Development and Application of a Performance and Operational Feasibility Guide to Facilitate Adoption of Soil Moisture Sensors

Soil moisture sensors can be effective and promising decision-making tools for diverse applications and audiences, including agricultural managers, irrigation practitioners, and researchers. Nevertheless, there exists immense adoption potential in the United States, with only 1.2 in 10 farms nationally using soil moisture sensors to decide when to irrigate. This number is much lower in the global scale. Increased adoption is likely hindered by lack of scientific support in need assessment, selection, suitability and use of these sensors. Here, through extensive field research, we address the operational feasibility of soil moisture sensors, an aspect which has been overlooked in the past, and integrate it with their performance accuracy, in order to develop a quantitative framework to guide users in the selection of best-suited sensors for varying applications. These evaluations were conducted for nine commercially available sensors under silt loam and loamy sand soils in irrigated cropland and rainfed grassland for two different installation orientations [sensing component parallel (horizontal) and perpendicular (vertical) to the ground surface] typically used. All the sensors were assessed for their aptness in terms of cost, ease of operation, convenience of telemetry, and performance accuracy. Best sensors under each soil condition, sensor orientation, and user applications (research versus agricultural production) were identified. The step-by-step guide presented here will serve as an unprecedented and holistic adoption-assisting resource and can be extended to other sensors as well

Soil evaporation studies using mini-lysimeters under differently established rice-wheat cropping sequence in Punjab, India

Present investigations were carried out in rice-wheat cropping sequence as a whole including the intervening period under divergent establishment methods from 2012-14 at experimental farm of Punjab Agricultural University, Ludhiana, Punjab. Treatments included tillage in wheat viz. zero (ZTW) and conventionally tilled wheat (CTW) - main followed by establishment methods viz. direct seeded rice (DSR) and mechanically transplanted rice (MTR) - sub while tillage in rice viz. puddle (PTR), conventionally tilled (CTR) and zero tilled rice (ZTR) - sub-sub plot. Mini-lysimeters were used for delineating the evaporation trends which found to be fast, low cost, reliable and accurate. During rabi seasons, CTW plots evaporated 15.8 and 3.0% faster respectively, as compared to the ZTW plots. CTW plots during 2012-13 evaporated 7% higher than during 2013-14 while ZTW plots evaporated with almost same pace during both the years. After rabi season during intervening period, ZTW plots evaporated 6.8 and 13.6% faster than the CTW plots during 2012-13 and 2013-14, respectively. During rice seasons, among pure tillage system, zero tilled plots viz. ZTWDSRZT evaporated 21.7 and 22.2% faster than CTWDSRCT plots during rice 2013 and 2014, while coming over to the mixed tillage systems, CTWDSRZT evaporated 36.7 and 18.4% faster than the ZTWDSRCT plots. The results from this and other studies suggest that mulching suppress the evaporation losses which further improves the water use efficiency and finally land productivity of the rice-wheat sequence in the region

Delineating soil moisture dynamics as affected by tillage in wheat, Rice and establishment methods of rice during intervening period

Intervening cropping period perhaps the most ignored period, which could be exploited for cultivating the intervening crops which further add to the soil, crop and water productivity and finally livelihood of the farmers of the region. The present investigation was carried out after rice- 2014, to monitor the residual effect of different tillage (wheat), establishment methods and tillage (rice) on the fluctuating behaviour of the soil moisture during intervening period. Our findings suggested that CTW-DSRZT (conventionally tilled wheat and zero till direct seeded rice) plots conserved more moisture than ZTW-DSRZT (zero till wheat and zero till direct seeded rice) plots an exception of CTWDSRCT plots which were almost equally effective in conserving the soil moisture. On an average, soil matric tension (SMT) was reported to be 36% higher in CTWDSRZT than CTWDSRP plots at 10cm soil surface. Further, ZTW-DSRZT plots on an average dried 8% faster than ZTW-DSRP plots. At 20cm, DSRZT plots dried 3% faster than its allied plots while at 30cm depth, in DSRP plots, SMT values increased 12% and 11% higher under CTW block and ZTW blocks, respectively than its allied plots. SMT readings in all the ZTW plots on an average increased at much more faster rates (24%) than CTW plots. The ZT plots had 1.4% higher water depths than the CT plots. Evaporation losses pragmatic to be higher (17.2% and 7.3%) in ZTW-DSRZT plots as compared to the ZTW-DSRCT and CTW-DSRCT plots which might improve declining crops and water productivity in the region

