scholarly journals Examining Use of Sonic Bloom Technology on the Stomata Opening of Drought-Stressed Soybean

2018 ◽  
Vol 15 (4) ◽  
pp. 861-869 ◽  
Author(s):  
Istirochah Pujiwati ◽  
Bambang Guritno ◽  
Nurul Aini ◽  
Setyawan P. Sakti
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Protein Content ◽  
Nutrient Uptake ◽  
Sound Wave ◽  
Soil Moisture Content ◽  
Phosphorus Uptake ◽  
Soybean Seed ◽  
Stomatal Opening ◽  
Wave Frequency

Sonic bloom is a technology that combines high frequency sound waves and organic nutrients, intended for better plant growth to increase its productivity. This study aimed to determine the effect of sound wave frequency and drought stress on stomatal opening, nutrient uptake efficiency through leaf, and soybean yield. We designed the research as a split plot experiment. The main plot was sound wave frequency consisting of four levels (no frequency imposed, frequencies 2, 4 and 6 kHz. The sub-plot was three soil moisture contents (50,75, and 100% field capacity). We found that the interaction of frequency and soil moisture content affected the width of stomata at the age of 30,40 and 50 days after planting (dap), the efficiency of nitrogen uptake, phosphorus uptake and potassium uptake and the protein content of seeds. The width of stomatal opening at a frequency of 4 kHz in soil moisture 100% FC showed the highest value and was not significantly different from soil moisture 75% FC. There was a positive correlation between exposure to plants with a frequency of 4 kHz with stomatal opening, nutrient uptake and increased yield of soybean crops. The use of sonic bloom technology with plant exposure at a frequency of 4 kHz could increase drought tolerance to 75% soil moisture content. Soybean seed yield increased by 40.89% and seed protein content increased by 10.3%.

scholarly journals THE EFFECT OF VARYING ROW SPACINGS ON THE AGRONOMIC AND QUALITY CHARACTERISTICS OF CEREALS AND FLAX

1963 ◽  
Vol 43 (2) ◽  
pp. 119-130 ◽  
Author(s):  
L. B. Siemens
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Protein Content ◽  
Soil Moisture Content ◽  
Quality Characteristics ◽  
Kernel Weight ◽  
Row Spacing ◽  
Kernel Weights

During a 3-year study (1957–1959) at three Manitoba locations, agronomic and quality characteristics of Selkirk wheat, Garry oats, Swan barley and Raja flax were studied when crops were seeded in rows spaced 6, 12, 18, 24 and 30 inches apart. Within crops the same seedling rate per row was used for all spacings.A row spacings increased from 6 to 30 inches, yields of all crops gradually declined whereas tillering and seed return increased. The 1000-kernel weight of barley increased substantially with wider row spacings, but in wheat and flax the lowest 1000-kernel weights were recorded at the widest spacing. The kernel weight of oats and the bushel weight of all crops were not affected noticeably by row spacing. Protein content of wheat at 30-inch spacing averaged 3.2 per cent higher than wheat at 6-inch spacing. Protein in barley and flax also appeared to increase at wider row spacings, but not as sharply as in wheat.Average soil moisture content between 30-inch flax rows was higher at the time of boll formation than between 6- and 18-inch rows. A similar trend was found in wheat at time of heading.Wheat variety by spacing interactions was studied in one test in which Lerma, Lee, Thatcher and Selkirk wheats were seeded in rows spaced 6, 12, 18, 24 and 30 inches apart. No significant interactions were observed in tillering and protein content, whereas interactions in yield and 1000-kernel weights were highly significant.

