scholarly journals Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress

2021 ◽  
Vol 13 (2) ◽  
pp. 250
Author(s):  
Kangying Zhu ◽  
Zhigang Sun ◽  
Fenghua Zhao ◽  
Ting Yang ◽  
Zhenrong Tian ◽  
...  
Keyword(s):  
Salt Stress ◽  
Water Resources ◽  
Winter Wheat ◽  
Soil Salinity ◽  
Brackish Water ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Soil Layer ◽  
Hyperspectral Data ◽  
Irrigation Systems

Abundant shallow underground brackish water resources could help in alleviating the shortage of fresh water resources and the crisis concerning agricultural water resources in the North China Plain. Improper brackish water irrigation will increase soil salinity and decrease the final yield due to salt stress affecting the crops. Therefore, it is urgent to develop a practical and low-cost method to monitor the soil salinity of brackish irrigation systems. Remotely sensed spectral vegetation indices (SVIs) of crops are promising proxies for indicating the salinity of the surface soil layer. However, there is still a challenge concerning quantitatively correlating SVIs with the salinity of deeper soil layers, in which crop roots are mainly distributed. In this study, a field experiment was conducted to investigate the relationship between SVIs and salinity measurements at four soil depths within six winter wheat plots irrigated using three salinity levels at the Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences during 2017–2019. The hyperspectral reflectance was measured during the grain-filling stage of winter wheat, since it is more sensitive to soil salinity during this period. The SVIs derived from the observed hyperspectral data of winter wheat were compared with the salinity at four soil depths. The results showed that the optimized SVIs, involving soil salt-sensitive blue, red-edge, and near-infrared wavebands, performed better when retrieving the soil salinity (R2 ≥ 0.58, root mean square error (RMSE) ≤ 0.62 g/L), especially at the 30-cm depth (R2 = 0.81, RMSE = 0.36 g/L). For practical applications, linear or quadratic models based on the screened SVIs in the form of normalized differential vegetation indices (NDVIs) could be used to retrieve soil salinity (R2 ≥ 0.63, RMSE ≤ 0.62 g/L) at all soil depths and then diagnose salt stress in winter wheat. This could provide a practical technique for evaluating regional brackish water irrigation systems.

scholarly journals Effects of Irrigating with Brackish Water on Soil Moisture, Soil Salinity, and the Agronomic Response of Winter Wheat in the Yellow River Delta

2019 ◽  
Vol 11 (20) ◽  
pp. 5801 ◽  
Author(s):  
Wang ◽  
Xu ◽  
Pang
Keyword(s):  
Soil Moisture ◽  
Salt Stress ◽  
Winter Wheat ◽  
Fresh Water ◽  
Soil Salinity ◽  
Brackish Water ◽  
Yellow River ◽  
Yellow River Delta ◽  
River Delta ◽  
Filling Stage

Water shortages due to low precipitation and seawater intrusion in the Lower China Yellow River Delta have occurred in recent years. Exploiting underground brackish water through well drilling is a potential alternative way to satisfy the demand for agricultural irrigation. However, how to successfully use brackish water for irrigation has become a new problem to solve. A two-year field experiment was conducted in this typical saline-alkaline region to investigate the effects of irrigating with brackish water on the soil water-salt dynamics, and the physiological response of winter wheat to drought-salt stress. The experiment was laid out in a randomized block design with three replications according to the quantity (160 mm and 240 mm) and quality (fresh water and brackish water with a salt concentration of 3 g L-1) of irrigation water: T1 was 240 mm of fresh water, T2 was 160 mm of fresh water, T3 was 80 mm of fresh water and 160 mm of brackish water, and T4 was 80 mm of fresh water and 80 mm of brackish water. The results showed that the soil moisture of T3 was almost the same as T1 after the harvest of winter wheat each year, therefore, irrigating with brackish water can maintain soil moisture while saving fresh water resources. After two years, the soil salinity of each treatment increased by 0.307, 0.406, 0.383, and 0.889 g kg-1, respectively. During the jointing-flowering stage, salt stress has a significant inhibitory effect on photosynthesis; T3 and T4 were lower than T1 and T2 in terms of plant height and dry weight. During the filling stage, because the effect of drought stress is more serious than that of salt stress, the photosynthesis of T3 was greater than that of T2 and T4. For both years, the yield of crops followed the rank order T1 > T3 > T2 > T4. Compared with irrigating with fresh water in T1, T3 changed the second and third irrigation into brackish water, however we did not find that soil salinity increased significantly, and this treatment was able to ensure crop growth during the filling stage. Therefore, the combination of fresh water (80 mm), then brackish water (80 mm), then brackish water (80 mm) is a feasible irrigation strategy in China's Yellow River Delta for winter wheat.

scholarly journals Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 341
Author(s):  
Pauliina Salmi ◽  
Matti A. Eskelinen ◽  
Matti T. Leppänen ◽  
Ilkka Pölönen
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Strong Correlations ◽  
Algae Biomass ◽  
Chlorophyll A Concentration ◽  
Cost Efficient ◽  
Hyperspectral Camera

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.

