Biological and chemical pruning wound protectants reduce infection of grapevine trunk disease pathogens

Grapevine trunk diseases (GTDs) are currently considered some of the most important challenges for viticulture, curtailing vineyard longevity and productivity in nearly every raisin, table and wine grape production region in California and worldwide. Pruning wounds provide the main entry point for fungal pathogens responsible for these diseases; pathogens enter the wounds following precipitation events. The aim of this study was to evaluate the efficacy of selected chemical and experimental biological fungicides for protection of pruning wounds against two of the most common and virulent fungal pathogens causing GTDs: Eutypa lata and Neofusicoccum parvum. This study was conducted on sauvignon blanc at the UC Davis Department of Plant Pathology Field Station. Results showed that several chemical and biological fungicides, notably the chemical fungicide Luna Sensation, the biofungicide Vintec and a combination of the biofungicides Bio-Tam and CrabLife Powder, provided significant protection against at least one of the two canker pathogens used in this study. However, the majority of products tested did not provide simultaneous control of both E. lata and N. parvum pathogens, highlighting the continuing challenge of controlling GTDs.

The economic feasibility of Gerga's orange (Citrus sp.) agribusiness as a new source of economic growth in Bengkulu, Indonesia

This research gave the empirical verification that orange’s agribusiness can be a source of new growth for its center production region, as in case the Gerga’s orange agribusiness for Bengkulu province in Indonesia. It is verified this kind of agribusiness benefited its largest stakeholder, namely farmers, based on parameters such as B/C ratio, farmer's share, and marketing margin. From a macroeconomic perspective, Gerga's agribusiness also can solve macroeconomic problems such as poverty, unemployment, basic needs, and regional minimum wages.

Changes of Extreme Agro-Climatic Droughts and Their Impacts on Grain Yields in Rain-Fed Agricultural Regions in China over the Past 50 Years

Climate change and climate extremes and their impacts on agriculture, water resources, and ecosystems have become important issues globally. Agricultural sustainability and food security are facing unprecedented challenges due to the increasing occurrence of extreme climatic events, including, notably, extreme droughts in recent years in China. In this study, a threshold determination model of extreme agro-climatic droughts (EADs) was built based on the cumulative probability distribution functions (CDF) of an agricultural drought index—the consecutive days without available precipitation (CDWAP). The CDWAP was established by combining meteorological data with the characteristics of cropping patterns and the water requirement in different growing periods of crops. The CDF of CDWAP was obtained based on the relationship of CDWAP and its occurrence frequency. Based on the model, the spatial pattern of the thresholds of EADs and the threshold exceedance time series of EADs in 500 meteorological stations were obtained, and then changes in the frequencies and intensities of EADs in China and their impacts on grain yields in rain-fed regions during the past 50 years were analyzed. The results follow: (1) The threshold value of EADs in China gradually increased from southeast to northwest. The stations of the highest value were located in the Northwest China, with the CDWAP more than 60 days, while the lowest value was in the middle reaches of the Yangzi River, with the CDWAP less than 16 days. (2) The frequencies and intensities of the EADs increased mostly in the east areas of the Hu Huanyong line, which was also the main agricultural production region in China. The North China (NC) and Southwest China (SW) regions showed the highest increasing rates of the EADs; their frequencies and intensities were 11.3% and 2.2%, respectively, for the NC region, and 9.3% and 2.7%, respectively, for the SW region. (3) Case studies in the NC, SW, and SE regions indicated that there was a negative correlation between grain yields and EAD frequency and intensity; i.e., the low grain yields often occurred in the year with relatively higher frequency or/and stronger intensity of EADs. The correlation coefficients of grain yield and EAD were generally greater than that of merely extreme climatic droughts; therefore, the study of EAD is necessary when researching the impacts of extreme drought events on grain yield.

