[Objectives]This study was conducted to explore how can we better break the dormancy of velvetleaf seeds and the best method to promote seed germination.[Methods]With the seeds of velvetleaf(Abutilon theophrasti)as ex...[Objectives]This study was conducted to explore how can we better break the dormancy of velvetleaf seeds and the best method to promote seed germination.[Methods]With the seeds of velvetleaf(Abutilon theophrasti)as experimental materials,the dormancy of velvetleaf seeds was revealed through seed vigor determination,water absorption rate determination and germination tests,and the seeds of velvetleaf were treated by physical and chemical methods to explore the best method for breaking dormancy of velvetleaf seeds.[Results]Poor water permeability of seed coat and endogenous inhibitory substances present in the seeds were the main reasons leading to the dormancy of velvetleaf seeds.The shell-breaking treatment,98%concentrated sulfuric acid treatment and 40%NaOH strong alkali treatment all could break the dormancy obstacle of velvetleaf seed coat.Compositing the above measures with 200 mg/ml gibberellin solution could further improve the germination ability of seeds.Among them,compositing the mechanical shell-breaking treatment with gibberellin had the best effect,followed by the composite of 10 and 15 min of 98%concentrated sulfuric acid treatment with gibberellin.[Conclusions]This study lays a foundation for the utilization and development and the comprehensive prevention and control research of velvetleaf seeds.展开更多
Weed management is a major component of a soybean (Glycine max L.) production system;thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties ...Weed management is a major component of a soybean (Glycine max L.) production system;thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The objective of this study was to evaluate normalized difference vegetation indices derived from multispectral leaf reflectance data as input into random forest machine learner to differentiate soybean and three broad leaf weeds: Palmer amaranth (Amaranthus palmeri L.), redroot pigweed (A. retroflexus L.), and velvetleaf (Abutilon theophrasti Medik). Leaf reflectance measurements were acquired from plants grown in two separate greenhouse experiments conducted in 2014. Twelve normalized difference vegetation indices were derived from the reflectance measurements, including advanced, green, greenred, green-blue, and normalized difference vegetation indices, shortwave infrared water stress indices, normalized difference pigment and red edge indices, and structure insensitive pigment index. Using the twelve vegetation indices as input variables, the conditional inference version of random forest (cforest) readily distinguished soybean and velvetleaf from the two pigweeds (Palmer amaranth and redroot pigweed) and from each other with classification accuracies ranging from 93.3% to 100%. The greatest errors were observed between the two pigweed classes, with classification accuracies ranging from 70% to 93.3%. Results suggest combining them into one class to increase classification accuracy. Vegetation indices results were equivalent to or slightly better than results obtained with sixteen multispectral bands used as input data into cforest. This research further supports using vegetation indices and machine learning algorithms such as cforest as decision support tools for weed identification.展开更多
Weed tolerance of UV-B radiation varies with species, and the radiation could affect weed ecology and management. Variations In growth, photosynthesis and defense system among four important agronomic weeds, Abutllon ...Weed tolerance of UV-B radiation varies with species, and the radiation could affect weed ecology and management. Variations In growth, photosynthesis and defense system among four important agronomic weeds, Abutllon theophrastl Medlk, Amaranthus retroflexus L., Digitaria sanguinalis （L.） Scop and Chloris virgata Swartz, under Increased UV-B radiation （ambient and increased radiation at 2.7, 5.4 and 10.8 kJ.m^-2.d-1） were studied In the greenhouse experiment. After 2 weeks of radiation, the shoots＇ dry mass decreased with increasing UV-B radiation except for D. sanguinalis. The reduction in biomass was the result of changes in morphology and physiology. Higher levels of UV-B treatment decreased the leaf area, plant height, net photosynthetic rate and chlorophyll contents, while it increased the contents of wax and UV-B absorbing compound in all species, except for A. retroflexus, which did not increase significantly. The activity of superoxide dismutase, catalase, ascorbate peroxide and the content of ascorblc acid changed differently among the weed species as UV-B radiation increased. D. sangulnalls was the most tolerant and A. retroflexus the most sensitive to increased UV-B radiation. The results also show that the two grass species （D. sanguinalis and C. virgata） were more tolerant to UV-B radiation than the two broadleafed species （A. theophrasti and A. retroflexus）. The UV-B absorbing compound and leaf wax played Important roles against UV-B damages in the two grass weeds. The overall results suggest that weed community, competition and management will be altered by continuous ozone depletion.展开更多