Monitor Disease Incidence of Winter Wheat Stripe Rust Using Hyperspectral Data: Analysis of Characteristic Spectrum and Establishing of Inversion Models

2014 ◽  
Vol 602-605 ◽  
pp. 2462-2467
Author(s):  
Mu Yi Huang ◽  
Wen Jiang Huang ◽  
Xiao Dong Yang ◽  
Guang Zhou Chen
Keyword(s):  
Winter Wheat ◽  
Stripe Rust ◽  
Vegetation Index ◽  
Near Infrared ◽  
Disease Incidence ◽  
Correlation Coefficients ◽  
Hyperspectral Data ◽  
Wheat Stripe Rust ◽  
Canopy Spectral Reflectance ◽  
Reflectance Data

It was discussed of the selection method of characteristic spectral band and the establishing of inversion model to monitor winter wheat stripe rust using hyperspectral data in this study. The correlation coefficients between the DI (disease incidence) at different stages of infection and the initial canopy reflectance spectral and the derivative of the reflectance spectrum were compared, respectively. The results showed that the derivative of the reflectance spectra has reached higher significant level with the DI than the initial reflectance spectral data. The initial reflectance in the visible light 680nm wavelength and the near infrared 976nm, 1010nm wavelength were selected to do regression with the DI of winter wheat stripe rust. And some inversion models between the DI and the hyperspectral data or its conversion patterns like NDVI (Normalized difference vegetation index), RVI (Ratio vegetation index), TVI (Transformed vegetation index) and its differential values of the canopy spectral reflectance data to monitor winter wheat stripe rust were established. Meanwhile, those correlation coefficients were compared respectively, of which we found the pattern of vegetation index has more efficient commonly than initial canopy spectral reflectance data by aggression analysis with the DI. The paper also suggested that the possibility of developing a special visible/near-infrared sensor for the detection of the DI of winter wheat stripe rust theoretically. Else, the SRSI (stripe rust stress index) mechanism model was presented for the first time in this paper.

scholarly journals Early Identification of Root Rot Disease by Using Hyperspectral Reflectance: The Case of Pathosystem Grapevine/Armillaria

2021 ◽  
Vol 13 (13) ◽  
pp. 2436
Author(s):  
Federico Calamita ◽  
Hafiz Ali Imran ◽  
Loris Vescovo ◽  
Mohamed Lamine Mekhalfi ◽  
Nicola La Porta
Keyword(s):  
Root Rot ◽  
Woody Plants ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Disease Diagnosis ◽  
Hyperspectral Data ◽  
Detection Methods ◽  
Root Rot Disease ◽  
Rot Disease

Armillaria genus represents one of the most common causes of chronic root rot disease in woody plants. Prompt recognition of diseased plants is crucial to control the pathogen. However, the current disease detection methods are limited at a field scale. Therefore, an alternative approach is needed. In this study, we investigated the potential of hyperspectral techniques to identify fungi-infected vs. healthy plants of Vitis vinifera. We used the hyperspectral imaging sensor Specim-IQ to acquire leaves’ reflectance data of the Teroldego Rotaliano grapevine cultivar. We analyzed three different groups of plants: healthy, asymptomatic, and diseased. Highly significant differences were found in the near-infrared (NIR) spectral region with a decreasing pattern from healthy to diseased plants attributable to the leaf mesophyll changes. Asymptomatic plants emerged from the other groups due to a lower reflectance in the red edge spectrum (around 705 nm), ascribable to an accumulation of secondary metabolites involved in plant defense strategies. Further significant differences were observed in the wavelengths close to 550 nm in diseased vs. asymptomatic plants. We evaluated several machine learning paradigms to differentiate the plant groups. The Naïve Bayes (NB) algorithm, combined with the most discriminant variables among vegetation indices and spectral narrow bands, provided the best results with an overall accuracy of 90% and 75% in healthy vs. diseased and healthy vs. asymptomatic plants, respectively. To our knowledge, this study represents the first report on the possibility of using hyperspectral data for root rot disease diagnosis in woody plants. Although further validation studies are required, it appears that the spectral reflectance technique, possibly implemented on unmanned aerial vehicles (UAVs), could be a promising tool for a cost-effective, non-invasive method of Armillaria disease diagnosis and mapping in-field, contributing to a significant step forward in precision viticulture.