Herbicide Efficacy of Spot Spraying Systems in Fallow and Postharvest in the Pacific Northwest Dryland Wheat Production Region

Real-time spot spraying technology has the potential to reduce herbicide costs and slow herbicide resistance. However, few studies exist on the efficacy of this technology in the Pacific Northwest (PNW). This research compared the herbicide efficacy (reduction in weed density and cover) of WEED-IT and WeedSeeker spot spraying systems to uniform spraying in fallow and postharvest in 2019 and 2020. Weed community types included naturally occurring weeds, natural + Russian thistle (Salsola tragus L.), or natural + kochia (Bassia scoparia (L.) A. J. Scott). Herbicides included glyphosate or the pre-mix bromoxynil + pyrasulfotole. Additionally, herbicide efficacy was studied with short stubble (~10 cm), tall stubble (~25 cm), and normal stubble (~20 cm) with chaff and straw removed. In fallow, herbicide efficacy was 1.5 times higher for uniform applications than for WEED-IT or WeedSeeker in 2019 and 2020. Herbicide efficacy was also 1.9 times higher for uniform applications in postharvest in 2019 but no differences were found in 2020. The weed community impacted herbicide efficacy but herbicide efficacy did not differ between residue management treatments. Finally, WEED-IT and WeedSeeker used 53% less herbicide volume in comparison to uniform applications. This research demonstrated that spot spraying technology can be efficacious and economical for growers in the PNW.

Spin and Accretion Rate Dependence of Black Hole X-Ray Spectra

We present a survey of how the spectral features of black hole X-ray binary systems depend on spin, accretion rate, viewing angle, and Fe abundance when predicted on the basis of first-principles physical calculations. The power-law component hardens with increasing spin. The thermal component strengthens with increasing accretion rate. The Compton bump is enhanced by higher accretion rate and lower spin. The Fe Kα equivalent width grows sublinearly with Fe abundance. Strikingly, the Kα profile is more sensitive to accretion rate than to spin because its radial surface brightness profile is relatively flat, and higher accretion rate extends the production region to smaller radii. The overall radiative efficiency is at least 30%–100% greater than as predicted by the Novikov–Thorne model.

Declining methane emissions and steady, high leakage rates observed over multiple years in a western US oil/gas production basin

Methane, a potent greenhouse gas, is the main component of natural gas. Previous research has identified considerable methane emissions associated with oil and gas production, but estimates of emission trends have been inconsistent, in part due to limited in-situ methane observations spanning multiple years in oil/gas production regions. Here we present a unique analysis of one of the longest-running datasets of in-situ methane observations from an oil/gas production region in Utah’s Uinta Basin. The observations indicate Uinta methane emissions approximately halved between 2015 and 2020, along with declining gas production. As a percentage of gas production, however, emissions remained steady over the same years, at ~ 6–8%, among the highest in the U.S. Addressing methane leaks and recovering more of the economically valuable natural gas is critical, as the U.S. seeks to address climate change through aggressive greenhouse emission reductions.

Microseismicity Associated with Actively Exploited Geothermal Systems: Earthquake Detection and Probabilistic Location at Rotokawa and Statistical Seismic Network Design at Kawerau

<p>Geothermal power has progressively been recognised as an important energy resource due to the depletion of old power sources, and as a more environmentally aware population pushes for an increase in renewable energy sources. Monitoring microseismicity occurring in active geothermal systems is one means of both characterising the system’s fault architecture and characterising fluid/rock interaction in response to production. This study focuses on better understanding seismicity in two active geothermal fields, through the development and implementation of two different algorithms: an automated microearthquake detection algorithm using a matched filter technique (improving earthquake detection), and an optimal seismic network design algorithm (improving earthquake location). Both algorithms have been implemented in codes that are easily adaptable to other data sets. The first of these algorithms has been applied to five months of continuous seismic waveform data spanning a fluid injection operation in the Rotokawa geothermal field. The cross-correlation of 14 high-quality master events with the continuous seismic data yields 2461 newly detected earthquakes spanning the magnitude range M=-0.4 to M=2.6 with a mean magnitude of M=0.47. The earthquakes detected with each master event exhibit high waveform similarity over approximately three orders of magnitude, and appear to follow a Gutenberg-Richter power law with a catalogue completeness down to M~ 0. Hypocentres for these detected events computed using the probabilistic earthquake location algorithm NonLinLoc reveal the dominant locus of seismicity to lie between 1.0–2.5 km depth, a location consistent with that of the Rotokawa Andesite which forms the Rotokawa reservoir. Focal mechanism solutions for the master events are predominantly normal, with half displaying a large strike-slip component, and the stress parameters obtained for this suite of focal mechanisms imply a northeast–southwest oriented maximum horizontal stress: both of these results are consistent with the extensional regime of the TVZ. Seismicity occurring within a 300 m horizontal radius of the injection well’s feed-zones, and extending to 5 km depth, initially exhibits a correlation with injection flow rates with a ~ 2 day lag, and seismicity rates decrease ~ 10 weeks after injection. We surmise that seismicity within the injection region and close to the injection well is likely to be injection-induced, with one portion of the injectate returning to the production region, while the other either migrates southeastward out of the field or remains within the injection region; the origin of seismicity within the production region in relationship to production and injection processes is unclear. The second of these algorithms involves the derivation of a design criterion, which we apply to inform the expansion of the existing seismic monitoring programme at Kawerau geothermal field; we also apply an early version to the short-term/rapid-response network design following the M7.1 September 2010 Darfield earthquake. Unlike previous seismic network design algorithms, the new algorithm incorporates methods for the realistic representation of 3D velocity structures and attenuation models for both P and S travel times, a surface noise model, and the ability to apply complex weighting functions to the earthquake set. The results demonstrate the utility of this algorithm in even simplistic cases, and show how each new parameter incorporated into the design model affects the optimal network design obtained, identifying the need for accurate input data to provide optimal results.</p>

