213 research outputs found
Herbicide-resistant Grain Sorghum
A fluazifop-resistant sorghum cultivar designated ‘21534_ACCase-R’ and plants comprising a polynucleotide encoding the polypeptide of SEQ ID NO: 39 are disclosed herein. The present invention provides seeds, plants, and plant parts derived from sorghum cultivar ‘21534_ACCase-R’ and those including SEQ ID NO: 39. Further, it provides methods for producing a sorghum plant by crossing ‘21534_ACCase-R’ with itself or another sorghum variety. The invention also encompasses any sorghum seeds, plants, and plant parts produced by the methods disclosed herein, including those in which additional traits have been transferred into ‘21534_ACCase-R’ through the introduction of a transgene or by breeding ‘21534_ACCase-R’ with another sorghum cultivar
Seed production of barnyardgrass (Echinochloa crus-galli) in response to time of emergence in cotton and rice
The spread of herbicide resistance in barnyardgrass (Echinochloa crus-galli (L.) Beauv.) poses a serious threat to crop production in the southern United States. A thorough knowledge of the biology of barnyardgrass is fundamental for designing effective resistance-management programmes. In the present study, seed production of barnyardgrass in response to time of emergence was investigated in cotton and rice, respectively, in Fayetteville and Rohwer, Arkansas, over a 2-year period (2008–09). Barnyardgrass seed production was greater when seedlings emerged with the crop, but some seed production was observed even if seedlings emerged several weeks after crop emergence. Moreover, barnyardgrass seed production was highly variable across environments. When emerging with the crop (0 weeks after crop emergence (WAE)), barnyardgrass produced c. 35 500 and 16 500 seeds/plant in cotton, and c. 39 000 and 2900 seeds/plant in rice, in 2008 and 2009, respectively. Seed production was observed when seedlings emerged up to 5 WAE (2008) or 7 WAE (2009) in cotton and up to 5 WAE (2008, 2009) in rice; corresponding seed production was c. 2500 and 1500 seeds/plant in cotton, and c. 14 700 and 110 seeds/plant in rice, in 2008 and 2009, respectively. The results suggest that cultural approaches that delay the emergence of barnyardgrass or approaches that make the associated crop more competitive will be useful in integrated management programmes. In the context of herbicide resistance management, it may be valuable to prevent seed return to the seedbank, irrespective of cohorts. The findings are vital for parameterizing herbicide resistance simulation models for barnyardgrass
Herbicide-resistant Grain Sorghum
A fluazifop-resistant sorghum cultivar designated ‘21534_ACCase-R’ and plants comprising a polynucleotide encoding the polypeptide of SEQ ID NO: 39 are disclosed herein. The present invention provides seeds, plants, and plant parts derived from sorghum cultivar ‘21534_ACCase-R’ and those including SEQ ID NO: 39. Further, it provides methods for producing a sorghum plant by crossing ‘21534_ACCase-R’ with itself or another sorghum variety. The invention also encompasses any sorghum seeds, plants, and plant parts produced by the methods disclosed herein, including those in which additional traits have been transferred into ‘21534_ACCase-R’ through the introduction of a transgene or by breeding ‘21534_ACCase-R’ with another sorghum cultivar
Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development
Unmanned Aerial Vehicles and Systems (UAV or UAS) have become increasingly popular in recent years for agricultural research applications. UAS are capable of acquiring images with high spatial and temporal resolutions that are ideal for applications in agriculture. The objective of this study was to evaluate the performance of a UAS-based remote sensing system for quantification of crop growth parameters of sorghum (Sorghum bicolor L.) including leaf area index (LAI), fractional vegetation cover (fc) and yield. The study was conducted at the Texas A&M Research Farm near College Station, Texas, United States. A fixed-wing UAS equipped with a multispectral sensor was used to collect image data during the 2016 growing season (April±October). Flight missions were successfully carried out at 50 days after planting (DAP; 25 May), 66 DAP (10 June) and 74 DAP (18 June). These flight missions provided image data covering the middle growth period of sorghum with a spatial resolution of approximately 6.5 cm. Field measurements of LAI and fc were also collected. Four vegetation indices were calculated using the UAS images. Among those indices, the normalized difference vegetation index (NDVI) showed the highest correlation with LAI, fc and yield with R2 values of 0.91, 0.89 and 0.58 respectively. Empirical relationships between NDVI and LAI and between NDVI and fc were validated and proved to be accurate for estimating LAI and fc from UAS-derived NDVI values. NDVI determined from UAS imagery acquired during the flowering stage (74 DAP) was found to be the most highly correlated with final grain yield. The observed high correlations between UAS-derived NDVI and the crop growth parameters (fc, LAI and grain yield) suggests the applicability of UAS for withinseason data collection of agricultural crops such as sorghum
