PVA Treated PEDOT-PSS: TiO2 Nanocomposite Based High-Performance Sensors Towards Detection of Relative Humidity and Soil Moisture Content for Agricultural Applications

2020 ◽  
Author(s):  
Syed Khasim ◽  
Apsar Pasha ◽  
Nacer Badi ◽  
Mohana Lakshmi ◽  
S. A. Al-Ghamdi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Moisture Content ◽  
High Performance ◽  
Soil Moisture Content ◽  
Agricultural Applications

scholarly journals Synchrony in Leafing, Flowering, and Fruiting Phenology ofSenegalia senegalwithin Lake Baringo Woodland, Kenya: Implication for Conservation and Tree Improvement

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Stephen F. Omondi ◽  
David W. Odee ◽  
George O. Ongamo ◽  
James I. Kanya ◽  
Damase P. Khasa
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Floral Morphology ◽  
Tree Improvement ◽  
Flowering Period ◽  
Leaf Fall ◽  
Senegalia Senegal ◽  
Seed Collections

Leafing, flowering, and fruiting patterns ofSenegalia senegalwere studied over a period of 24 months from January 2014 to December 2015. The phenological events of the species are bimodal and follow the rainfall patterns. The leafing phase starts during the onset of rains and lasts for 18 weeks. New leaves continued to appear on the new shoots while old leaves persisted to the leaf fall period. Flowering event takes 12 weeks and is concentrated in the months of high relative humidity (April and October) with one-month peak flowering period. Fruiting phase starts at the peak of the rainy seasons (May and November) and peaks in June and December. This phase lasted for 14 weeks. The fruits mature towards the end of the rainy season (January/February and July/August). The fruits open for dispersal mainly in February/March and September during the peak dry season. High synchrony index (SI) was found in leafing (SI: 0.87), flowering (SI: 0.75), and fruiting (SI: 0.85) events among the populations. Temperature, precipitation, and soil moisture content were significantly correlated with the phenological events. Significant variations in floral morphology and fruits traits were also evident. Seed collections should be undertaken in the months of January/February and July/August.

scholarly journals Soil Moisture and Turgidity of Selected Robusta Coffee Clones on Alluvial Plain with Seasonal Rainfall Pattern

2005 ◽  
Vol 21 (2) ◽  
Author(s):  
Rudy Erwiyono
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Alluvial Plain ◽  
Experimental Site ◽  
Rooted Cuttings ◽  
Soil Layers ◽  
Robusta Coffee ◽  
Coffee Plants

Observation on the seasonal variations of hydrological condition and turgidity of selected Robusta coffee clones has been carried out in Kaliwining Experimental Station, Indonesian Coffee and Cocoa Research Institute in Jember. The aim was to evaluate the effect of hydrological variation on the coffee plants and the degree of soil moisture effect on plant performance. Experimental site overlays on alluvial plain, + 45 m a.s.l., 8o 15’ South with D rainfall type. Observation was conducted by survey method at the experimental plots of organic fertilizer and nitogen treatments on selected Robusta coffee clones derived from rooted cuttings, i.e. BP 436, BP 42, BP 936 and BP 358. Observation was only conducted at the experimental blocks of organic matter trials of 20 l/tree/year at nitrogen (Urea) application of locally recommanded rate during the subsequent years of 1999 to 2001. Parameters observed included plant turgidity and soil moisture content of three different depths, i.e. 0—20, 20—40 and 40—60 cm and the weather. Observation was carried out in five replicates designed as blocks of barn manure treatment and N-fertilizer of recommended rate as basal fertilizer. The results showed that meteorological condition and soil moisture of experimental site through the years have seasonal patterns following the seasonal pattern of rainfall. Compared to other meteorological characteristics, relative humidity dominantly determined evaporation and plant turgidity. Plant turgi-dity was not only determined by soil moisture condition, but also atmospheric demand. When relative humidity (RH) was relatively high, plant turgidity was relatively stable although soil moisture of surface layers was very low, and the reversal when soil moisture content was high plant turgidity was controlled by atmospheric demand (relative humidity). With a 3—4 dry month period, relative turgidity of the coffee plants was relatively stable above 82%, except when soil moisture of 60 cm surface layer was below 25% (w/w) and or atmospheric demand was relatively high (RH 85%). Soil moisture contents of deeper soil layers seemed to have greater impact on the plant turgidity and the deeper the soil layers the narrower the seasonal variation of their soil moisture contents. Selected different clones originated from rooted cuttings showed different response to water stress and could be put in order from the most sensitive to water stress as follows BP 436, BP 42, BP 936 and BP 358. Barn manure application could significantly increase soil moisture content but its influence could not significantly increase plant turgidity.Key words : Seasonal variation, atmospheric condition, soil moisture, plant turgidity, Robusta coffee clones.

