Imidazolinone-Resistant Sunflower Tolerance to Imazapic

2009 ◽  
Vol 23 (1) ◽  
pp. 188-190
Author(s):  
Eric P. Prostko ◽  
Timothy L. Grey ◽  
Jerry W. Davis

Field trials were conducted in Georgia in 2007 to 2008 to evaluate the tolerance of three imidazolinone-resistant sunflower cultivars to POST applications of imazapic. There was no interaction between sunflower cultivar and herbicide treatment. When averaged over sunflower cultivars, imazapic, at 70 and 140 g ai/ha and applied at 30 d after planting, had no effect on sunflower above-ground biomass, plant height, seed-heads per meter row, and seed-head weights. Sunflower response to imazapic was similar to that of imazamox. Imazapic could be used in imidazolinone-resistant sunflower production systems without risk of unacceptable crop injury.

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 28 ◽  
Author(s):  
Uma Shankar Panday ◽  
Nawaraj Shrestha ◽  
Shashish Maharjan ◽  
Arun Kumar Pratihast ◽  
Shahnawaz ◽  
...  

Food security is one of the burning issues in the 21st century, as a tremendous population growth over recent decades has increased demand for food production systems. However, agricultural production is constrained by the limited availability of arable land resources, whereas a significant part of these is already degraded due to overexploitation. In order to get optimum output from the available land resources, it is of prime importance that crops are monitored, analyzed, and mapped at various stages of growth so that the areas having underdeveloped/unhealthy plants can be treated appropriately as and when required. This type of monitoring can be performed using ultra-high-resolution earth observation data like the images captured through unmanned aerial vehicles (UAVs)/drones. The objective of this research is to estimate and analyze the above-ground biomass (AGB) of the wheat crop using a consumer-grade red-green-blue (RGB) camera mounted on a drone. AGB and yield of wheat were estimated from linear regression models involving plant height obtained from crop surface models (CSMs) derived from the images captured by the drone-mounted camera. This study estimated plant height in an integrated setting of UAV-derived images with a Mid-Western Terai topographic setting (67 to 300 m amsl) of Nepal. Plant height estimated from the drone images had an error of 5% to 11.9% with respect to direct field measurement. While R2 of 0.66 was found for AGB, that of 0.73 and 0.70 were found for spike and grain weights respectively. This statistical quality assurance contributes to crop yield estimation, and hence to develop efficient food security strategies using earth observation and geo-information.


2019 ◽  
Vol 11 (11) ◽  
pp. 1261 ◽  
Author(s):  
Yaxiao Niu ◽  
Liyuan Zhang ◽  
Huihui Zhang ◽  
Wenting Han ◽  
Xingshuo Peng

The rapid, accurate, and economical estimation of crop above-ground biomass at the farm scale is crucial for precision agricultural management. The unmanned aerial vehicle (UAV) remote-sensing system has a great application potential with the ability to obtain remote-sensing imagery with high temporal-spatial resolution. To verify the application potential of consumer-grade UAV RGB imagery in estimating maize above-ground biomass, vegetation indices and plant height derived from UAV RGB imagery were adopted. To obtain a more accurate observation, plant height was directly derived from UAV RGB point clouds. To search the optimal estimation method, the estimation performances of the models based on vegetation indices alone, based on plant height alone, and based on both vegetation indices and plant height were compared. The results showed that plant height directly derived from UAV RGB point clouds had a high correlation with ground-truth data with an R2 value of 0.90 and an RMSE value of 0.12 m. The above-ground biomass exponential regression models based on plant height alone had higher correlations for both fresh and dry above-ground biomass with R2 values of 0.77 and 0.76, respectively, compared to the linear regression model (both R2 values were 0.59). The vegetation indices derived from UAV RGB imagery had great potential to estimate maize above-ground biomass with R2 values ranging from 0.63 to 0.73. When estimating the above-ground biomass of maize by using multivariable linear regression based on vegetation indices, a higher correlation was obtained with an R2 value of 0.82. There was no significant improvement of the estimation performance when plant height derived from UAV RGB imagery was added into the multivariable linear regression model based on vegetation indices. When estimating crop above-ground biomass based on UAV RGB remote-sensing system alone, looking for optimized vegetation indices and establishing estimation models with high performance based on advanced algorithms (e.g., machine learning technology) may be a better way.


