scholarly journals Social Comparisons in Real Time: A Field Experiment of Residential Electricity and Water Use

2017 ◽  
Author(s):  
Andrius Kaaukauskas ◽  
Thomas Broberg ◽  
Jurate Jaraite
Keyword(s):  
Field Experiment ◽  
Real Time ◽  
Water Use ◽  
Social Comparisons ◽  
Residential Electricity

scholarly journals Soil moisture depletion and ground water use by bed planted barley as influenced by cultivars, crop geometry and moisture regimes

2017 ◽  
Vol 9 (3) ◽  
pp. 1465-1468 ◽  
Author(s):  
Naveen Kumar ◽  
Suresh Kumar ◽  
Parveen Kumar ◽  
Meena Sewhag
Keyword(s):  
Soil Moisture ◽  
Field Experiment ◽  
Ground Water ◽  
Water Use ◽  
Moisture Regime ◽  
Rabi Season ◽  
Shallow Water Table ◽  
Moisture Regimes ◽  
Crop Geometry ◽  
Plot Design

A field experiment was conducted during rabi season 2011-2012 at Research Farm, CCS Haryana Agri-cultural University, Hisar, Haryana (India) to study the periodic soil moisture depletion and ground water use by bed planted barley as influenced by cultivars, crop geometry and moisture regimes under shallow water table conditions. The experiment was laid out in split plot design with three replications keeping combinations of three cultivars viz., BH 393, BH 902 and BH 885 and two crop geometries viz 2 rows per bed and 3 rows per bed (70 cm wide with 40 cm top and 30 cm furrow) in main plots and three moisture regimes (irrigation at IW/CPE 0.3, 0.4 & 0.5) in sub plots. The results revealed that maximum soil moisture depletion (105 mm) and ground water contribution (62 mm) were recorded in BH 902, followed by BH 393 and BH 885. Among crop geometries, soil moisture depletion (96.6 mm) and ground water contribution (61 mm) were recorded higher in 3 rows per bed than 2 rows per bed. Among three moisture regimes, the soil moisture depletion (108 mm) and ground water contribution (65 mm) decreased with increase in moisture regime from irrigation at IW/CPE 0.3 to irrigation at IW/CPE 0.4 or 0.5.

scholarly journals Yield and Yield Attributing Parameters of Toria (Brassica campestries) under Real Time Rainfall Situation in an Inceptisols of Assam, India

2020 ◽  
pp. 311-321
Author(s):  
R. Borah ◽  
N. Baruah ◽  
P. K. Sarma ◽  
R. Borah ◽  
A. Sonowal ◽  
...  
Keyword(s):  
Field Experiment ◽  
Real Time ◽  
Seed Yield ◽  
Seed Weight ◽  
Growth Yield ◽  
Rabi Season ◽  
Higher Plant ◽  
College Of Agriculture ◽  
Sowing Dates ◽  
Stover Yield

A field experiment was conducted during rabi season of 2018-19 and 2019-20 in Dryland experimental field belong to soil order Inceptisols, Biswanath college of Agriculture, Assam Agricultural University, Biswanath chariali, Assam to study the ‘‘Yield and yield attributing parameters of toria (Brassica campestries) under real time rainfall situation in an Inceptisols of Assam, India’’ under AICRPDA, NICRA. The treatments consisting of 4 different dates of sowing i.e. S1-41th SMW, S2-44th SMW, S3-46th SMW, and S4- 48th SMW, & three variety i.e. V1-JT-90-1(Jeuti), V2-Yellow sarson (Benoy) and V3- TS-38. Growth, yield and yield attributing characters of toria varieties were influenced by different dates of sowing. S1 registered higher plant height (43.2 cm, 92.9 cm and 106.6 cm & 40.2 cm, 89.8 cm and 101.5 cm) and number of branch (3.8, 5.3 and 7.2 & 3.4, 5.1 and 6.9) at 30 DAS, 45 DAS and 60 DAS, respectively, during 2018-19 and 2019-20. Yield attributing characters like number of siliqua, number of seed per siliqua, 1000 seed weight (g) were gradually decreased with advancement of sowing dates. Among the three varieties V1 (Jeuti) recorded highest seed yield (8.9 q ha-1 and 8.1 q ha-1) and stover yield (23.4 q ha-1 and 22.2 q ha-1) in 2018-19 and 2019-20, respectively. Highest HI (28.5% and 25.8%) was recorded in S1 and lowest was recorded in S4 (20.7% and 14.6%).

scholarly journals How managers can reduce household water use through communication: A field experiment

2020 ◽  
Author(s):  
Heather Hodges ◽  
Colin Kuehl ◽  
Sarah E. Anderson ◽  
Phillip John Ehret ◽  
Cameron Brick
Keyword(s):  
Field Experiment ◽  
Water Use ◽  
Cost Effective ◽  
High Water ◽  
Single Family ◽  
Residential Water Use ◽  
Household Water ◽  
Average Water ◽  
Water District ◽  
Residential Water