Microseismicity Associated with Actively Exploited Geothermal Systems: Earthquake Detection and Probabilistic Location at Rotokawa and Statistical Seismic Network Design at Kawerau

<p>Geothermal power has progressively been recognised as an important energy resource due to the depletion of old power sources, and as a more environmentally aware population pushes for an increase in renewable energy sources. Monitoring microseismicity occurring in active geothermal systems is one means of both characterising the system’s fault architecture and characterising fluid/rock interaction in response to production. This study focuses on better understanding seismicity in two active geothermal fields, through the development and implementation of two different algorithms: an automated microearthquake detection algorithm using a matched filter technique (improving earthquake detection), and an optimal seismic network design algorithm (improving earthquake location). Both algorithms have been implemented in codes that are easily adaptable to other data sets. The first of these algorithms has been applied to five months of continuous seismic waveform data spanning a fluid injection operation in the Rotokawa geothermal field. The cross-correlation of 14 high-quality master events with the continuous seismic data yields 2461 newly detected earthquakes spanning the magnitude range M=-0.4 to M=2.6 with a mean magnitude of M=0.47. The earthquakes detected with each master event exhibit high waveform similarity over approximately three orders of magnitude, and appear to follow a Gutenberg-Richter power law with a catalogue completeness down to M~ 0. Hypocentres for these detected events computed using the probabilistic earthquake location algorithm NonLinLoc reveal the dominant locus of seismicity to lie between 1.0–2.5 km depth, a location consistent with that of the Rotokawa Andesite which forms the Rotokawa reservoir. Focal mechanism solutions for the master events are predominantly normal, with half displaying a large strike-slip component, and the stress parameters obtained for this suite of focal mechanisms imply a northeast–southwest oriented maximum horizontal stress: both of these results are consistent with the extensional regime of the TVZ. Seismicity occurring within a 300 m horizontal radius of the injection well’s feed-zones, and extending to 5 km depth, initially exhibits a correlation with injection flow rates with a ~ 2 day lag, and seismicity rates decrease ~ 10 weeks after injection. We surmise that seismicity within the injection region and close to the injection well is likely to be injection-induced, with one portion of the injectate returning to the production region, while the other either migrates southeastward out of the field or remains within the injection region; the origin of seismicity within the production region in relationship to production and injection processes is unclear. The second of these algorithms involves the derivation of a design criterion, which we apply to inform the expansion of the existing seismic monitoring programme at Kawerau geothermal field; we also apply an early version to the short-term/rapid-response network design following the M7.1 September 2010 Darfield earthquake. Unlike previous seismic network design algorithms, the new algorithm incorporates methods for the realistic representation of 3D velocity structures and attenuation models for both P and S travel times, a surface noise model, and the ability to apply complex weighting functions to the earthquake set. The results demonstrate the utility of this algorithm in even simplistic cases, and show how each new parameter incorporated into the design model affects the optimal network design obtained, identifying the need for accurate input data to provide optimal results.</p>