基金Excellent Youth Project of the Education Department of Hunan Province(18B461)the Science and Technology Innovation Program of Hunan Province(2019NK4170)Double First-class Applied Characteristic Discipline in Hunan Province Plant protection。
文摘[Objectives]This study was conducted to explore how can we better break the dormancy of velvetleaf seeds and the best method to promote seed germination.[Methods]With the seeds of velvetleaf(Abutilon theophrasti)as experimental materials,the dormancy of velvetleaf seeds was revealed through seed vigor determination,water absorption rate determination and germination tests,and the seeds of velvetleaf were treated by physical and chemical methods to explore the best method for breaking dormancy of velvetleaf seeds.[Results]Poor water permeability of seed coat and endogenous inhibitory substances present in the seeds were the main reasons leading to the dormancy of velvetleaf seeds.The shell-breaking treatment,98%concentrated sulfuric acid treatment and 40%NaOH strong alkali treatment all could break the dormancy obstacle of velvetleaf seed coat.Compositing the above measures with 200 mg/ml gibberellin solution could further improve the germination ability of seeds.Among them,compositing the mechanical shell-breaking treatment with gibberellin had the best effect,followed by the composite of 10 and 15 min of 98%concentrated sulfuric acid treatment with gibberellin.[Conclusions]This study lays a foundation for the utilization and development and the comprehensive prevention and control research of velvetleaf seeds.
文摘Weed management is a major component of a soybean (Glycine max L.) production system;thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The objective of this study was to evaluate normalized difference vegetation indices derived from multispectral leaf reflectance data as input into random forest machine learner to differentiate soybean and three broad leaf weeds: Palmer amaranth (Amaranthus palmeri L.), redroot pigweed (A. retroflexus L.), and velvetleaf (Abutilon theophrasti Medik). Leaf reflectance measurements were acquired from plants grown in two separate greenhouse experiments conducted in 2014. Twelve normalized difference vegetation indices were derived from the reflectance measurements, including advanced, green, greenred, green-blue, and normalized difference vegetation indices, shortwave infrared water stress indices, normalized difference pigment and red edge indices, and structure insensitive pigment index. Using the twelve vegetation indices as input variables, the conditional inference version of random forest (cforest) readily distinguished soybean and velvetleaf from the two pigweeds (Palmer amaranth and redroot pigweed) and from each other with classification accuracies ranging from 93.3% to 100%. The greatest errors were observed between the two pigweed classes, with classification accuracies ranging from 70% to 93.3%. Results suggest combining them into one class to increase classification accuracy. Vegetation indices results were equivalent to or slightly better than results obtained with sixteen multispectral bands used as input data into cforest. This research further supports using vegetation indices and machine learning algorithms such as cforest as decision support tools for weed identification.
基金Supported by the National Natural Science Foundation of China （30370940）.
文摘Weed tolerance of UV-B radiation varies with species, and the radiation could affect weed ecology and management. Variations In growth, photosynthesis and defense system among four important agronomic weeds, Abutllon theophrastl Medlk, Amaranthus retroflexus L., Digitaria sanguinalis （L.） Scop and Chloris virgata Swartz, under Increased UV-B radiation （ambient and increased radiation at 2.7, 5.4 and 10.8 kJ.m^-2.d-1） were studied In the greenhouse experiment. After 2 weeks of radiation, the shoots＇ dry mass decreased with increasing UV-B radiation except for D. sanguinalis. The reduction in biomass was the result of changes in morphology and physiology. Higher levels of UV-B treatment decreased the leaf area, plant height, net photosynthetic rate and chlorophyll contents, while it increased the contents of wax and UV-B absorbing compound in all species, except for A. retroflexus, which did not increase significantly. The activity of superoxide dismutase, catalase, ascorbate peroxide and the content of ascorblc acid changed differently among the weed species as UV-B radiation increased. D. sangulnalls was the most tolerant and A. retroflexus the most sensitive to increased UV-B radiation. The results also show that the two grass species （D. sanguinalis and C. virgata） were more tolerant to UV-B radiation than the two broadleafed species （A. theophrasti and A. retroflexus）. The UV-B absorbing compound and leaf wax played Important roles against UV-B damages in the two grass weeds. The overall results suggest that weed community, competition and management will be altered by continuous ozone depletion.
