scholarly journals Electrical Properties Predict Wheat Leaf Moisture

2021 ◽  
Vol 64 (3) ◽  
pp. 929-936
Author(s):  
Yumei Hao ◽  
Yuantao Hua ◽  
Xu Li ◽  
Xianqiang Gao ◽  
Jilong Chen
Keyword(s):  
Electrical Properties ◽  
Moisture Content ◽  
Real Time ◽  
Standard Error ◽  
Parameter Method ◽  
Wheat Leaf ◽  
Wheat Leaves ◽  
Non Destructive ◽  
Precision Irrigation ◽  
Southern Xinjiang

HighlightsA non-destructive prediction model for moisture content of wheat leaves was established based on electrical properties.The model based on a single property (capacitance or resistance) was improved by using both properties.The model accurately detected the moisture content of wheat leaves in real-time to avoid irrigation lag.The results provide a basis for real-time and targeted water-saving irrigation of winter wheat in an arid region.Abstract. In this study, we aimed to establish a non-destructive and rapid approach to monitor the moisture content of wheat leaves in Southern Xinjiang, China, and promptly acquire information on the physiological water demand of crops to guide precision irrigation. Wheat leaves were used as the research object. Using a custom-made clamped parallel-plate capacitor and LCR digital bridge meter, we determined the electrical properties (capacitance and resistance) of wheat leaves with various moisture contents within a frequency range from 0.12 to 100 kHz. Moreover, we explored the correlation between leaf moisture content and the electrical properties. Our data showed that leaf moisture exhibited the best correlation with the electrical properties at 50 kHz. Under these optimized conditions, a model for moisture measurement was established using a single-parameter method (capacitance or resistance). However, the estimated standard errors (RMSE) of this method were 3.29% (for resistance) and 3.49% (for capacitance), which were greater than the standard error of the measured moisture content (2%). Therefore, we developed an improved model using a two-parameter method (capacitance and resistance), and the estimated standard error was 2.68%, which was more feasible for predicting moisture content compared with the single-parameter method. The model was validated using eight groups of wheat leaf samples at the turning-green stage and the jointing stage, and the RMSE values were less than 2%. Our findings provide a scientific basis for real-time and targeted water-saving irrigation of wheat in arid areas of Southern Xinjiang. Keywords: Electrical property, Model, Moisture content, Precision irrigation, Wheat leaves.

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

scholarly journals Moisture Measurement in Paper and Cardboard Packaging Waste Bales for Recycling

2021 ◽  
Vol 11 (10) ◽  
pp. 4586
Author(s):  
Ana Silveira ◽  
João Cardoso ◽  
Maria José Correia ◽  
Graça Martinho
Keyword(s):  
Quality Control ◽  
Dielectric Properties ◽  
Moisture Content ◽  
Reliable Method ◽  
Drying Method ◽  
Waste Streams ◽  
Oven Drying ◽  
Quality Issue ◽  
Commercial Device ◽  
Non Destructive

Moisture content is a quality issue raised by recycling plants in the acceptance of paper and cardboard coming from waste streams. The current way to measure this parameter is by the oven drying method, which is a slow and invasive process, costing time and resources for the recyclers to do this type of quality control. An alternative to such a measurement technique is the use of plate-form devices which indirectly measure the moisture content using the dielectric properties of water and paper. This study has tested this method and developed a representative equation for the use of devices with these properties in the Portuguese market. For that, 48 wastepaper and cardboard bales were tested with both the traditional (oven drying) method and a commercial device equipped with dielectric technology. An equation that fits the studied reality (R2 = 0.76) was achieved, and possible problems regarding the use of this device were tested. The results showed that this type of device could be used as a time- and cost-saving, non-destructive and reliable method in the quality control of wastepaper and cardboard bales.

Developing an electronic portable device based on dielectric power spectroscopy for non-destructive prediction of date moisture content

2016 ◽  
Vol 247 ◽  
pp. 289-297 ◽  
Author(s):  
Seyed Ahmad Mireei ◽  
Rahmatollah Bagheri ◽  
Morteza Sadeghi ◽  
Ali Shahraki
Keyword(s):  
Moisture Content ◽  
Portable Device ◽  
Non Destructive

Identification prediction moisture content of Thai coconut sugar (Cocos nucifera L.) using FT-NIR spectroscopy

Food Research ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 382-385
Author(s):  
D. Thumrongchote
Keyword(s):  
Moisture Content ◽  
Cocos Nucifera ◽  
Nir Spectroscopy ◽  
Grocery Stores ◽  
Absorbance Spectrum ◽  
Coconut Tree ◽  
Cocos Nucifera L ◽  
The Cost ◽  
Non Destructive ◽  
Low Glycemic Index

Coconut sugar is a local sugar from the blossoms of a coconut tree. It has been considered a healthy sugar due to its low glycemic index. There is an attempt to add other sugar to it to lower the cost. Thus, this research aimed to identify Thai coconut sugar and to establish models for predicting the moisture content of coconut sugar by using FT-NIR spectroscopy. Thai coconut sugar samples were purchased from local grocery stores in four provinces, online, and the community market. Their moisture contents were varied and equilibrated for 24 hrs prior to the measurements of moisture and FT-NIR spectra. The results showed that FT-NIR spectra of Thai coconut sugar differ from sucrose, glucose and fructose at the absorbance spectrum of 5379-5011 cm-1 . FT-NIR spectroscopy of 54 known moisture samples of Thai coconut sugar was used to obtain a model to predict moisture content. The predicted equation, using the PLS technique with the Spectrum Quant program, was found to give a standard error of prediction (SEP) 0.077% (less than 0.10%), indicating a non-destructive method of accurately and precisely predicting moisture levels in the coconut sugar. The results obtained suggested that FTNIR spectroscopy has the potential to be used as a tool to identify Thai coconut sugar accurately. It can rapidly predict the moisture content in the sample which will be useful in quality control standards.

scholarly journals Association of Pestalotiopsis Guepinii (DESM.) Stay. with Bipolaris Leaf Blight (BpLB) Infected Wheat Leaves-A new Record

2016 ◽  
Vol 40 (1) ◽  
pp. 87-90
Author(s):  
Shamim Shamsi ◽  
Mst Selina Momtaz
Keyword(s):  
New Record ◽  
Leaf Blight ◽  
Wheat Varieties ◽  
Anamorphic Fungus ◽  
Wheat Leaf ◽  
Wheat Leaves ◽  
Academy Of Sciences

Pestalotiopsis guepinii (Desm.) Stay an anamorphic fungus belonging to the class Celomycetes was isolated from Bipolaris leaf blight (BpLB) infected wheat leaf of two wheat varieties namely, Balaka and Saurab during the period of February to March, 2011. Association of Pestalotiopsis guepinii with wheat is a new record.Journal of Bangladesh Academy of Sciences, Vol. 40, No. 1, 87-90, 2016

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