Comparative secretome analysis of Striga and Cuscuta species identifies candidate virulence factors for two evolutionarily independent parasitic plant lineages.

BACKGROUND: Many parasitic plants of the genera Striga and Cuscuta inflict huge agricultural damage worldwide. To form and maintain a connection with a host plant, parasitic plants deploy virulence factors (VFs) that interact with host biology. They possess a secretome that represents the complement of proteins secreted from cells and like other plant parasites such as fungi, bacteria or nematodes, some secreted proteins represent VFs crucial to successful host colonisation. Understanding the genome-wide complement of putative secreted proteins from parasitic plants, and their expression during host invasion, will advance understanding of virulence mechanisms used by parasitic plants to suppress/evade host immune responses and to establish and maintain a parasite-host interaction. RESULTS: We conducted a comparative analysis of the secretomes of root (Striga spp.) and shoot (Cuscuta spp.) parasitic plants, to enable prediction of candidate VFs. Using orthogroup clustering and protein domain analyses we identified gene families/functional annotations common to both Striga and Cuscuta species that were not present in their closest non-parasitic relatives (e.g. strictosidine synthase like enzymes), or specific to either the Striga or Cuscuta secretomes. For example, Striga secretomes were strongly associated with 'PAR1' protein domains. These were rare in the Cuscuta secretomes but an abundance of 'GMC oxidoreductase' domains were found, that were not present in the Striga secretomes. We then conducted transcriptional profiling of genes encoding putatively secreted proteins for the most agriculturally damaging root parasitic weed of cereals, S. hermonthica. A significant portion of the Striga-specific secretome set was differentially expressed during parasitism, which we probed further to identify genes following a 'wave-like' expression pattern peaking in the early penetration stage of infection. We identified 39 genes encoding putative VFs with functions such as cell wall modification, immune suppression, protease, kinase, or peroxidase activities, that are excellent candidates for future functional studies. CONCLUSIONS: Our study represents a comprehensive secretome analysis among parasitic plants and revealed both similarities and differences in candidate VFs between Striga and Cuscuta species. This knowledge is crucial for the development of new management strategies and delaying the evolution of virulence in parasitic weeds.

Glutathione S-transferase activity facilitates rice tolerance to the barnyard grass root exudate DIMBOA.

BACKGROUND: In paddy fields, the noxious weed barnyard grass secretes 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one (DIMBOA) to interfere with rice growth. Rice is unable to synthesize DIMBOA. Rice cultivars with high or low levels of allelopathy may respond differently to DIMBOA. RESULTS: In this study, we found that low concentrations of DIMBOA (≤ 0.06 mM) promoted seedling growth in allelopathic rice PI312777, while DIMBOA (≤ 0.08 mM) had no significant influence on the nonallelopathic rice Lemont. DIMBOA treatment caused changes in the expression of a large number of glutathione S-transferase (GST) proteins, which resulting in enrichment of the glutathione metabolic pathway. This pathway facilitates plant detoxification of heterologous substances. The basal levels of GST activity in Lemont were significantly higher than those in PI312777, while GST activity in PI312777 was slightly induced by increasing DIMBOA concentrations. Overexpression of GST genes (Os09g0367700 and Os01g0949800) in these two cultivars enhanced rice resistance to DIMBOA. CONCLUSIONS: Taken together, our results indicated that different rice accessions with different levels of allelopathy have variable tolerance to DIMBOA. Lemont had higher GST activity, which helped it tolerate DIMBOA, while PI312777 had lower GST activity that was more inducible. The enhancement of GST expression facilitates rice tolerance to DIMBOA toxins from barnyard grass root exudates.

Allelopathic effect of the methanol extract of the weed species-red sorrel (Rumex acetosella L.) on the growth, phytohormone content and antioxidant activity of the cover crop - white clover (Trifolium repens L.).