The effects of fluctuations in soil moisture content on the availability of recently applied phosphate

Soil Research ◽  
1970 ◽  
Vol 8 (2) ◽  
pp. 209 ◽  
Author(s):  
JR Simpson ◽  
CH Williams
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Plant Uptake ◽  
Soil Moisture Content ◽  
Phosphorus Uptake ◽  
Organic Substrate ◽  
High Moisture Content ◽  
High Moisture ◽  
Phosphate Availability ◽  
Reduction Of Iron

Incubation for short periods at a high moisture content reduced the subsequent plant uptake of phosphorus from recently applied monocalcium phosphate in several soils. The effects on phosphorus uptake were reflected in the amounts of phosphate extracted by 0.5M sodium bicarbonate and by 0.01M calcium chloride. Phosphate availability decreased with increasing moisture content up to saturation. At saturation, availability decreased with increasing incubation period up to 4 days, but was not reversed by several weeks of subsequent incubation at 100 cm tension. The effect of waterlogging usually was greater on the air-dried soil than on soil which had undergone moist pre-incubation. The results suggest that the decrease in phosphate availability was closely associated with the reduction of iron during the anaerobic phase and its subsequent oxidation. Preincubation at 100 cm tension progressively decreased the amount of iron released, and phosphate subsequently immobilized. This appeared to be caused by oxidation of organic substrate during the aerobic phase, thus delaying the onset of anaerobiosis during waterlogging. Phosphate applied to the surface was affected by waterlogging in a similar way to phosphate mixed into the soil.

Analysis on Soil Moisture Content in the Middle Reaches of the Yellow River

2011 ◽  
Vol 28 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Run-chun LI ◽  
Xiu-zhi ZHANG ◽  
Li-hua WANG ◽  
Xin-yan LV ◽  
Yuan GAO
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Yellow River ◽  
The Yellow River

Distribution of soil moisture content and its effect on the potential growth of the over-story species in North-East Chalkidiki

2001 ◽  
Vol 66 ◽  
Author(s):  
M. Aslanidou ◽  
P. Smiris
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Moisture Distribution ◽  
Taxus Baccata ◽  
Mixed Stands ◽  
Potential Growth ◽  
North East ◽  
Soil Moisture Distribution

This  study deals with the soil moisture distribution and its effect on the  potential growth and    adaptation of the over-story species in north-east Chalkidiki. These  species are: Quercus    dalechampii Ten, Quercus  conferta Kit, Quercus  pubescens Willd, Castanea  sativa Mill, Fagus    moesiaca Maly-Domin and also Taxus baccata L. in mixed stands  with Fagus moesiaca.    Samples of soil, 1-2 kg per 20cm depth, were taken and the moisture content  of each sample    was measured in order to determine soil moisture distribution and its  contribution to the growth    of the forest species. The most important results are: i) available water  is influenced by the soil    depth. During the summer, at a soil depth of 10 cm a significant  restriction was observed. ii) the    large duration of the dry period in the deep soil layers has less adverse  effect on stands growth than in the case of the soil surface layers, due to the fact that the root system mainly spreads out    at a soil depth of 40 cm iii) in the beginning of the growing season, the  soil moisture content is    greater than 30 % at a soil depth of 60 cm, in beech and mixed beech-yew  stands, is 10-15 % in    the Q. pubescens  stands and it's more than 30 % at a soil depth of 60 cm in Q. dalechampii    stands.

scholarly journals Mapping barrier island soil moisture using a radiative transfer model of hyperspectral imagery from an unmanned aerial system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rehman S. Eon ◽  
Charles M. Bachmann
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Moisture Content ◽  
Layer Thickness ◽  
Soil Moisture Content ◽  
Hyperspectral Imagery ◽  
Barrier Island ◽  
Water Layer ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractThe advent of remote sensing from unmanned aerial systems (UAS) has opened the door to more affordable and effective methods of imaging and mapping of surface geophysical properties with many important applications in areas such as coastal zone management, ecology, agriculture, and defense. We describe a study to validate and improve soil moisture content retrieval and mapping from hyperspectral imagery collected by a UAS system. Our approach uses a recently developed model known as the multilayer radiative transfer model of soil reflectance (MARMIT). MARMIT partitions contributions due to water and the sediment surface into equivalent but separate layers and describes these layers using an equivalent slab model formalism. The model water layer thickness along with the fraction of wet surface become parameters that must be optimized in a calibration step, with extinction due to water absorption being applied in the model based on equivalent water layer thickness, while transmission and reflection coefficients follow the Fresnel formalism. In this work, we evaluate the model in both field settings, using UAS hyperspectral imagery, and laboratory settings, using hyperspectral spectra obtained with a goniometer. Sediment samples obtained from four different field sites representing disparate environmental settings comprised the laboratory analysis while field validation used hyperspectral UAS imagery and coordinated ground truth obtained on a barrier island shore during field campaigns in 2018 and 2019. Analysis of the most significant wavelengths for retrieval indicate a number of different wavelengths in the short-wave infra-red (SWIR) that provide accurate fits to measured soil moisture content in the laboratory with normalized root mean square error (NRMSE)< 0.145, while independent evaluation from sequestered test data from the hyperspectral UAS imagery obtained during the field campaign obtained an average NRMSE = 0.169 and median NRMSE = 0.152 in a bootstrap analysis.