FALL GROWTH AND COLD ACCLIMATION OF WINTER WHEAT AND RYE ON SALINE SOILS

1981 ◽  
Vol 61 (2) ◽  
pp. 225-230 ◽  
Author(s):  
D. B. FOWLER
Keyword(s):  
Salt Stress ◽  
Winter Wheat ◽  
Cold Acclimation ◽  
Soil Salinity ◽  
Cold Hardiness ◽  
Calcium Content ◽  
Triticum Aestivum L ◽  
Saline Soils ◽  
Variable Effect ◽  
Sodium Magnesium

The effect of salt stress during the period of cold acclimation for winter wheat (Triticum aestivum L.) and rye (Secale cereale L.) was studied in field trials on saline soils north of the Quill Lakes in the northeastern corner of the agricultural area of Saskatchewan. Shoot and crown dry weights and crown moisture, sodium, magnesium and sulfur contents were all strongly influenced by variables related to soil conductivity. Increased levels of soil sodium and magnesium salts were reflected by increased concentrations of sodium, magnesium and sulfur in the crown tissue. In contrast, crown calcium content decreased significantly with increased soil salinity. Soil salinity had a variable effect on cold hardiness. Although the general trend was towards reduced cold tolerance of plants with increased salt stress, reductions were not large enough to be of practical concern.

scholarly journals INFLUENCE OF THE VIEWING GEOMETRY WITHIN HYPERSPECTRAL IMAGES RETRIEVED FROM UAV SNAPSHOT CAMERAS

2016 ◽  
Vol III-7 ◽  
pp. 257-261 ◽  
Author(s):  
Helge Aasen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Field Of View ◽  
Hyperspectral Images ◽  
Single Image ◽  
Area Of Interest ◽  
Vegetation Parameter ◽  
Parameter Retrieval

Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. <br><br> This study investigates the influence of the different viewing geometries within an image on the apparent hyperspectral reflection retrieved by these sensors. Additionally, it is evaluated how hyperspectral vegetation indices like the NDVI are effected by the angular effects within a single image and if the viewing geometry influences the apparent heterogeneity with an area of interest. The study is carried out for a barley canopy at booting stage. <br><br> The results show significant influences of the position of the area of interest within the image. The red region of the spectrum is more influenced by the position than the near infrared. The ability of the NDVI to compensate these effects was limited to the capturing positions close to nadir. The apparent heterogeneity of the area of interest is the highest close to a nadir.

scholarly journals INFLUENCE OF THE VIEWING GEOMETRY WITHIN HYPERSPECTRAL IMAGES RETRIEVED FROM UAV SNAPSHOT CAMERAS

2016 ◽  
Vol III-7 ◽  
pp. 257-261 ◽  
Author(s):  
Helge Aasen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Field Of View ◽  
Hyperspectral Images ◽  
Single Image ◽  
Area Of Interest ◽  
Vegetation Parameter ◽  
Parameter Retrieval

Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. &lt;br&gt;&lt;br&gt; This study investigates the influence of the different viewing geometries within an image on the apparent hyperspectral reflection retrieved by these sensors. Additionally, it is evaluated how hyperspectral vegetation indices like the NDVI are effected by the angular effects within a single image and if the viewing geometry influences the apparent heterogeneity with an area of interest. The study is carried out for a barley canopy at booting stage. &lt;br&gt;&lt;br&gt; The results show significant influences of the position of the area of interest within the image. The red region of the spectrum is more influenced by the position than the near infrared. The ability of the NDVI to compensate these effects was limited to the capturing positions close to nadir. The apparent heterogeneity of the area of interest is the highest close to a nadir.

scholarly journals Effects of disk tillage on soil condition, crop yield and weed infestation

2011 ◽  
Vol 48 (No. 1) ◽  
pp. 20-26
Author(s):  
M. Birkás ◽  
T. Szalai ◽  
C. Gyuricza ◽  
M. Gecse ◽  
K. Bordás
Keyword(s):  
Winter Wheat ◽  
Crop Yield ◽  
Field Experiments ◽  
Soil Layer ◽  
Soil Condition ◽  
Perennial Weeds ◽  
Weed Infestation ◽  
Set Up ◽  
Different Levels

This research was instigated by the fact that during the last decade annually repeated shallow disk tillage on the same field became frequent practice in Hungary. In order to study the changes of soil condition associated with disk tillage and to assess it is consequences, long-term tillage field experiments with different levels of nutrients were set up in 1991 (A) and in 1994 (B) on Chromic Luvisol at G&ouml;d&ouml;ll&ouml;. The effects of disk tillage (D) and disk tillage combined with loosening (LD) on soil condition, on yield of maize and winter wheat, and on weed infestation were examined. The evaluation of soil condition measured by cone index and bulk density indicated that use of disking annually resulted in a dense soil layer below the disking depth (diskpan-compaction). It was found, that soil condition deteriorated by diskpan-compaction decreased the yield of maize significantly by 20 and 42% (w/w), and that of wheat by 13 and 15% (w/w) when compared to soils with no diskpan-compaction. Averaged over seven years, and three fertilizer levels, the cover % of the total, grass and perennial weeds on loosened soils were 73, 69 and 65% of soils contained diskpan-compaction.

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