Allelopathy is a biological process in which one organism releases biochemicals that affect the growth and development of other organisms. The current investigation sought to determine the allelopathic effect of Rumex acetosella on white clover (Trifolium repens) growth and development by using its shoot extract (lower IC50 value) as a foliar treatment. Here, different concentrations (25, 50, 100, and 200 g/L) of shoot extract from Rumex acetosella were used as treatments. With increasing concentrations of shoot extract, the plant growth parameters, chlorophyll and total protein content of Trifolium repens decreased. On the other hand, ROS, such as O2.- and H2O2, and antioxidant enzymes, including SOD, CAT, and POD, increased with increasing shoot extract concentration. A phytohormonal study indicated that increased treatment concentrations increased ABA and SA levels while JA levels were reduced. For the identification of allelochemicals, liquid‒liquid extraction, thin-layer chromatography, and open-column chromatography were conducted using R. acetosella shoot extracts, followed by a seed bioassay on the separated layer. A lower IC50 value was obtained through GC/MS analysis. gammaSitosterol was identified as the most abundant component. The shoot extract of Rumex acetosella has strong allelochemical properties that may significantly impede the growth and development of Trifolium repens. This approach could help to understand the competitive abilities of this weed species and in further research provide an alternate weed management strategy.

Introgression from local cultivars is a driver of agricultural adaptation in Argentinian weedy rice.

Weedy rice, a pervasive and troublesome weed found across the globe, has often evolved through fertilization of rice cultivars with little importance of crop-weed gene flow. In Argentina, weedy rice has been reported as an important constraint since the early 1970s, and, in the last few years, strains with herbicide-resistance are suspected to evolve. Despite their importance, the origin and genetic composition of Argentinian weedy rice as well its adaptation to agricultural environments has not been explored so far. To study this, we conducted genotyping-by-sequencing on samples of Argentinian weedy and cultivated rice and compared them with published data from weedy, cultivated and wild rice accessions distributed worldwide. In addition, we conducted a phenotypic characterization for weedy-related traits, a herbicide resistance screening and genotyped accessions for known mutations in the acetolactate synthase (ALS) gene, which confers herbicide resistance. Our results revealed large phenotypic variability in Argentinian weedy rice. Most strains were resistant to ALS-inhibiting herbicides with a high frequency of the ALS mutation (A122T) present in Argentinian rice cultivars. Argentinian cultivars belonged to the three major genetic groups of rice: japonica, indica and aus while weeds were mostly aus or aus-indica admixed, resembling weedy rice strains from the Southern Cone region. Phylogenetic analysis supports a single origin for aus-like South American weeds, likely as seed contaminants from the United States, and then admixture with local indica cultivars. Our findings demonstrate that crop to weed introgression can facilitate rapid adaptation to agriculture environments.

A Critical Review of Conventional and Modern Approaches to Develop Herbicide-Resistance in Rice.

Together with rice, weeds strive for nutrients and space in farmland, resulting in reduced rice yield and quality. Planting herbicide-resistant rice varieties is one of the effective ways to control weeds. In recent years, a series of breakthroughs have been made to generate herbicide-resistant germplasm, especially the emergence of biotechnological tools such as gene editing, which provides an inherent advantage for the knock-out or knock-in of the desired genes. In order to develop herbicide-resistant rice germplasm resources, gene manipulation has been conducted to enhance the herbicide tolerance of rice varieties through the utilization of techniques such as physical and chemical mutagenesis, as well as genome editing. Based on the current research and persisting problems in rice paddy fields, research on the generation of herbicide-resistant rice still needs to explore genetic mechanisms, stacking multiple resistant genes in a single genotype, and transgene-free genome editing using the CRISPR system. Current rapidly developing gene editing technologies can be used to mutate herbicide target genes, enabling targeted genes to maintain their biological functions, and reducing the binding ability of target gene encoded proteins to corresponding herbicides, ultimately resulting in herbicide-resistant crops. In this review article, we have summarized the utilization of conventional and modern approaches to develop herbicide-resistant cultivars in rice as an effective strategy for weed control in paddy fields, and discussed the technology and research directions for creating herbicide-resistant rice in the future.

Seed pretreatment with brassinosteroids stimulates sunflower immunity against parasitic weed (Orobanche cumana) infection.