Effect of oxidative stress on ABC transporters: contribution to epilepsy pharmacoresistance

Epilepsy is a neurological disorder affecting around 1%-2% of population worldwide and its treatment includes use of antiepileptic drugs to control seizures. Failure to respond to antiepileptic drug therapy is a major clinical problem and over expression of ATP-binding cassette transporters is considered one of the major reasons for pharmacoresistance. In this review, we have summarized the regulation of ABC transporters in response to oxidative stress due to disease and antiepileptic drugs. Further, ketogenic diet and antioxidants were examined for their role in pharmacoresistance. The understanding of signalling pathways and mechanism involved may help in identifying potential therapeutic targets and improving drug response

Long-Term Patterns of Air Temperatures, Daily Temperature Range, Precipitation, Grass-Reference Evapotranspiration and Aridity Index in the Usa Great Plains: Part I. Spatial Trends

Due to their substantial spatio-temporal behavior, long-term quantification and analyses of important hydrological variables are essential for practical applications in water resources planning, evaluating the water use of agricultural crop production and quantifying crop evapotranspiration patterns and irrigation management vs. hydrologic balance relationships. Observed data at over 800 sites across the Great Plains of USA, comprising of 9 states and 2,307,410 km2 of surface area, which is about 30% of the terrestrial area of the USA, were used to quantify and map large-scale and long-term (1968-2013) spatial trends of air temperatures, daily temperature range (DTR), precipitation, grass-reference evapotranspiration (ETo) and aridity index (AI) at monthly, growing season and annual time steps. Air temperatures had a strong north to south increasing trend, with annual average varying from –1 to 24°C, and growing season average temperature varying from 8 to 30°C. DTR gradually decreased from western to eastern parts of the region, with a regional annual and growing season averages of 14.25°C and 14.79°C, respectively. Precipitation had a gradual shift towards higher magnitudes from west to east, with the average annual and growing season (May-September) precipitation ranging from 163 to 1,486 mm and from 98 to 746 mm, respectively. ETo had a southwest-northeast increasing trend, with regional annual and growing season averages of 1,297 mm and 823 mm, respectively. AI increased from west to east, indicating higher humidity (less arid) towards the east, with regional annual and growing season averages of 0.49 and 0.44, respectively. The spatial datasets and maps for these important climate variables can serve as valuable background for climate change and hydrologic studies in the Great Plains region. Through identification of priority areas from the developed maps, efforts of the concerned personnel and agencies and resources can be diverted towards development of holistic strategies to address water supply and demand challenges under changing climate. These strategies can consist of, but not limited to, advancing water, crop and soil management, and genetic improvements and their relationships with the climatic variables on large scales

Maize response to coupled irrigation and nitrogen fertilization under center pivot, subsurface drip and surface (furrow) irrigation: Growth, development and productivity

Water availability and water quality problems negatively impact agricultural productivity due to improper nitrogen (N) and irrigation management, which can also negatively affect environmental services. Coupled irrigation and N management practices must be developed and practiced for alleviating these challenges. Investigating crop growth and development and yield response to coupled irrigation and N management under different irrigation methods can aid in developing optimum agronomic management practices to enhance crop production efficiency. Field experiments were conducted in 2016 and 2017 growing seasons to measure and compare maize (Zea mays L.) grain yield, leaf area index (LAI), plant height (and their relationships), and stem diameter under different N application timing treatments and traditional N application under different irrigation methods [center pivot (CP), subsurface drip irrigation (SDI), and furrow irrigation (FI)]. The irrigation levels were full irrigation treatment (FIT or 100%), 80% of FIT, 60% of FIT, and rainfed conditions (RFT) coupled with fertigation application timing treatments. The N treatments were: (i) traditional (TN) with spring pre-plant application, (ii) non-traditional-1 (NT-1) with three pre-season and in-season N applications, and (iii) nontraditional-2 (NT-2) with four pre- and in-season N applications. Grain yield, LAI, and plant height were significantly (p \u3c 0.05) altered by increasing irrigation levels for the traditional N and non-traditional N treatments for the given irrigation method as well between the irrigation methods for the same treatment. The irrigation method had a substantial influence on LAI, and both CP and SDI had 24% higher averaged LAI than FI across traditional N treatments. The highest grain yields were observed under NT-1 and NT-2 at FIT across the irrigation methods. The highest grain yields of 17.3, 16.8 and 15.2 Mg ha-1 were observed in 100% NT-1-CP, 100%-NT-1-SDI, and 100% T-FI in the 2016 growing season, respectively; and 17.8, 16.7 and 14 Mg ha-1 were observed in 100% NT-1-CP, 100%-NT-2-SDI, and 100% T-FI in the 2017 growing season, respectively. The traditional N treatment showed significantly (p \u3c 0.05) higher yield under CP than FI (8.1% and 25.5% higher under CP in 2016 and 2017, respectively). SDI had 8.1% and 23% higher yield than FI in 2016 and 2017 seasons, respectively. NT-1 and NT-2 treatments had significantly higher (p \u3c 0.05) grain yields than traditional N treatment under CP and SDI; and NT-1 and NT-2 yields were significantly higher (p \u3c 0.05) under CP than SDI. There was no significant difference (p \u3e 0.05) in yield between NT-1 and NT-2. However, the TN-1 yielded 4.3% higher under CP than in SDI method. NT-1 can be an effective N management practice coupled with 80% of FIT irrigation level under CP and SDI. Results and analyses presented here can provide guidance to growers and their advisors to assess maize productivity under different irrigation and N management strategies under different irrigation methods in the soil, climatic and management practices similar to those presented in this research