2014 ◽  
Vol 28 (3) ◽  
pp. 479-485 ◽  
Author(s):  
Robert G. Wilson ◽  
Gustavo M. Sbatella

Field trials were conducted from 2010 through 2012 to evaluate the integration of three factors: overhead irrigation after planting great northern dry bean; three methods of seedbed preparation: no-tillage, one or two diskings; and eight weed control treatments on dry bean development and weed control. The previous crop each year was corn. Overhead irrigation with 13 mm of water immediately after herbicide application and planting in early June did not improve or reduce herbicide efficacy but where herbicides were not utilized, irrigation increased weed emergence. Soil crusting increased in 2 of 3 yr when soil was disked at a 20-cm depth before planting. Crop injury from herbicides applied PRE increased when soil crusting occurred. No tillage before planting reduced crop injury from herbicides in 2010 and 2011 and weed density in 2012. Dry bean injury was minimal from herbicides applied PRE except for flumioxazin, which reduced crop density in 2011 and 2012. Imazamox plus bentazon applied POST caused early-season dry bean injury in 2 of 3 yr and resulted in a reduction in crop seed yield compared to dimethenamid-P or halosulfuron applied PRE. As producers move away from intensive tillage before planting to reduced tillage or no-tillage production systems, the results of this experiment show that dimethenamid-P, halosulfuron, pendimethalin, andS-metolachlor can be utilized PRE to provide acceptable weed control and crop selectivity. Although flumioxazin applied PRE reduced plant density, Great Northern dry bean yields were not affected by the loss of plant stand.


2018 ◽  
Vol 9 ◽  
Author(s):  
Jose A. Jimenez-Berni ◽  
David M. Deery ◽  
Pablo Rozas-Larraondo ◽  
Anthony (Tony) G. Condon ◽  
Greg J. Rebetzke ◽  
...  

1989 ◽  
Vol 7 (1) ◽  
pp. 35-37
Author(s):  
Ted Whitwell ◽  
Kathie Kalmowitz

Abstract Granular herbicide combinations were evaluated for longevity of prostrate spurge (Euphorbia humistrata Engelm.ex.Gray) and large crabgrass (Digitaria sanguinalis L.) control. Rout (oxytluorfen + oryzalin), Ornamental Herbicide 2 (oxytluorfen + pendimethalin), Ronstar plus Modown (oxadiazon + bifenox) and Ronstar (oxadiazon) were applied at labeled rates and twice labeled rate in container grown Compact Japanese Holly (Ilex crenata ‘Compacta’). Weeds were reseeded each month but herbicides were not reapplied. The normal use rate controlled both weeds during the first 30 days after treatment (DAT) while twice this rate controlled the weed species at 60 DAT. No herbicide treatment effectively (>80%) controlled prostrate spurge 90 DAT. The high rate of Rout controlled (>80%) crabgrass at 90 DAT. Weed numbers and above ground biomass retlected visual control ratings. Compact Japanese Holly was not injured by any treatment.


2020 ◽  
pp. 113-118
Author(s):  
Getachew Amare ◽  
Temesgen Mamo

Keeping in view of lack of recommended rates of N and NPS fertilizers, a field experiment was conducted to evaluate the effect of the newly introduced NPS fertilizer and nitrogen on growth, physiology and above ground biomass of garlic. Four NPS (0-0-0, 78.75-69-12.75, 105-92-17 and 131.25-115-21.25 kg N-P-S ha-1) and three nitrogen fertilizer rates (114.13, 228.26 and 278.33 kg N ha-1) were laid out in Randomized Complete Block Design with three replications. Significantly highest plant height (28.02 cm), leaf diameter (1.27 cm), dry and fresh weight (4.71 g and 6.11 g) and leaf length were recorded on garlic plants supplied with 105-92-17 kg N-P-S ha-1 and also the highest plant height (27.75 cm), leaf length (24.02 cm), fresh and dry weight (6.23 g and 5.04 g) were recorded on garlic plants supplied with 278.33 kg N ha-1. The interaction effect also show a significant effect in almost all the growth parameters; the early day to 50% emergence was recorded from a plot which received 228.26 kg N ha-1 and 105-92-17 kg NPS ha-1 and the highest plant height, leaf length, fresh and dry above ground biomass and leaf diameter were 29.62 cm, 25.60 cm, 6.93 g, 5.59 g and 1.4 cm, respectively were observed by the interaction of 278.33 kg N ha-1 and 105-92-17 kg N-P-S ha-1 with no significant difference with 228.26 N and 78.75-69-12.75 kg N-P-S ha−1. From this one season experiment, fertilizer rates 307.01-69-12.75 kg N-P-S ha−1 could be recommended for garlic production.