Broomrape (Orobanche cumana) negatively affects sunflower, causing severe yield losses, and thus, there is a need to control O. cumana infestation. Brassinosteroids (BRs) play key roles in plant growth and provide resilience to weed infection. This study aims to evaluate the mechanisms by which BRs ameliorate O. cumana infection in sunflower (Helianthus annuus). Seeds were pretreated with BRs (1, 10, and 100 nM) and O. cumana inoculation for 4 weeks under soil conditions. O. cumana infection significantly reduced plant growth traits, photosynthesis, endogenous BRs and regulated the plant defence (POX, GST), BRs signalling (BAK1, BSK1 to BSK4) and synthesis (BRI1, BR6OX2) genes. O. cumana also elevated the levels of malondialdehyde (MDA), hydroxyl radical (OH-), hydrogen peroxide (H2O2) and superoxide (O2 •-) in leaves/roots by 77/112, 63/103, 56/97 and 54/89%, as well as caused ultrastructural cellular damages in both leaves and roots. In response, plants activated a few enzymes, superoxide dismutase (SOD), peroxidase (POD) and reduced glutathione but were unable to stimulate the activity of ascorbate peroxidase (APX) and catalase (CAT) enzymes. The addition of BRs (especially at 10 nM) notably recovered the ultrastructural cellular damages, lowered the production of oxidative stress, activated the key enzymatic antioxidants and induced the phenolic and lignin contents. The downregulation in the particular genes by BRs is attributed to the increased resilience of sunflower via a susceptible reaction. In a nutshell, BRs notably enhanced the sunflower resistance to O. cumana infection by escalating the plant immunity responses, inducing systemic acquired resistance, reducing oxidative or cellular damages, and modulating the expression of BR synthesis or signalling genes.

Monitoring of parasite Orobanche cumana using Vis-NIR hyperspectral imaging combining with physio-biochemical parameters on host crop Helianthus annuus.

KEY MESSAGE: This study provided a non-destructive detection method with Vis-NIR hyperspectral imaging combining with physio-biochemical parameters in Helianthus annuus in response to Orobanche cumana infection that took insights into the monitoring of sunflower weed. Sunflower broomrape (Orobanche cumana Wallr.) is an obligate weed that attaches to the host roots of sunflower (Helianthus annuus L.) leading to a significant reduction in yield worldwide. The emergence of O. cumana shoots after its underground life-cycle causes irreversible damage to the crop. In this study, a fast visual, non-invasive and precise method for monitoring changes in spectral characteristics using visible and near-infrared (Vis-NIR) hyperspectral imaging (HSI) was developed. By combining the bands sensitive to antioxidant enzymes (SOD, GR), non-antioxidant enzymes (GSH, GSH + GSSG), MDA, ROS (O2-, OH-), PAL, and PPO activities obtained from the host leaves, we sought to establish an accurate means of assessing these changes and conducted imaging acquisition using hyperspectral cameras from both infested and non-infested sunflower cultivars, followed by physio-biochemical parameters measurement as well as analyzed the expression of defense related genes. Extreme learning machine (ELM) and convolutional neural network (CNN) models using 3-band images were built to classify infected or non-infected plants in three sunflower cultivars, achieving accuracies of 95.83% and 95.83% for the discrimination of infestation as well as 97.92% and 95.83% of varieties, respectively, indicating the potential of multi-spectral imaging systems for early detection of O. cumana in weed management.

Crofton weed derived isomers of ageraphorone as potent antifeedant against Plutella xylostella (L.).

Global agricultural production is significantly hampered by insect pests, and the demand for natural pragmatic pesticides with environmental concern remains unfulfilled. Ageratina adenophora (Spreng.) also known as Crofton weed, is an invasive perennial herbaceous plant that is known to possess multiple bioactive compounds. In our study, two isomers of ageraphorone metabolites i.e, 10 Hα-9-oxo-ageraphorone (10HA) and 10 Hß-9-oxo-ageraphorone (10HB), were identified from Crofton weed, exhibiting potent antifeedant and larvicidal activities against Plutella xylostella. For antifeedant activity, the median effective concentration (EC50) values for 10HA and 10HB in the choice method were 2279 mg/L and 3233 mg/L, respectively, and for the no choice method, EC50 values were 1721 mg/L and 2394 mg/L, respectively. For larvicidal activity, lethal concentration (LC50) values for 10HA and 10HB were 2421 mg/L and 4109 mg/L at 48 h and 2101 mg/L and 3550 mg/L at 72 h. Furthermore, both in- vivo and in-vitro studies revealed that the isomers 10HA and 10HB exhibited potent detoxifying enzymes inhibition activity such as carboxylesterase and glutathione S-transferases. Molecular docking and MD simulation analysis provide insight into the possible interaction between isomers of ageraphorone metabolites and Carboxylic Ester Hydrolase protein (Gene: pxCCE016b) of P. xylostella, which led to a finding that CarEH protein plays a significant role in the detoxification of the two compounds in P. xylostella. Finally, our findings show that the primary enzymes undergoing inhibition by isomers of ageraphorone metabolites, causing toxicity in insects, are Carboxylesterase and glutathione S-transferase.

Gene flow and spontaneous mutations are responsible for imidazolinone herbicide-resistant weedy rice (Oryza sativa L.).

For more than two decades, weedy rice (Oryza sativa L.) has been controlled in rice fields by using imidazolinone (IMI) herbicide-resistant rice technology (Clearfield®). Outcrossing in weedy rice populations and spontaneous mutations are potential problems with herbicide-resistant crop management technologies, such as the IMI-resistant rice. The aim of this study was to characterize the mechanism of IMI herbicide resistance in weedy rice through dose-response bioassay study and evaluating amino acid substitutions in acetolactate synthase (ALS) protein. A total of 118 suspected IMI-resistant weedy rice samples, which survived in the field after an IMI herbicide application, were collected at harvest time from Türkiye in 2020 and 2021. Single-dose imazamox application experiment revealed that 38 plants survived herbicide treatment. The imazamox resistance of the surviving plants was confirmed by dose-response experiment. ALS gene region underwent a sanger DNA partial sequencing. No substitution was found in 10 samples, however, amino acid substitutions were found in 26 samples with S563N, one sample with S653T, and one sample with E630D. The S653N point is the same substitution point that serves as the origin of resistance for the Clearfield® rice varieties that are commonly cultivated in the region. It has been hypothesized that the gene flow from IMI-resistant rice may be the cause of resistance in the IMI resistant weedy rice samples with S653N. The other substitution, S653T, were considered spontaneous mutation to IMI resistance. Interestingly, the S653T mutation was detected for the first time in weedy rice. The mechanism of resistance of 10 resistant weedy rice was not confirmed in this study, however, it may be a non-target resistance or another mutation point in target site, but evidently, they did not acquire resistance by gene flow from IMI-resistant rice. It has been concluded that the effectiveness of IMI-resistant rice technology in controlling weedy rice has drastically decreased due to possible gene flow, spontaneous mutation and non-target resistance. In addition to cultural controls like clean seed, clean machinery and crop rotation, other herbicide-tolerant rice systems such as Provisia® and Roxy-RPS® rice are needed to create a diverse weedy rice management ensemble available for rice production and move towards sustainable rice farming.

Cyperus rotundus L.: Invasive weed plant with insecticidal potential against Aphis craccivora Koch and Planococcus lilacinus (Cockerell).

Cyperus rotundus L. is a widely distributed invasive weed plant with vast traditional medicinal uses. Herein, the methanolic root extract of C. rotundus and its fractions (n-hexane, chloroform, n-butanol, and aqueous) were evaluated for insecticidal activity against nymphs of Aphis craccivora Koch and crawlers of Planococcus lilacinus (Cockerell) to find promising lead (s). In contact topical assay, among extract/fractions, n-hexane fraction exhibited more toxicity against A. craccivora (LD50 = 1.12 µg/insect) and P. lilacinus (LD50 = 0.94 µg/insect). The chemical analysis of n-hexane fraction revealed a volatile composition similar to that of the essential oil (EO) of C. rotundus roots. Hence, EO was extracted using water and deep eutectic solvents (DESs) as cosolvent, which revealed enhancement in EO yield (from 0.28 to 0.46% w/w) on implementing DESs. A total of 35 diverse volatile metabolites were identified in all EO samples, accounting for 85.0 to 91.8% of chemical composition, having cyperotundone, cyperene mustakone, isolongifolen-5-one, boronia butenal as major constituents. The EO obtained with DES-7 [choline chloride: ethylene glycol (1:4)] and DES-6 [choline chloride: lactic acid (1:3)] were found effective against A. craccivora (LD50 = 0.62-0.87 µg/insect) and P. lilacinus (LD50= 0.59-0.67 µg/insect) after 96 h. NMR analysis of EO revealed cyperotundone as a major compound, which was isolated along with cyperene and cyperene epoxide. All the molecules were found effective against P. lilacinus, whereas against A. craccivora cyperotundone, cyperene and cyperene epoxide showed promising toxicity (LD50 = 0.74-0.86 µg/insect). Extract/fractions, EO, and isolated molecules showed a significant reproductive inhibition rate of A. craccivora at higher concentrations. All the tested concentrations of cyperotundone showed significant inhibition of acetylcholinesterase (AChE) and glutathione-S-transferase (GST) in A. craccivora and P. lilacinus. Based upon the present study, C. rotundus can be recommended to control targeted insects in the greenhouse/field conditions after performing bio-efficacy and phytotoxicity studies.

An Asp376Glu substitution and P450s-involved metabolism endow resistance to ALS inhibitors in an Ammannia auriculata Willd. Population.

Ammannia auriculata Willd. is a noxious broadleaf weed, commonly infesting rice ecosystems across southern China. A putative resistant A. auriculata population (AHSC-5) was sampled from a rice field of Anhui Province, where bensulfuron-methyl (BM) was unable to control its occurrence. This study aimed to determine the sensitivities of the AHSC-5 population to common-use herbicides, and to investigate the underlying resistance mechanisms. The bioassays showed that the AHSC-5 population was 138.1-fold resistant to BM, compared with the susceptible population (JSGL-1). Pretreatment of malathion reduced the resistance index to 19.5. ALS sequencing revealed an Asp376Glu substitution in the AHSC-5 population, and in vitro ALS activity assays found that 50% activity inhibition (I50) of BM in AHSC-5 was 75.4 times higher than that of JSGL-1. Moreover, the AHSC-5 population displayed cross-resistance to pyrazosulfuron-ethyl (10.6-fold), bispyribac­sodium (3.6-fold), and imazethapyr (2.2-fold), and was in the process of evolving multiple resistance to synthetic auxin herbicides fluroxypyr (2.3-fold) and florpyrauxifen-benzyl (3.1-fold). This study proved the BM resistance in A. auriculata caused by the Asp376Glu mutation and P450-regulated metabolism. This multi-resistant population can still be controlled by penoxsulam, MCPA, bentazone, and carfentrazone-ethyl, which aids in developing targeted and effective weed management strategies.

Low-concentration repeated exposure and high-concentration single exposure of cyanamide suppressed the growth of redroot pigweed in the alfalfa field.

The inclination toward natural products has led to the onset of the discovery of new bioactive metabolites that could be targeted for specific therapeutic or agronomic applications. Despite increasing knowledge coming to light of plant-derived materials as leads for new herbicides, relatively little is known about the mode of action on herbicide-resistant weeds. Cyanamide (CA) is a naturally occurring herbicide synthesized by hairy vetch (Vicia villosa Roth.). However, it has not been experimentally verified whether CA suppresses target plants via sustained discharge at low concentrations, as is often the case with most plant-derived materials. This study aimed to detect the toxicity and the mode of action of CA to alfalfa (Medicago sativa L.) and redroot pigweed (Amaranthus retroflexus L.). The toxicity of CA toward the alfalfa and redroot pigweed by three different exposure patterns was compared: low-concentration repeated exposure with 0.3 g/L CA (LRE), high-concentration single exposure with 1.2 g/L CA (HSE), and distilled water spray as control. The results showed that CA had a stronger inhibitory effect on redroot pigweed growth compared to alfalfa under both LRE and HSE exposure modes, with leaves gradually turning yellow and finally wilting. Beyond that, field trials were conducted to corroborate the toxicity of CA to alfalfa and redroot pigweed. The results have also shown that CA could inhibit the growth of redroot pigweed without significant adverse effects on alfalfa. The outcomes concerning electrolyte permeability, root activity, and malondialdehyde (MDA) content indicated that CA suppressed the growth of redroot pigweed by interfering with the structure of the cell membrane and impacting cellular osmotic potential. CA could destroy the cell membrane structure to inhibit the growth of the redroot pigweed by both LRE and HSE exposure modes, which provides a theoretical basis for preventing and controlling redroot pigweed in alfalfa fields.

Synthesis and Evaluation of New Phytotoxic Fluorinated Chalcones as Photosystem II and Seedling Growth Inhibitors.

The development of novel phytotoxic compounds has been an important aim of weed control research. In this study, we synthesized fluorinated chalcone derivatives featuring both electron-donating and electron-withdrawing groups. These compounds were evaluated both as inhibitors of the photosystem II (PSII) electron chain as well as inhibitors of the germination and seedling growth of Amaranthus plants. Chlorophyll a (Chl a) fluorescence assay was employed to evaluate their effects on PSII, while germination experiments were conducted to assess their impact on germination and seedling development. The results revealed promising herbicidal activity for (E)-3-(4-bromophenyl)-1-(4-fluorophenyl)prop-2-en-1-one (7 a) and (E)-1-(4-fluorophenyl)-3-phenylprop-2-en-1-one (7 e). Compounds 7 a and 7 e exhibited a reduction in Chl a parameters associated with performance indexes and electron transport per reaction center. This reduction suggests a decrease in PSII activity, attributed to the blockage of electron flow at the quinone pool. Molecular docking analyses of chalcone derivatives with the D1 protein of PSII revealed a stable binding conformation, wherein the carbonyl and fluorine groups interacted with Phe265 and His215 residues, respectively. Additionally, at a concentration of 100 µM, compound 7 e demonstrated pre- and post-emergent herbicidal activity, resulting in a reduction of the seed germination index, radicle and hypocotyl lengths of Amaranthus weeds.

Variation in Pathogenicity and Subsequent Production of Sclerotia of Sclerotinia sclerotiorum Isolates in Different Cover Crops, Flower Strips, and Weeds.

Cover crops and flower strips are used in agricultural fields as part of integrated pest management strategies. However, their potential as secondary hosts of soilborne pathogens such as Sclerotinia sclerotiorum in oilseed rape cultivation is not fully comprehended. In the current study, we evaluated the effect of pathogen virulence on the development of Sclerotinia stem/leaf rot and sclerotia production in 33 plant species from 11 botanical families using two S. sclerotiorum isolates. Furthermore, the effect of sclerotial size on carpogenic germination was studied. Results showed that the pathogen's virulence significantly affected the occurrence and development of Sclerotinia stem/leaf rot and the subsequent production of sclerotia. Among all plant species tested, 26 were more susceptible to the highly aggressive S. sclerotiorum isolate, which produced more and bigger sclerotia in 17 species than the less aggressive isolate. Moreover, a stronger positive correlation was found between the relative lesion length of plants inoculated with the highly aggressive isolate and the number of sclerotia produced by this isolate (Spearman's rank correlation coefficient [rs] = 0.572; P = 0.004). Additionally, we found that larger and heavier sclerotia produced stipes and apothecia earlier and at a greater rate than smaller ones. The heavyweight class had the highest carpogenic germination rate (82.4%), followed by the average (67.2%) and lightweight classes (59.5%). Our findings highlight the need for further investigation into the potential risks associated with cover crops, weeds, and flower strips as secondary hosts of soilborne pathogens in agricultural fields.

A pilot-scale assessment of five common weeds in the sustainable treatment of sewage utilizing SHEFROL®, with prospects of a closed-loop biorefinery.

Relative efficacy of five common weeds-of the kind that are either rooted in soil or which freely float over water-was assessed in rapid, effective and sustainable treatment of sewage at pilot plant scale in the recently developed and patented SHEFROL® bioreactors. The plants were utilized in a unit of capacity 12,000 liters/day (LPD) which, after two years of use, was enlarged to handle 40,000 LPD of sewage. It was then further expanded after an year to treat 57,000 LPD. All the five weeds, of which none has previously been tested in a pilot-scale SHEFROL, were able to foster highly efficient primary treatment (in terms of suspended and total solids) and secondary treatment (in terms of BOD and COD) to levels exceeding 85% in most cases. Additionally, the weeds also helped in achieving significant tertiary treatment. At different hydraulic retention times, and at steady state, the five weeds achieved treatment of BOD, COD, suspended solids, nitrogen, phosphorous, copper, nickel, zinc, and manganese in the ranges, 80-95, 79-91, 82-95, 61-71, 51-73, 37-43, 30-38, 39-47, and 27-35%, respectively. It all occurred in a single process step and without the use of any machine or chemical. This made the system not only simple and inexpensive to install but also to maintain. Over continuous long-term operation for four years, the system was seen to be very robust as it was able to handle wide variations in the volumes and characteristics of sewage, as well as absorb shock loads without compromising the reactor performance. The sustainability of the system can be further enhanced by upgrading it to a circular biorefinery. Energy sources in the form of volatile fatty acids (VFAs) can be extracted from the weeds removed from SHEFROL and then the weeds can be converted into organic fertilizer using high-rate vermireactors recently developed by the authors.