As populations increase and droughts intensify, water providers are using tools such as persuasive messaging to decrease residential water use. However, district-led messaging campaigns are rarely informed by psychological science, evaluated for effectiveness, or strategically disseminated. In collaboration with a water district, we report a field experiment among single-family households using persuasive messaging based on the information-motivation-behavioral skills model (IMB). We randomly assigned 10,000 households to receive different mailings and measured household water use. All messaging reduced water consumption relative to the control. On average, water use dropped 0.68 HCF (509 gallons) per household in the first month. Had all 10,000 single-family, occupied, non-agricultural residences been mailed the IMB messaging, more than 5 million gallons would have been saved in the first month. The effects declined but persisted for approximately three months and were three to six times greater in households with high water use (75th-90th percentiles) relative to average water use. These findings suggest that combining message elements from the IMB model can reduce residential water use and that targeting high-use households is particularly cost-effective.

scholarly journals Watson on the Farm: Using Cloud-Based Artificial Intelligence to Identify Early Indicators of Water Stress

2019 ◽  
Vol 11 (22) ◽  
pp. 2645 ◽  
Author(s):  
Daniel Freeman ◽  
Shaurya Gupta ◽  
D. Hudson Smith ◽  
Joe Mari Maja ◽  
James Robbins ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Water Stress ◽  
Real Time ◽  
Water Use ◽  
Visual Recognition ◽  
Small Sample ◽  
Unmanned Aircraft ◽  
Minimal Amount ◽  
Sustainable Water Use ◽  
Early Indicators

As demand for freshwater increases while supply remains stagnant, the critical need for sustainable water use in agriculture has led the EPA Strategic Plan to call for new technologies that can optimize water allocation in real-time. This work assesses the use of cloud-based artificial intelligence to detect early indicators of water stress across six container-grown ornamental shrub species. Near-infrared images were previously collected with modified Canon and MAPIR Survey II cameras deployed via a small unmanned aircraft system (sUAS) at an altitude of 30 meters. Cropped images of plants in no, low-, and high-water stress conditions were split into four-fold cross-validation sets and used to train models through IBM Watson’s Visual Recognition service. Despite constraints such as small sample size (36 plants, 150 images) and low image resolution (150 pixels by 150 pixels per plant), Watson generated models were able to detect indicators of stress after 48 hours of water deprivation with a significant to marginally significant degree of separation in four out of five species tested (p < 0.10). Two models were also able to detect indicators of water stress after only 24 hours, with models trained on images of as few as eight water-stressed Buddleia plants achieving an average area under the curve (AUC) of 0.9884 across four folds. Ease of pre-processing, minimal amount of training data required, and outsourced computation make cloud-based artificial intelligence services such as IBM Watson Visual Recognition an attractive tool for agriculture analytics. Cloud-based artificial intelligence can be combined with technologies such as sUAS and spectral imaging to help crop producers identify deficient irrigation strategies and intervene before crop value is diminished. When brought to scale, frameworks such as these can drive responsive irrigation systems that monitor crop status in real-time and maximize sustainable water use.

Effect of LCC-based nitrogen application on growth and yieldof rice (Oryza sativa L.) varieties during dry season

2016 ◽  
Vol 51 (1) ◽  
Author(s):  
Shrabani Moharana ◽  
J.M. L. Gulati ◽  
S. N. Jena
Keyword(s):  
Oryza Sativa ◽  
Field Experiment ◽  
Grain Yield ◽  
Real Time ◽  
Oryza Sativa L ◽  
Threshold Value ◽  
Nitrogen Management ◽  
Nitrogen Application ◽  
Panicle Length ◽  
Straw Yield

Data from a field experiment on Real Time Nitrogen Management (RTNM) in rice revealed that variety Gobinda produced significantly the highest grain yield of 49.6 q ha-1 associated with long panicle (26.75 cm) bearing significantly the maximum number of filled grains panicle-1 (156.78) producing highest net return (Rs.33214.71), B-C ratio (1.83) and return per rupee invested (0.83). Application of nitrogen based on LCC threshold value 4 produced significantly the highest grain (52.6 q ha-1), straw yield (64.4 q ha-1), number of EBT m-2 (403.71), panicle length (25.43 cm) and 148.94 filled grain panicle-1. Variety x RTNM interaction was significant and variety Naveen and Gobinda produced significantly the highest yield of 55.4 and 58.2 q ha-1 at recommended of nitrogen whereas, Lalat and Hiranmayee responded to LCC threshold value 4 (N4) with grain yield of 50.4 and 52.1 q ha-1, respectively.

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