Genetic landscape of common epilepsies: advancing towards precision in treatment

Epilepsy, a neurological disease characterized by recurrent seizures, is highly heterogeneous in nature. Based on the prevalence, epilepsy is classified into two types: common and rare epilepsies. Common epilepsies affecting nearly 95% people with epilepsy, comprise generalized epilepsy which encompass idiopathic generalized epilepsy like childhood absence epilepsy, juvenile myoclonic epilepsy, juvenile absence epilepsy and epilepsy with generalized tonic-clonic seizure on awakening and focal epilepsy like temporal lobe epilepsy and cryptogenic focal epilepsy. In 70% of the epilepsy cases, genetic factors are responsible either as single genetic variant in rare epilepsies or multiple genetic variants acting along with different environmental factors as in common epilepsies. Genetic testing and precision treatment have been developed for a few rare epilepsies and is lacking for common epilepsies due to their complex nature of inheritance. Precision medicine for common epilepsies require a panoramic approach that incorporates polygenic background and other non-genetic factors like microbiome, diet, age at disease onset, optimal time for treatment and other lifestyle factors which influence seizure threshold. This review aims to comprehensively present a state-of-art review of all the genes and their genetic variants that are associated with all common epilepsy subtypes. It also encompasses the basis of these genes in the epileptogenesis. Here, we discussed the current status of the common epilepsy genetics and address the clinical application so far on evidence-based markers in prognosis, diagnosis, and treatment management. In addition, we assessed the diagnostic predictability of a few genetic markers used for disease risk prediction in individuals. A combination of deeper endo-phenotyping including pharmaco-response data, electro-clinical imaging, and other clinical measurements along with genetics may be used to diagnose common epilepsies and this marks a step ahead in precision medicine in common epilepsies management

Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

<p>Abstract</p> <p>Background</p> <p>Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose.</p> <p>Methods</p> <p>We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups.</p> <p>Results</p> <p>AD patients had a significantly reduced number of watershed regions compared to controls (<it>p </it>< 0.01). A sensitivity of 94.1% and specificity of 80% was obtained with a threshold value of 57.11 for the watershed domain number. The narrowing of the SPECT analysis to parietal regions leads to a substantial increase in both sensitivity and specificity.</p> <p>Conclusions</p> <p>Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.</p

Autonomous Irrigation Management in Decision Agriculture

In this chapter, the important application of autonomous irrigation management in the field decision agriculture is discussed. The different types of sensor-guided irrigation systems are presented that includes center pivot systems and drip irrigation systems. Their sensing and actuator components are with detailed focus on real-time decision-making and integration to the cloud. This chapter also presents irrigation control systems which takes, as an input, soil moisture and temperature from IOUT and weather data from Internet and communicate with center pivot based irrigation systems. Moreover, the system architecture is explored where development of the nodes including sensing and actuators is presented. Finally, the chapter concludes with comprehensive discussion of adaptive control systems, software, and visualization system design

Current Advances in Internet of Underground Things

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells