Preliminary observation on response of waterlogged cotton to different doses of AVG application

The obvious symptoms of waterlogging response in cotton are leaf chlorosis (yellowing) and dropping squares & bolls. In addition, Huck (1970) showed that tap root growth stopped within 30 min of reducing the oxygen in the soils, and that the growing point of the root was completely dead within 3 hrs. In other plant species, these responses have been associated with the effect of ethylene, produced in response to lack of oxygen (Pratt, 1953; Jackson, 1984; 1985; Jackson & Drew, 1984; Raskin & Konde, 1984; Stead, 1985; Voesenek & Blom, 1989; Osborne, 1991;Reid & Wu, 1991; Brady & Speirs, 1991; Voesenek et al, 1992; Drew, 1997). Ethylene is known to accelerate premature senescence, defoliation and boll dehiscence in cotton (Hall et al, 1957; Kirzek, 1986), but the involvement of ethylene in cotton's response to waterlogging has not been demonstrated. AVG (aminoethoxyvinylglycine)is an inhibitor of ethylene production. It can be used to indicate the involvement of ethylene production in physiological processes. Improvements in commercial production of AVG provide an exciting opportunity to explore the importance of ethylene production in plant responses to waterlogging in the field. To achieve meaningful results, dose-response tests are necessary to establish the concentration of AVG that is high enough to inhibit ethylene formation while low enough to minimise nonspecific and possibly toxic effects to the plants from AVG itself(Jackson, 1991)

Waterlogging and its effect on cotton growth and yield

Watterlogging is an important cause of yield loss on the cracking grey clays. We conducted a field experiment to quantify its impact on growth and yield. In terms of management, the results demonstrates the importance of ensuring adequate bed height and allowing excess water to leave the field quickly, definitely not later than 48 hours after irrigation

Nitrous oxide emissions from the Arabian Sea: A synthesis

We computed high-resolution (1º latitude x 1º longitude) seasonal and annual nitrous oxide (N2O) concentration fields for the Arabian Sea surface layer using a database containing more than 2400 values measured between December 1977 and July 1997. N2O concentrations are highest during the southwest (SW) monsoon along the southern Indian continental shelf. Annual emissions range from 0.33 to 0.70 Tg N2O and are dominated by fluxes from coastal regions during the SW and northeast monsoons. Our revised estimate for the annual N2O flux from the Arabian Sea is much more tightly constrained than the previous consensus derived using averaged in-situ data from a smaller number of studies. However, the tendency to focus on measurements in locally restricted features in combination with insufficient seasonal data coverage leads to considerable uncertainties of the concentration fields and thus in the flux estimates, especially in the coastal zones of the northern and eastern Arabian Sea. The overall mean relative error of the annual N2O emissions from the Arabian Sea was estimated to be at least 65%

Nitrous oxide emissions from the Arabian Sea: A synthesis

We computed high-resolution (1º latitude x  1º longitude) seasonal and annual nitrous oxide (N₂O) concentration fields for the Arabian Sea surface layer using a database containing more than 2400 values measured between December 1977 and July 1997. N₂O concentrations are highest during the southwest (SW) monsoon along the southern Indian continental shelf. Annual emissions range from 0.33 to 0.70 Tg N₂O and are dominated by fluxes from coastal regions during the SW and northeast monsoons. Our revised estimate for the annual N₂O flux from the Arabian Sea is much more tightly constrained than the previous consensus derived using averaged in-situ data from a smaller number of studies. However, the tendency to focus on measurements in locally restricted features in combination with insufficient seasonal data coverage leads to considerable uncertainties of the concentration fields and thus in the flux estimates, especially in the coastal zones of the northern and eastern Arabian Sea. The overall mean relative error of the annual N₂O emissions from the Arabian Sea was estimated to be at least 65%

Improving temperature‐based predictions of the timing of flowering in cotton

Key management recommendations for cotton (Gossypium hirsutum L.) management require estimates of the timing of crop phenology. Most commonly growing day degree (DD) (thermal time) approaches are used. Currently, across many cotton production regions, there is no consistent approach to predicting first square and flower timing. Day degree approaches vary considerably, with base thresholds different (12.0–15.6 °C) with no consistency using an optimum temperature threshold (i.e., temperature where development ceases to increase). As cotton is grown in variable and changing climates, and cultivars change, there is a need to ensure the accuracy of this approach for predicting timing of flowering for assisting cotton management. In this study new functions to predict first square and first flower were developed and validated using data collected in multiple seasons and regions (Australia and the United States). Earlier controlled environment studies that monitored crop development were used to assess in more detail how temperatures were affecting early cotton development. New DD functions developed predicted first square and first flower better than the existing Australian and U.S. approaches. The best performing functions had base temperatures like those of existing U.S. functions (15.6 °C) and an optimum threshold temperature of 32.0 °C. New universal DD targets for first square (343 DD [°C]) and first flower (584 DD) were developed. Controlled environment studies supported this base temperature outcome; however, it was less clear that 32.0 °C was the optimum threshold temperature from these data. Precise predictions of cotton development will facilitate accurate growth stage assessments and hence better cotton management decisions

The Cumulative Effect of Transient Synchrony States on Motor Performance in Parkinson's Disease.