Modelling the Dynamics of Feral Alfalfa Populations and Its Management Implications
BACKGROUND: Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. METHODOLOGY/PRINCIPAL FINDINGS: We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. CONCLUSIONS/SIGNIFICANCE: Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be applied to other perennial herbaceous plants with similar life-history characteristics
Simulation models on the ecology and management of arableweeds: Structure, quantitative insights, and applications
In weed science and management, models are important and can be used to better understand what has occurred in management scenarios, to predict what will happen and to evaluate the outcomes of control methods. To-date, perspectives on and the understanding of weed models have been disjointed, especially in terms of how they have been applied to advance weed science and management. This paper presents a general overview of the nature and application of a full range of simulation models on the ecology, biology, and management of arable weeds, and how they have been used to provide insights and directions for decision making when long-term weed population trajectories are impractical to be determined using field experimentation. While research on weed biology and ecology has gained momentum over the past four decades, especially for species with high risk for herbicide resistance evolution, knowledge gaps still exist for several life cycle parameters for many agriculturally important weed species. More research efforts should be invested in filling these knowledge gaps, which will lead to better models and ultimately better inform weed management decision making.Fil: Bagavathiannan, Muthukumar V.. Texas A&M University; Estados UnidosFil: Beckie, Hugh J.. University of Western Australia; AustraliaFil: Chantre Balacca, Guillermo Ruben. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de AgronomÃa; ArgentinaFil: González Andujar, José L.. Consejo Superior de Investigaciones CientÃficas; EspañaFil: Leon, Ramon G.. North Carolina State University; Estados UnidosFil: Neve, Paul. Agriculture & Horticulture Development Board; Reino UnidoFil: Poggio, Santiago Luis. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de AgronomÃa. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Schutte, Brian J.. New Mexico State University.; Estados UnidosFil: Somerville, Gayle J.. Sustainable Agriculture Sciences; Reino UnidoFil: Werle, Rodrigo. University of Wisconsin; Estados UnidosFil: Acker, Rene Van. University of Guelph; Canad
Seedbank Persistence of Palmer Amaranth (\u3ci\u3eAmaranthus palmeri\u3c/i\u3e) and Waterhemp (\u3ci\u3eAmaranthus tuberculatus\u3c/i\u3e) across Diverse Geographical Regions in the United States
Knowledge of the effects of burial depth and burial duration on seed viability and, consequently, seedbank persistence of Palmer amaranth (Amaranthus palmeri S. Watson) and waterhemp [Amaranthus tuberculatus (Moq.) J. D. Sauer] ecotypes can be used for the development of efficient weed management programs. This is of particular interest, given the great fecundity of both species and, consequently, their high seedbank replenishment potential. Seeds of both species collected from five different locations across the United States were investigated in seven states (sites) with different soil and climatic conditions. Seeds were placed at two depths (0 and 15cm) for 3 yr. Each year, seeds were retrieved, and seed damage (shrunken, malformed, or broken) plus losses (deteriorated and futile germination) and viability were evaluated. Greater seed damage plus loss averaged across seed origin, burial depth, and year was recorded for lots tested at Illinois (51.3% and 51.8%) followed by Tennessee (40.5% and 45.1%) and Missouri (39.2% and 42%) for A. palmeri and A. tuberculatus, respectively. The site differences for seed persistence were probably due to higher volumetric water content at these sites. Rates of seed demise were directly proportional to burial depth (α=0.001), whereas the percentage of viable seeds recovered after 36 mo on the soil surface ranged from 4.1% to 4.3% compared with 5% to 5.3% at the 15-cm depth for A. palmeri and A. tuberculatus, respectively. Seed viability loss was greater in the seeds placed on the soil surface compared with the buried seeds. The greatest influences on seed viability were burial conditions and time and site-specific soil conditions, more so than geographical location. Thus, management of these weed species should focus on reducing seed shattering, enhancing seed removal from the soil surface, or adjusting tillage systems
- …