2020 ◽  
Vol 12 (20) ◽  
pp. 3464
Author(s):  
Mauro Maesano ◽  
Sacha Khoury ◽  
Farid Nakhle ◽  
Andrea Firrincieli ◽  
Alan Gay ◽  
...  

Replacing fossil fuels with cellulosic biofuels is a valuable component of reducing the drivers of climate change. This leads to a requirement to develop more productive bioenergy crops, such as Arundo donax with the aim of increasing above-ground biomass (AGB). However, direct measurement of AGB is time consuming, destructive, and labor-intensive. Phenotyping of plant height and biomass production is a bottleneck in genomics- and phenomics-assisted breeding. Here, an unmanned aerial vehicle (UAV) for remote sensing equipped with light detection and ranging (LiDAR) was tested for remote plant height and biomass determination in A. donax. Experiments were conducted on three A. donax ecotypes grown in well-watered and moderate drought stress conditions. A novel UAV-LiDAR data collection and processing workflow produced a dense three-dimensional (3D) point cloud for crop height estimation through a normalized digital surface model (DSM) that acts as a crop height model (CHM). Manual measurements of crop height and biomass were taken in parallel and compared to LiDAR CHM estimates. Stepwise multiple regression was used to estimate biomass. Analysis of variance (ANOVA) tests and pairwise comparisons were used to determine differences between ecotypes and drought stress treatments. We found a significant relationship between the sensor readings and manually measured crop height and biomass, with determination coefficients of 0.73 and 0.71 for height and biomass, respectively. Differences in crop heights were detected more precisely from LiDAR estimates than from manual measurement. Crop biomass differences were also more evident in LiDAR estimates, suggesting differences in ecotypes’ productivity and tolerance to drought. Based on these results, application of the presented UAV-LiDAR workflow will provide new opportunities in assessing bioenergy crop morpho-physiological traits and in delivering improved genotypes for biorefining.


2014 ◽  
Vol 94 (8) ◽  
pp. 1471-1479 ◽  
Author(s):  
Wang Xiangxiang ◽  
Wang Quanjiu ◽  
Fan Jun ◽  
Su Lijun ◽  
Shen Xinlei

Xiangxiang, W., Quanjiu, W., Jun, F., Lijun, S. and Xinlei, S. 2014. Logistic model analysis of winter wheat growth on China's Loess Plateau. Can. J. Plant Sci. 94: 1471–1479. The leaf area index (LAI) and above-ground biomass are closely related to crop growth status and yields. Therefore, analysis of their variation and development of a mathematical model for their prediction can provide a theoretical basis for further research. This paper presents a new equation for logistic pattern that calculates above-ground biomass and LAI for different irrigation treatments independent of growing degree days (GDD) and plant height. The model root mean square of error (RMSE) for the LAI was from 0.25 to 1.36, and for above-ground biomass it was from 0.49 to 1.34. The r2 values for the model's output under the single irrigation, double irrigation, triple irrigation, and quadruple irrigation treatments were 0.98, 0.87, 0.96, 0.98 and 0.99, respectively. For above-ground biomass they were 0.96, 0.97, 0.99, 0.97, and 0.97, respectively. The relative error for LAI ranged from 0.026 to 15.2%. For above-ground biomass, the Re ranged from 5.78 to 8.79%. The results gave good agreement between the estimated values and the measured values. The Logistic model was good at estimating the LAI and the above-ground biomass from the plant height.


2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.


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