scholarly journals Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

2021 ◽  
Vol 13 (8) ◽  
pp. 1562
Author(s):  
Xiangyu Ge ◽  
Jianli Ding ◽  
Xiuliang Jin ◽  
Jingzhe Wang ◽  
Xiangyue Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Soil Moisture ◽  
Moisture Content ◽  
Hyperspectral Imaging ◽  
Fractional Order ◽  
Arid Regions ◽  
Soil Moisture Content ◽  
Order Derivative ◽  
Imaging Data ◽  
Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

scholarly journals A GNSS-IR Method for Retrieving Soil Moisture Content from Integrated Multi-Satellite Data That Accounts for the Impact of Vegetation Moisture Content

2021 ◽  
Vol 13 (13) ◽  
pp. 2442
Author(s):  
Jichao Lv ◽  
Rui Zhang ◽  
Jinsheng Tu ◽  
Mingjie Liao ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Satellite Data ◽  
Vegetation Index ◽  
Soil Moisture Content ◽  
Support Vector ◽  
Observation Data ◽  
Multipath Effect ◽  
Mars Model ◽  
The Impact

There are two problems with using global navigation satellite system-interferometric reflectometry (GNSS-IR) to retrieve the soil moisture content (SMC) from single-satellite data: the difference between the reflection regions, and the difficulty in circumventing the impact of seasonal vegetation growth on reflected microwave signals. This study presents a multivariate adaptive regression spline (MARS) SMC retrieval model based on integrated multi-satellite data on the impact of the vegetation moisture content (VMC). The normalized microwave reflection index (NMRI) calculated with the multipath effect is mapped to the normalized difference vegetation index (NDVI) to estimate and eliminate the impact of VMC. A MARS model for retrieving the SMC from multi-satellite data is established based on the phase shift. To examine its reliability, the MARS model was compared with a multiple linear regression (MLR) model, a backpropagation neural network (BPNN) model, and a support vector regression (SVR) model in terms of the retrieval accuracy with time-series observation data collected at a typical station. The MARS model proposed in this study effectively retrieved the SMC, with a correlation coefficient (R2) of 0.916 and a root-mean-square error (RMSE) of 0.021 cm3/cm3. The elimination of the vegetation impact led to 3.7%, 13.9%, 11.7%, and 16.6% increases in R2 and 31.3%, 79.7%, 49.0%, and 90.5% decreases in the RMSE for the SMC retrieved by the MLR, BPNN, SVR, and MARS model, respectively. The results demonstrated the feasibility of correcting the vegetation changes based on the multipath effect and the reliability of the MARS model in retrieving the SMC.

Multi-algorithm comparison to predict soil organic matter and soil moisture content from cell phone images

Geoderma ◽  
2021 ◽  
Vol 385 ◽  
pp. 114863
Author(s):  
Perry Taneja ◽  
Hitesh Kumar Vasava ◽  
Prasad Daggupati ◽  
Asim Biswas
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Soil Organic Matter ◽  
Moisture Content ◽  
Cell Phone ◽  
Soil Moisture Content ◽  
Algorithm Comparison
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