Using k-NN to analyse images of diverse germination phenotypes and detect single seed germination in Miscanthus sinensis

Background: Miscanthus is a leading second generation bio-energy crop. It is mostly rhizome propagated; however, the increasing use of seed is resulting in a greater need to investigate germination. Miscanthus seed are small, germination is often poor and carried out without sterilisation; therefore, automated methods applied to germination detection must be able to cope with, for example, thresholding of small objects, low germination frequency and the presence or absence of mould. Results: Machine learning using k-NN improved the scoring of different phenotypes encountered in Miscanthus seed. The k-NN-based algorithm was effective in scoring the germination of seed images when compared with human scores of the same images. The trueness of the k-NN result was 0.69-0.7, as measured using the area under a ROC curve. When the k-NN classifier was tested on an optimised image subset of seed an area under the ROC curve of 0.89 was achieved. The method compared favourably to an established technique. Conclusions: With non-ideal seed images that included mould and broken seed the k-NN classifier was less consistent with human assessments. The most accurate assessment of germination with which to train classifiers is difficult to determine but the k-NN classifier provided an impartial consistent measurement of this important trait. It was more reproducible than the existing human scoring methods and was demonstrated to give a high degree of trueness to the human score

Using a Taguchi DOE to investigate factors and interactions affecting germination in Miscanthus sinensis

The Miscanthus genus of perennial grasses is grown for bioenergy and biorenewable feedstocks. Most Miscanthus crop is M × giganteus which is rhizome propagated and therefore difficult to multiply at large scale. Seed-based propagation of new hybrids is being developed, but Miscanthus is difficult to establish from seed especially in the field. Miscanthus is often grown on marginal land adding to the challenge of successfully establishing the crop. Improved understanding of the limits and biology of germination in Miscanthus species is needed. Seed germination is affected by physical and chemical factors that impact germination differently depending on level of exposure. In this investigation of Miscanthus germination, four hormones plus water stress were investigated and the range over which these factors affect germination was determined. An efficient Taguchi experimental design was used to assess the five factors in combination with the effects of light and seed priming. This determined an example of a set of optimum conditions for Miscanthus germination and demonstrated how this could change based on fixing one condition. The experiment showed how environmental stress impacted germination and how treatments such as gibberellic acid could be used to mitigate stress

Detection and Classification of Floating Plastic Litter Using a Vessel-Mounted Video Camera and Deep Learning

Marine plastic pollution is a major environmental concern, with significant ecological, economic, public health and aesthetic consequences. Despite this, the quantity and distribution of marine plastics is poorly understood. Better understanding of the global abundance and distribution of marine plastic debris is vital for global mitigation and policy. Remote sensing methods could provide substantial data to overcome this issue. However, developments have been hampered by the limited availability of in situ data, which are necessary for development and validation of remote sensing methods. Current in situ methods of floating macroplastics (size greater than 1 cm) are usually conducted through human visual surveys, often being costly, time-intensive and limited in coverage. To overcome this issue, we present a novel approach to collecting in situ data using a trained object-detection algorithm to detect and quantify marine macroplastics from video footage taken from vessel-mounted general consumer cameras. Our model was able to successfully detect the presence or absence of plastics from real-world footage with an accuracy of 95.2% without the need to pre-screen the images for horizon or other landscape features, making it highly portable to other environmental conditions. Additionally, the model was able to differentiate between plastic object types with a Mean Average Precision of 68% and an F1-Score of 0.64. Further analysis suggests that a way to improve the separation among object types using only object detection might be through increasing the proportion of the image area covered by the plastic object. Overall, these results demonstrate how low-cost vessel-mounted cameras combined with machine learning have the potential to provide substantial harmonised in situ data of global macroplastic abundance and distribution

Allelopathic and intraspecific growth competition effects establishment of direct sown Miscanthus