A novel and inexpensive, yet very efficient sewage treatment system is presented.The versatility and robustness of the system has been assessed at pilot plant scale for several years.The long-term continuous studies establish the efficacy of five common weeds­not hitherto explored at pilot plant level­which can serve as the main bioagent(s) in the sewage treatment system.The system has the potential of being transformed in to a closed-loop-no-waste biorefinery.

YOLOv8 Model for Weed Detection in Wheat Fields Based on a Visual Converter and Multi-Scale Feature Fusion.

Accurate weed detection is essential for the precise control of weeds in wheat fields, but weeds and wheat are sheltered from each other, and there is no clear size specification, making it difficult to accurately detect weeds in wheat. To achieve the precise identification of weeds, wheat weed datasets were constructed, and a wheat field weed detection model, YOLOv8-MBM, based on improved YOLOv8s, was proposed. In this study, a lightweight visual converter (MobileViTv3) was introduced into the C2f module to enhance the detection accuracy of the model by integrating input, local (CNN), and global (ViT) features. Secondly, a bidirectional feature pyramid network (BiFPN) was introduced to enhance the performance of multi-scale feature fusion. Furthermore, to address the weak generalization and slow convergence speed of the CIoU loss function for detection tasks, the bounding box regression loss function (MPDIOU) was used instead of the CIoU loss function to improve the convergence speed of the model and further enhance the detection performance. Finally, the model performance was tested on the wheat weed datasets. The experiments show that the YOLOv8-MBM proposed in this paper is superior to Fast R-CNN, YOLOv3, YOLOv4-tiny, YOLOv5s, YOLOv7, YOLOv9, and other mainstream models in regards to detection performance. The accuracy of the improved model reaches 92.7%. Compared with the original YOLOv8s model, the precision, recall, mAP1, and mAP2 are increased by 10.6%, 8.9%, 9.7%, and 9.3%, respectively. In summary, the YOLOv8-MBM model successfully meets the requirements for accurate weed detection in wheat fields.

Stereo Vision for Plant Detection in Dense Scenes.

Automated precision weed control requires visual methods to discriminate between crops and weeds. State-of-the-art plant detection methods fail to reliably detect weeds, especially in dense and occluded scenes. In the past, using hand-crafted detection models, both color (RGB) and depth (D) data were used for plant detection in dense scenes. Remarkably, the combination of color and depth data is not widely used in current deep learning-based vision systems in agriculture. Therefore, we collected an RGB-D dataset using a stereo vision camera. The dataset contains sugar beet crops in multiple growth stages with a varying weed densities. This dataset was made publicly available and was used to evaluate two novel plant detection models, the D-model, using the depth data as the input, and the CD-model, using both the color and depth data as inputs. For ease of use, for existing 2D deep learning architectures, the depth data were transformed into a 2D image using color encoding. As a reference model, the C-model, which uses only color data as the input, was included. The limited availability of suitable training data for depth images demands the use of data augmentation and transfer learning. Using our three detection models, we studied the effectiveness of data augmentation and transfer learning for depth data transformed to 2D images. It was found that geometric data augmentation and transfer learning were equally effective for both the reference model and the novel models using the depth data. This demonstrates that combining color-encoded depth data with geometric data augmentation and transfer learning can improve the RGB-D detection model. However, when testing our detection models on the use case of volunteer potato detection in sugar beet farming, it was found that the addition of depth data did not improve plant detection at high vegetation densities.

Intrarow Uncut Weed Detection Using You-Only-Look-Once Instance Segmentation for Orchard Plantations.

Mechanical weed management is a drudging task that requires manpower and has risks when conducted within rows of orchards. However, intrarow weeding must still be conducted by manual labor due to the restricted movements of riding mowers within the rows of orchards due to their confined structures with nets and poles. However, autonomous robotic weeders still face challenges identifying uncut weeds due to the obstruction of Global Navigation Satellite System (GNSS) signals caused by poles and tree canopies. A properly designed intelligent vision system would have the potential to achieve the desired outcome by utilizing an autonomous weeder to perform operations in uncut sections. Therefore, the objective of this study is to develop a vision module using a custom-trained dataset on YOLO instance segmentation algorithms to support autonomous robotic weeders in recognizing uncut weeds and obstacles (i.e., fruit tree trunks, fixed poles) within rows. The training dataset was acquired from a pear orchard located at the Tsukuba Plant Innovation Research Center (T-PIRC) at the University of Tsukuba, Japan. In total, 5000 images were preprocessed and labeled for training and testing using YOLO models. Four versions of edge-device-dedicated YOLO instance segmentation were utilized in this research-YOLOv5n-seg, YOLOv5s-seg, YOLOv8n-seg, and YOLOv8s-seg-for real-time application with an autonomous weeder. A comparison study was conducted to evaluate all YOLO models in terms of detection accuracy, model complexity, and inference speed. The smaller YOLOv5-based and YOLOv8-based models were found to be more efficient than the larger models, and YOLOv8n-seg was selected as the vision module for the autonomous weeder. In the evaluation process, YOLOv8n-seg had better segmentation accuracy than YOLOv5n-seg, while the latter had the fastest inference time. The performance of YOLOv8n-seg was also acceptable when it was deployed on a resource-constrained device that is appropriate for robotic weeders. The results indicated that the proposed deep learning-based detection accuracy and inference speed can be used for object recognition via edge devices for robotic operation during intrarow weeding operations in orchards.

Herbicide Bioassay Using a Multi-Well Plate and Plant Spectral Image Analysis.

A spectral image analysis has the potential to replace traditional approaches for assessing plant responses to different types of stresses, including herbicides, through non-destructive and high-throughput screening (HTS). Therefore, this study was conducted to develop a rapid bioassay method using a multi-well plate and spectral image analysis for the diagnosis of herbicide activity and modes of action. Crabgrass (Digitaria ciliaris), as a model weed, was cultivated in multi-well plates and subsequently treated with six herbicides (paraquat, tiafenacil, penoxsulam, isoxaflutole, glufosinate, and glyphosate) with different modes of action when the crabgrass reached the 1-leaf stage, using only a quarter of the recommended dose. To detect the plant's response to herbicides, plant spectral images were acquired after herbicide treatment using RGB, infrared (IR) thermal, and chlorophyll fluorescence (CF) sensors and analyzed for diagnosing herbicide efficacy and modes of action. A principal component analysis (PCA), using all spectral data, successfully distinguished herbicides and clustered depending on their modes of action. The performed experiments showed that the multi-well plate assay combined with a spectral image analysis can be successfully applied for herbicide bioassays. In addition, the use of spectral image sensors, especially CF images, would facilitate HTS by enabling the rapid observation of herbicide responses at as early as 3 h after herbicide treatment.

Remote Sensing Evaluation Drone Herbicide Application Effectiveness for Controlling Echinochloa spp. in Rice Crop in Valencia (Spain).

Rice (Oryza sativa L.) is a staple cereal in the diet of more than half of the world's population. Within the European Union, Spain is a leader in rice production due to its climate and tradition, accounting for 26% of total EU production in 2020. The Valencian rice area covers around 15,000 hectares and is strongly influenced by biotic and abiotic factors. An important biotic factor affecting rice production is weeds, which compete with rice for sunlight, water and nutrients. The dominant weed in Spain is Echinochloa spp., although wild rice is becoming increasingly important. Rice cultivation in Valencia takes place in the area of L'Albufera de Valencia, which is a natural park, i.e., a special protection area. In this natural area, the use of phytosanitary products is limited, so it is necessary to use the minimum amount possible. Therefore, the objective of this work is to evaluate the possibility of using remote sensing effectively to determine the effectiveness of the application of the herbicide cyhalofop-butyl by drone for the control of Echinochloa spp. in rice crops in Valencia. The results will be compared with those obtained by using sterilisation machines (electric backpack sprayers) to apply the herbicide. To evaluate the effectiveness of the application, the reflectance obtained by the satellite sensors in the red and near infrared (NIR) wavelengths, as well as the normalised difference vegetation index (NDVI), were used. The remote sensing results were analysed and complemented by the number of rice plants and weeds per area, plant dry weight, leaf area, BBCH phenological state, SPAD index values, chlorophyll content and relative growth rate. Remote sensing is validated as an effective tool for determining the efficacy of an herbicide in controlling weeds applied by both the drone and the electric backpack sprayer. The weeds slowed down their development after the treatment. Depending on the phenological state of the crop and the active ingredient of the herbicide, these results are applicable to other areas with different climatic and environmental conditions.