Bursts of beta frequency band activity in the basal ganglia of patients with Parkinson's disease (PD) are associated with impaired motor performance. Here we test in human adults whether small variations in the timing of movement relative to beta bursts have a critical effect on movement velocity and whether the cumulative effects of multiple beta bursts, both locally and across networks, matter. We recorded local field potentials from the subthalamic nucleus (STN) in 15 PD patients of both genders OFF-medication, during temporary lead externalization after deep brain stimulation surgery. Beta bursts were defined as periods exceeding the 75th percentile amplitude threshold. Subjects performed a visual cued joystick reaching task, with the visual cue being triggered in real time with different temporal relationships to bursts of STN beta activity. The velocity of actions made in response to cues prospectively triggered by STN beta bursts was slower than when responses were not time-locked to recent beta bursts. Importantly, slow movements were those that followed multiple bursts close to each other within a trial. In contrast, small differences in the delay between the last burst and movement onset had no significant impact on velocity. Moreover, when the overlap of bursts between the two STN was high, slowing was more pronounced. Our findings suggest that the cumulative, but recent, history of beta bursting, both locally and across basal ganglia networks, may impact on motor performance.SIGNIFICANCE STATEMENT Bursts of beta frequency band activity in the basal ganglia are associated with slowing of voluntary movement in patients with Parkinson's disease. We show that slow movements are those that follow multiple bursts close to each other and bursts that are coupled across regions. These results suggest that the cumulative, but recent, history of beta bursting, both locally and across basal ganglia networks, impacts on motor performance in this condition. The manipulation of burst dynamics may be a means of selectively improving motor impairment

Local field potential activity dynamics in response to deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Local field potentials (LFPs) may afford insight into the mechanisms of action of deep brain stimulation (DBS) and potential feedback signals for adaptive DBS. In Parkinson's disease (PD) DBS of the subthalamic nucleus (STN) suppresses spontaneous activity in the beta band and drives evoked resonant neural activity (ERNA). Here, we investigate how STN LFP activities change over time following the onset and offset of DBS. To this end we recorded LFPs from the STN in 14 PD patients during long (mean: 181.2 s) and short (14.2 s) blocks of continuous stimulation at 130 Hz. LFP activities were evaluated in the temporal and spectral domains. During long stimulation blocks, the frequency and amplitude of the ERNA decreased before reaching a steady state after ~70 s. Maximal ERNA amplitudes diminished over repeated stimulation blocks. Upon DBS cessation, the ERNA was revealed as an under-damped oscillation, and was more marked and lasted longer after short duration stimulation blocks. In contrast, activity in the beta band suppressed within 0.5 s of continuous DBS onset and drifted less over time. Spontaneous activity was also suppressed in the low gamma band, suggesting that the effects of high frequency stimulation on spontaneous oscillations may not be selective for pathological beta activity. High frequency oscillations were present in only six STN recordings before stimulation onset and their frequency was depressed by stimulation. The different dynamics of the ERNA and beta activity with stimulation imply different DBS mechanisms and may impact how these activities may be used in adaptive feedback

Development and application of process-based simulation models for cotton production: a review of past, present, and future directions

The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeastern United States in the 1960's and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation models, examines applications of the models since the turn of the century, and identifies opportunities for improving models and their use in cotton research and decision support. Cotton models reviewed include those specific to cotton (GOSSYM, Cotton2K, COTCO2, OZCOT, and CROPGRO-Cotton) and generic crop models that have been applied to cotton production (EPIC, WOFOST, SUCROS, GRAMI, CropSyst, and AquaCrop). Model application areas included crop water use and irrigation water management, nitrogen dynamics and fertilizer management, genetics and crop improvement, climatology, global climate change, precision agriculture, model integration with sensor data, economics, and classroom instruction. Generally, the literature demonstrated increased emphasis on cotton model development in the previous century and on cotton model application in the current century. Although efforts to develop cotton models have a 40-year history, no comparisons among cotton models were reported. Such efforts would be advisable as an initial step to evaluate current cotton simulation strategies. Increasingly, cotton simulation models are being applied by non-traditional crop modelers, who are not trained agronomists but wish to use the models for broad economic or life cycle analyses. While this trend demonstrates the growing interest in the models and their potential utility for a variety of applications, it necessitates the development of models with appropriate complexity and ease-of-use for a given application, and improved documentation and teaching materials are needed to educate potential model users. Spatial scaling issues are also increasingly prominent, as models originally developed for use at the field scale are being implemented for regional simulations over large geographic areas. Research steadily progresses toward the advanced goal of model integration with variable-rate control systems, which use real-time crop status and environmental information to spatially and temporally optimize applications of crop inputs, while also considering potential environmental impacts, resource limitations, and climate forecasts. Overall, the review demonstrates a languished effort in cotton simulation model development, but the application of existing models in a variety of research areas remains strong and continues to grow