High yielding perennial crops are being developed as a sustainable feedstock for renewable energy and bioproducts. Miscanthus is a leading biomass crop, but most plantations comprise a sterile hybrid Miscanthus × giganteus that is clonally propagated. To develop new varieties across large areas, rhizome cloning is inefficient, time consuming and expensive. Alternative approaches use seed, and in temperate regions, this has been successfully applied by raising seedlings as plug plants in glasshouses before transfer to the field. Direct sowing has yet to be proven commercially viable because poor germination has resulted in inconsistent stand establishment. Oversowing using seed clusters is a common approach to improve the establishment of crops and it was hypothesized that such an approach will improve uniformity of density in early Miscanthus stands and thereby improve yield. Sowing multiple seeds creates potential for new interactions, and we identified at least two inhibitory mechanisms related to seed numbers. Germinating seed produced allelopathic effects on nearby seed thereby inhibiting plant growth. The inhibitory effect of Miscanthus seed on germination percentages was related to seed number within clusters. An extract from germinating Miscanthus seed inhibited the germination of Miscanthus seed. The extract was analysed by HPLC, which identified a complex mixture including several known allelopathic compounds including proanthocyanidins and vanillic acid. There was also evidence of root competition in soil in a controlled environment experiment. When the experiment on competition was replicated at field scale, the establishment rates were much lower and there was evidence of shoot competition. We conclude that the numbers of seed required to ensure an acceptable level of establishment in the field may be economically impractical until other agronomic techniques are included either to reduce the inhibitory effects of higher seed numbers or to reduce oversowing rates

Optimizing seed-based Miscanthus plug plant production with supplemental heat and light, compost type and volume

To help meet greenhouse gas mitigation targets perennial biomass crops will need to be planted at large scales and at a much greater pace over the coming decades. Miscanthus is a leading biomass crop but rapid upscaling is technically challenging due to costly and time-consuming clonal propagation. Seed-based hybrids are considered a viable route to rapid upscaling, but direct sowing has not been found feasible under temperate climate conditions due to high thermal requirements for germination and slow early plant development compared with larger seeded annuals. Seed-based plug plants, initially propagated in greenhouses, provide a suitable route to improve field establishment. Here, we describe an input optimization experiment for seeded Miscanthus plugs raised for spring planting in a naturally lit greenhouse with the following treatments: supplemental heat to maintain a minimum of 15°C, supplemental predawn light from modern LEDs at PPFD 300–400 μmol m−2 s−1, two proprietary types of compost (known as 50k and 70k), and two compost volumes (35 and 15 cm3). Our results showed that variations in all four factors had significant effects on above- and belowground biomass: (i) supplemental heat increased root-to-shoot ratio, (ii) supplemental light increased total biomass and root-to-shoot ratio, (iii) compost type affected total biomass and (iv) compost volume was positively correlated with total biomass and stem base diameter. No factor had a significant effect on axillary shoot formation. We recommend nurseries in the United Kingdom use LEDs as predawn supplemental light but no supplemental heat, compost that has both good water-holding capacity and aeration, and a larger compost volume, which provided optimized cost-plug resilience for spring-sown, seed-based Miscanthus plug production

Optimizing seed-based Miscanthus plug plant production with supplemental heat and light, compost type and volume

To help meet greenhouse gas mitigation targets perennial biomass crops will need to be planted at large scales and at a much greater pace over the coming decades. Miscanthus is a leading biomass crop but rapid upscaling is technically challenging due to costly and time-consuming clonal propagation. Seed-based hybrids are considered a viable route to rapid upscaling, but direct sowing has not been found feasible under temperate climate conditions due to high thermal requirements for germination and slow early plant development compared with larger seeded annuals. Seed-based plug plants, initially propagated in greenhouses, provide a suitable route to improve field establishment. Here, we describe an input optimization experiment for seeded Miscanthus plugs raised for spring planting in a naturally lit greenhouse with the following treatments: supplemental heat to maintain a minimum of 15°C, supplemental predawn light from modern LEDs at PPFD 300–400 μmol m−2 s−1, two proprietary types of compost (known as 50k and 70k), and two compost volumes (35 and 15 cm3). Our results showed that variations in all four factors had significant effects on above- and belowground biomass: (i) supplemental heat increased root-to-shoot ratio, (ii) supplemental light increased total biomass and root-to-shoot ratio, (iii) compost type affected total biomass and (iv) compost volume was positively correlated with total biomass and stem base diameter. No factor had a significant effect on axillary shoot formation. We recommend nurseries in the United Kingdom use LEDs as predawn supplemental light but no supplemental heat, compost that has both good water-holding capacity and aeration, and a larger compost volume, which provided optimized cost-plug resilience for spring-sown, seed-based Miscanthus plug production

Assessing seed priming, sowing date, and mulch film to improve the germination and survival of direct-sown Miscanthus sinensis in the United Kingdom

Direct sowing of Miscanthus seed could lower crop establishment costs, and increase the rate of grower uptake and biomass supply for the emerging bio-economy. A replicated field trial was conducted at two contrasting UK sites: Aberystwyth (ABR) in mid-Wales and Blankney (BLK) in Lincolnshire. These sites encompass the west–east meteorological gradient in the United Kingdom where the growing season at ABR is cooler and wetter while BLK is warmer and drier. Primed and unprimed Miscanthus sinensis seeds were sown directly onto the soil surface with and without a clear biodegradable mulch film, at nine dates interspersed from May to October. Average daily mean soil surface temperatures measured over the first 2 months after sowing under the mulch film were higher than control plots (2.7°C ABR and 4.2°C BLK). At both sites, the film covering also affected soil volumetric moisture relative to uncovered control plots (−3% ABR and 8% BLK), demonstrating the negative impact of mulch film when sowing on dry soil. Over nine sowings, seed germination at ABR under film varied between −28% and +18% of germination under control conditions. Seedlings from the first three sowings at both sites under film had sufficient physiological maturity to survive the first winter period. At BLK, mulch film significantly increased tiller count and height in both the first and second years after sowing. At ABR, where temperatures were lower, film covering significantly increased tiller height but not count. Water priming had no significant effect on seed viability or germination in the field tests. Base temperatures for germination of primed and unprimed seeds on a thermal gradient plate were 7.0°C and 5.7°C, respectively, with a ± 1.7°C confidence interval. Based on our results for M. sinensis in the United Kingdom, we recommend the sowing of unprimed seed in May under film and only when the soil is moist

Developing Miscanthus seed plug establishment protocols with mulch film for commercial upscaling

High-yielding crops with C4 photosynthesis arising in tropical climates are being bred for, and increasingly grown in, temperate climates. Miscanthus, a C4 from Eastern Asia is a leading perennial biomass crop, but commercial deployment is limited by low temperatures in Northern Europe, low clonal multiplication rates and slow establishment rates requiring up to 4 years to reach mature yields. While new seeded hybrids have multiplication rates >2000, direct field sown seed has proven impractical. Protocols for safe establishment of seeded hybrids require that seedlings are raised in the glasshouse in compost filled modules (also known as ‘plugs’) which are transplanted into the field in springtime. To protect seedlings from damage from late frosts, drought and grazing and to increase temperature stimulating growth rates, plug plants were covered with oxo-degradable plastic mulch film designed for maize. At two sites in the UK, this mulch film significantly reduced plant losses at transplanting and overwintering, increased stem heights and shoot counts, and reduced the time to mature yield from 4 to 3 years (p < 0.01). However, the breakdown products of oxo-degradable mulch films contribute to microplastics in the soil. Therefore, further mulch film experiments were conducted with bio-derived plastics which are bio-degradable in soil at extruded thicknesses of 10, 18 and 30 microns. The 10 micron film combined sufficient strength for machine laying and worked as well as oxo-degradable film on de-risking establishment. Halving the mulch film widths covering 1 row rather than 2 reduced the amount of plastic by 25%. Commercial plug-to-field protocols are built on results from the plot experiments and field-scale plantings over multiple years and locations and are ready for future upscaling of biomass production from seed-based Miscanthus hybrids

UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using a VIs time series, and predicted yield using a peak descriptor derived from a VIs time series with 2.3 Mg DM ha−1 of the root mean square error (RMSE). The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production

Drone imagery and deep learning for mapping the density of wild Pacific oysters to manage their expansion into protected areas

The recent expansion of wild Pacific oysters already had negative repercussions on sites in Europe and has raised further concerns over their potential harmful impact on the balance of biomes within protected areas. Monitoring their colonisation, especially at early stages, has become an urgent ecological issue. Current efforts to monitor wild Pacific oysters rely on “walk-over” surveys that are highly laborious and often limited to specific areas of easy access. Remotely Piloted Aircraft Systems (RPAS), commonly known as drones, can provide an effective tool for surveying complex terrains and detect Pacific oysters. This study provides a novel workflow for automated detection, counting and mapping of individual Pacific oysters to estimate their density per square meter by using Convolutional Neural Networks (CNNs) applied to drone imagery. Drone photos were collected at low tides and altitudes of approximately 10 m across a variety of cases of rocky shore and mudflats scenarios. Using object detection, we compared how different Convolutional Neural Networks (CNNs) architectures including YOLOv5s, YOLOv5m, TPH-YOLOv5 and FR-CNN performed in the detection of Pacific oysters over the surveyed areas. We report the precision of our model at 88% with a difference in performance of 1% across the two sites. The workflow presented in this work proposes the use of grid maps to visualize the density of Pacific oysters per square meter towards ecological management and the creation of time series to identify trends