scholarly journals Variation Characteristics and Influencing Factors of Soil Moisture Content in the Lime Concretion Black Soil Region in Northern Anhui

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2251
Author(s):  
Mingcheng Du ◽  
Jianyun Zhang ◽  
Amgad Elmahdi ◽  
Zhenlong Wang ◽  
Qinli Yang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Crop Growth ◽  
Groundwater Depth ◽  
Factors Affecting ◽  
Moisture Variation ◽  
Main Factors ◽  
Soil Moisture Variation

Soil moisture content (SMC) is an important factor affecting crop growth. Based on the field SMC data measured at the Wudaogou experimental station from 1989 to 2019, two typical crop types, wheat and maize, were selected. By combining the groundwater depth, crop growth period, and meteorological factors in the same period, and using classical statistics and redundant analysis (RDA) methods, the characteristics and influencing factors of SMC changes in vertical profiles of different crops were compared and analyzed. The results showed that the SMC and average daily water storage of wheat were greater than that of maize. The crop growth mainly consumed 0–60 cm SMC. The SMC in this area was moderately variable; the SMC of 0–30 cm belongs to the active layer, and the SMC of 30–100 cm belongs to the sub-active layer. The RDA method identified ground temperature, groundwater depth, relative humidity, and the wheat growing period as the main factors affecting soil moisture variation in wheat fields; groundwater depth, relative humidity, and water vapor pressure differences were the main factors affecting soil moisture variation in maize fields. The results can provide a basis for accurate prediction of soil water dynamics and thus provide a reference for irrigation decision-makers.

CYTOSPORA CANKER OF POPLARS: FACTORS INFLUENCING THE DEVELOPMENT OF THE DISEASE

1962 ◽  
Vol 40 (10) ◽  
pp. 1271-1280 ◽  
Author(s):  
W. J. Bloomberg
Keyword(s):  
Soil Moisture ◽  
Relative Humidity ◽  
Moisture Content ◽  
Incubation Period ◽  
Soil Moisture Content ◽  
Populus Trichocarpa ◽  
Factors Influencing ◽  
Cytospora Chrysosperma ◽  
Moisture Deficit ◽  
Cytospora Canker

The effects of shoot moisture content, region of shoot, age of shoot, temperature, relative humidity, and soil moisture content on the development of cankers caused by Cytospora chrysosperma (Pers.) Fr. were studied in Populus trichocarpa Torr. and Gray, P. × canadensis Moench 'Regenerata', and P. × canadensis 'Robusta Bachelieri'. Within the range studied, canker growth varied proportionally with temperature, and inversely with shoot moisture content, relative humidity, and soil moisture content. Canker growth was greater in P. trichocarpa than in the two hybrids, which did not differ significantly from each other. Canker growth was less in 8-month-old than in 10- and 12-month-old shoots of the hybrids, but cankers on P. trichocarpa showed no differences in this respect. The critical bark moisture deficit for infection was least in P. trichocarpa, intermediate in P. 'Regenerata', and greatest in P. 'Robusta'. The critical bark moisture deficit was greater, and the incubation period was shorter, in the upper part than in the lower part of the shoot.

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.

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