biochemical reactions (e.g., antioxidant enzyme) can alleviate Al3+-induced growth inhibition in camelina. This study suggested melatonin or nano-Se can alleviate Al3+-induced growth inhibition by maintaining seed yield and improving oil quality in camelina.

Accurate identification and quantification of pollens (e.g., pollen of a flower, airborne pollens) is essential to understand plant pollination and reproductive biology, pollen aerobiology, and plant–insect interactions. Currently, a couple of methods are available for pollen counting, such as manual counting, flow cytometry-based and image software-based counting. However, due to inconsistent results and experimental repeatability, a more accurate, consistent, and high-throughput quantification approach is required. This study evaluated and compared the performance between a proposed Swin-transformer-YOLOv5 (S-T-YOLOv5) and common YOLO models in pollen detection and quantification. The present study demonstrated that the S-T-YOLOv5 outperformed other YOLO models, including YOLOv3, YOLOv4, YOLOR, and YOLOv5 for alfalfa (Medicago sativa L.) pollen detection and quantification, with excellent precision (99.6

Identifying insect pollinators and their roles in mediating pollen flow is critical to understand the potential gene flow risks of insect pollination-dependent crop species, such as alfalfa. This study was conducted to evaluate and compare the feasibility of You Only Look Once (YOLO) version 3 (YOLOv3), YOLOv5, YOLOv7, and YOLO Representation (YOLOR) to discriminate the three most common alfalfa pollinating bee species, including honeybee, bumblebee, and leafcutting bee. The metrics comparison results showed YOLOv3 and YOLOv5 outperformed YOLOv7 and YOLOR regarding model precision, recall, F1 score, and mAP50 values. YOLOv3 and YOLOv5 could successfully discriminate the three different bee species with an accuracy of almost 100% (99.9%, 99.8%, and 100% accuracy for honeybee, bumblebee, and leafcutting bee for the two models, respectively). Comparatively, YOLOv7 could discriminate honeybee with an accuracy of 95% but was more likely to mistakenly discriminate bumblebee and leafcutting bee due to the relatively lower discriminating accuracy (87.3% and 66.2%, respectively). While the values of determined parameters for YOLOR were lower than YOLOv3 and YOLOv5, the higher precision (0.99680) along with recall (0.98721), F1 (0.99198), mAP50 (0.99323), and mAP50-100 (0.89076) values indicate that this model could be able to obtain a favorable performance in discriminating the three bee species. In summary, the proposed method in this study has the potential for identifying the alfalfa pollinating bee species, studying the bees' flower-visiting behaviors, evaluating the risks of insect-mediated pollen flow, and thus contributing to the management of genetically engineered (GE) alfalfa transgene flow.

The potential for commercial cultivation of genetically engineered (GE) alfalfa has raised ecological concerns due to the possibility of introgression of GE alleles into conventional populations. The main objectives of this study were to determine the key affecting factors (i.e. size of pollen source, number of pollinating bees) on forming alfalfa pollen cloud density and test the mitigating effect using maize barrier rows on alfalfa pollen dispersal. The results showed that the mean pollen densities of alfalfa pollen source (Ø = 10 or 20 m) were statistically similar when treated with the same number of worker bumblebees and increased accordingly with increasing the worker bees (887 and 853 pollens m-3 h-1 for Ø = 10 and 20 m with 100-150 worker bees, respectively; 1040 and 1070 pollens m-3 h-1 for the two plots with 200-300 worker bees, respectively), demonstrating that the number of worker bees but not the size of the pollen source was the key determinant for forming alfalfa pollen density. A maize barrier row established at 0.5 m from the alfalfa edge consistently decreased downwind pollen densities (percent pollen density of pollen source) to 0.2-4.4 % at 1-9 m compared to 3.4-25.4 % and 7.5-37.8 % at the same distance range for the upwind and downwind sites without maize barrier rows, respectively. Based on the pods formed on the emasculated alfalfa flowers (due to pollen dispersal) located at various distances from the pollen source and subsequent prediction model, the pollen density threshold value for fertilizing alfalfa recipient under the wind-blown condition was determined of 65.8 pollens m-3 h-1 at 14.7 m from the pollen source edge. The results would help in understanding the pollination biology (minimum pollen density for fertilizing alfalfa recipient ovule) and the process of pollen-mediated gene flow and helpful in developing management strategies to reduce the pollen density and thus mitigate the gene flow in alfalfa.

While previous studies have shown camelina drought tolerance relative to other oilseed crops, drought has been documented to severely influence the productivity of camelina. To date, little information is available on the drought tolerance of camelina genotypes. This study was conducted to evaluate drought tolerance in fifteen camelina genotypes and test the alleviative effect of nanoparticles on PEG-induced water deficit stress (WDS) at the whole-plant level at the Yangzhou University Pratacultural Science Experimental Station in September 2021. Four different degrees of WDS were induced by a range of PEG solution concentrations (0, 16.7, 25.0, 37.5, and 56.3 mM). A petri dish study determined that CamK8 and CamK9 (GR50 = 19.0 and 34.3 mM, respectively) were the most sensitive and tolerant genotypes, respectively, to PEG-induced WDS. Results from the whole-plant test showed that the foliar application of MWCNTs (dose: 50 or 100 mg L−1) or nano-Se (dose: 5 or 10 mg L−1) alleviated the adverse effect of PEG-induced WDS, and increased the camelina plant height (ranges: 51.1–56.3 cm) and crop yield (ranges: 0.11–0.14 g plant−1) compared with untreated control and PEG-treated plants (height: 43.5–56.9 cm; yield: 0.06–0.12 g plant−1) in CamK8 without affecting the principal fatty acid composition and groups in camelina oil. The results of this study demonstrated that applying MWCNTs or nano-Se could alleviate WDS and maintain seed yield in camelina, providing the possibility of using these nanoparticles to manage WDS in agricultural practices.

Camelina [Camelina sativa (L.) Crantz] has gained extensive attention in Europe and North America as a potential dietary oil and biofuel feedstock. It is a relatively new crop in Asia (e.g., China, Korea). There is great potential for the cropping of camelina in eastern China on marginal lands where the climatic conditions (e.g., cooler temperature) may be suitable for cultivating this crop. However, little has been done to evaluate its agronomic performance in eastern China. To address this, a three-year (2019-2021) field study was conducted to evaluate the effect of fall and spring seeding dates on seed yield and quality of sixteen spring camelina genotypes across the three different growing environments in eastern China and to select potentially high-yielding genotypes for fall or spring seeding with the suitable seeding dates for each growing environment. The study showed that fall seeding camelina between late Oct. and the third week of Nov. in eastern China, including Anyang, Qingdao, and Yangzhou, produced a sustainable and satisfactory seed and oil yield (mean across genotypes, locations, and years: 2372 and 921 kg ha-1, respectively). While spring seeding between mid- and the end of April at Qingdao showed a lower productive performance (mean seed and oil yield across genotypes: 1081 and 373 kg ha-1, respectively), it still provides an alternative option for the production of high-quality edible oil compared to other oilseed crops such as soybean [Glycine max (L.) Merr.]. Although the strong genotype x environment interactions showed, among the tested camelina genotypes, fall seeding camelina accessions of CamK9, CamC2, and CamC4 at the suitable seeding dates showed a consistently greater mean seed yield (range: 1648-3170 kg ha-1) and oil yield (747-1368 kg ha-1) in all test locations compared to other genotypes. At the suitable fall seeding dates, mean seed oil content and yield across the tested genotypes and locations were 43.5% (range: 39.0-48.9%) and 856 kg ha-1 (range: 161-1489 ha-1), respectively, with the highest mean oil content of 45.9% determined at Yangzhou (range: 43.6-48.9%) and the highest mean seed yield of 2539 kg ha-1 at Qingdao (range: 1365-3501 kg ha-1). The camelina genotypes indicated would be good candidates for large-scale cropping in eastern China and other parts of the world with similar climatic conditions.

An understanding of the visiting behavior of the pollinator on a crop and the affecting factors on gene flow would help to predict the potential gene flow risk and develop the strategies to limit gene flow. In alfalfa (Medicago sativa L.), pollination requires a tripping mechanism by a pollinator to release the pollen. This typical pollination method implies that the variations in tripping efficiency among bee species may directly or indirectly affect alfalfa pollen dispersal and gene flow. The objective of this study was to quantify and compare the difference in the formation of alfalfa pollen cloud density resulting from the two distinct bee species, honeybees (Apis mellifera L.) and bumblebees (Bombus terrestris L.), and their indirect effects on the promotion of wind-blown pollen dispersal under turbulent or non-turbulent weather conditions. In this study, pollen collection using rotorod pollen collectors under caged or uncaged alfalfa plots indicated no alfalfa pollen released from the source in the absence of insects. In contrast, pollens detected within, and beyond the alfalfa pollen source evidenced the necessity of tripping the flowers by bees for pollen release. Bee species greatly affected the visiting duration of a single alfalfa flower and the number of tripped flowers min(-1). At the current experimental scale, although worker bees of bumblebees were less abundant than honeybees, they generated a significantly greater alfalfa pollen cloud density (mean across sampling times, dates, and weather conditions: 566 pollens m(- 3 )h(-1)) than that of honeybees (416 pollens m(- 3) h(-1)), which was closely correlated with the higher number of tripped flowers by bumblebees (8.8 flowers min(-1)) relative to honeybees (3.1 flowers min(-1)). While the similar patterns of wind-blown alfalfa pollen density negatively correlated with the distance observed for the two bee species, the pollen density generated by bumblebees at the same distance from the pollen source was greater than the values by honeybees. Additionally, a directional wind effect was detected with the greater pollen density always observed at downwind sites. The developed model predicted that alfalfa pollen cloud density reached 95% reduction of maximum potential value at 31.6 m (10 pollens m(- 3 )h(-1)) from the source edge, providing the reference value to understand the wind-blown alfalfa pollen dispersal and create isolation distance. Thus, the results will be helpful to understand the factors affecting the visiting behavior of pollinating bees associated with the flowers tripping, predict the gene flow risk, and develop management strategies to mitigate gene flow in alfalfa.

Camelina [Camelina sativa (L.) Crantz] is currently gaining considerable attention as a potential oilseed feedstock for biofuel, oil and feed source, and bioproducts. Studies have shown the potential of using camelina in an intercropping system. However, there are no camelina genotypes evaluated or bred for shade tolerance. The objective of this study was to evaluate and determine the shade tolerance of sixteen spring camelina genotypes (growth stage: BBCH 103; the plants with 4–5 leaves) for intercropping systems. In this study, we simulated three different shade levels, including low (LST), medium (MST), and high shade treatments (HST; 15, 25, and 50% reduction of natural light intensity, respectively), and evaluated the photosynthetic and physiological parameters, seed production, and seed quality. The mean chlorophyll pigments, including the total chlorophyll and chlorophyll a and b across the 16 genotypes increased as shade level increased, while the chlorophyll fluorescence parameter Fv/Fm, chlorophyll a/b, leaf area, the number of silicles and branches plant−1 decreased as shade level increased. The first day of anthesis and days of flowering duration of camelina treated with shade were significantly delayed and shortened, respectively, as shade increased. The shortened lifecycle and altered flowering phenology decreased camelina seed yield. Additionally, the shade under MST and HST reduced the seed oil content and unsaturated fatty acids, but not saturated fatty acids. The dendrograms constructed using the comprehensive tolerance membership values revealed that CamK9, CamC4, and ‘SO-40’ were the relatively shade-tolerant genotypes among the 16 camelina genotypes. These camelina genotypes can grow under the shade level up to a 25% reduction in natural light intensity producing a similar seed yield and seed oil quality, indicating the potential to intercrop with maize or other small grain crops. The present study provided the baseline information on the response of camelina genotypes to different shade levels, which would help in selecting or breeding shade-tolerant genotypes.

Camelina [Camelina sativa (L.) Crantz], a member of Brassicaceae family, is a relatively new oilseed crop in China. It is a highly adaptable cool season crop species that can be grown in a wide range of environment with low input, making it potentially suitable for growing in northern China. A five-year (2010-2014) field experiment was conducted to evaluate the seed yield and quality of two camelina cultivars across three different locations in China. The study showed camelina can be cultivated successfully in a relatively short growth period of 1308-1920 degrees C d (base temperature: 4 degrees C) across a wide range of environmental conditions. Overall, camelina cv. 'Xiaoguo' displayed a satisfactory high seed yield dry matter (d.m.) (mean: 1946 kg ha(-1), range: 1274-2650 kg ha(-1)) and oil yield (mean: 598 kg ha(-1), range: 387-778 kg ha(-1)) across three different locations over the 5-year field trial, indicating the potential commercial production of camelina in northern China. The average contents of saturated, monounsaturated, and polyunsaturated fatty acids in camelina oil across locations and years varied from 10-21% (mean: 13 %), 24-38% (mean: 33 %), and 47-63% (mean: 56 %), respectively. In the present study, a variety of polyunsaturated fatty acids, particularly C22:6 (DHA) which is commonly presented in aquatic ecosystem were detected in camelina oil, making camelina an attractive oil crop for its peculiar fatty acid composition. This is the first study evaluating the agronomic performance of camelina in different growing environments in China and the relatively short growing cycle and high seed yield make camelina as a suitable oilseed crop in northern China.

New Camelina sativa genotypes have been genetically engineered (GE) to produce unique high-value chemical compounds and biofuel products. However, baseline information on predictive environmental risk assessment on this plant is urgently needed to establish guidelines for commercial large-scale production. Pollinating insects such as bees could facilitate the spread of transgenes into the ecosystem and raises ecological concerns on insectmediated gene flow. Thus determination of the potential impact of pollinating insects on C. sativa pollination and gene flow becomes important. A 4-year experiment conducted in Connecticut, USA (2017) and Yangzhou, China (2019-2021) was carried out to determine the pollination effect of different densities of honey bees (Apis mellifera L.) populations on C. sativa seed yield and assess their involvement on C. sativa pollen dispersal. Insect cages experiments with presence or absence of honey bees showed that C. sativa seed yield was not affected by a relatively low population density of honey bees (20 honey bees m(-2)). However, at a higher density of honey bee population, Camelina sativa seed yield (0.23 g plant(-1) and 73.3 g m(-2)) was statistically greater than those of the uncaged control (0.21 g plant(-1) and 68.9 g m(-2)), caged C. sativa plants without honey bees (0.20 g plant(-1) and 66.3 g m(-2)) or with 20 honey bees m-2 (0.21 g plant(-1) and 66.9 g m(-2)), although C. sativa is commonly assumed to be self-pollinated. Principle coordinate analysis (PCoA) made from SSR markers revealed that honey bee and bumble bee are able to transfer C. sativa pollen from pollen source to adjacent flowers of other species (e.g., Brassica juncea, Brassica napus) up to 10-15 m beyond the field edge, raising ecological concerns on insectmediated gene flow between adjacent C. sativa fields particularly if GE C. sativa cultivars are involved. The new information in this study will help to better understand C. sativa pollination biology, environmental risks associated with insect-mediated gene flow, and develop management strategies to reduce gene flow and facilitate coexistence between GE and non-GE C. sativa under natural agroecosystem.