scholarly journals Application of UAV Remote Sensing in Monitoring Banana Fusarium Wilt

2021 ◽  
Author(s):  
Huichun Ye ◽  
Wenjiang Huang ◽  
Shanyu Huang ◽  
Chaojia Nie ◽  
Jiawei Guo ◽  
...  
Keyword(s):  
Fusarium Wilt ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Binary Logistic Regression ◽  
Wilt Disease ◽  
Red Edge ◽  
Fusarium Wilt Disease ◽  
Logistic Regression Method ◽  
Chlorophyll Index ◽  
Pigment Index

Fusarium wilt poses a current threat to worldwide banana plantation areas. To treat the Fusarium wilt disease and adjust banana planting methods accordingly, it is important to introduce timely monitoring processes. In this chapter, the multispectral images acquired by unmanned aerial vehicle (UAV) was used to establish a method to identify which banana regions were infected or uninfected with Fusarium wilt disease. The vegetation indices (VIs), including the normalised difference vegetation index (NDVI), normalised difference red edge index (NDRE), structural independent pigment index (SIPI), red-edge structural independent pigment index (SIPIRE), green chlorophyll index (CIgreen), red-edge chlorophyll index (CIRE), anthocyanin reflectance index (ARI), and carotenoid index (CARI), were selected for deciding the biophysical and biochemical characteristics of the banana plants. The relationships between the VIs and those plants infected or uninfected with Fusarium wilt were assessed using the binary logistic regression method. The results suggest that UAV-based multispectral imagery with a red-edge band is effective to identify banana Fusarium wilt disease, and that the CIRE had the best performance.

scholarly journals Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing

2020 ◽  
Vol 12 (6) ◽  
pp. 938 ◽  
Author(s):  
Huichun Ye ◽  
Wenjiang Huang ◽  
Shanyu Huang ◽  
Bei Cui ◽  
Yingying Dong ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Fusarium Wilt ◽  
Wilt Disease ◽  
Identification Accuracy ◽  
Validation Dataset ◽  
Multispectral Imagery ◽  
Red Edge ◽  
Fusarium Wilt Disease ◽  
Chlorophyll Index ◽  
Edge Band

Fusarium wilt (Panama disease) of banana currently threatens banana production areas worldwide. Timely monitoring of Fusarium wilt disease is important for the disease treatment and adjustment of banana planting methods. The objective of this study was to establish a method for identifying the banana regions infested or not infested with Fusarium wilt disease using unmanned aerial vehicle (UAV)-based multispectral imagery. Two experiments were conducted in this study. In experiment 1, 120 sample plots were surveyed, of which 75% were used as modeling dataset for model fitting and the remaining were used as validation dataset 1 (VD1) for validation. In experiment 2, 35 sample plots were surveyed, which were used as validation dataset 2 (VD2) for model validation. An UAV equipped with a five band multispectral camera was used to capture the multispectral imagery. Eight vegetation indices (VIs) related to pigment absorption and plant growth changes were chosen for determining the biophysical and biochemical characteristics of the plants. The binary logistic regression (BLR) method was used to assess the spatial relationships between the VIs and the plants infested or not infested with Fusarium wilt. The results showed that the banana Fusarium wilt disease can be easily identified using the VIs including the green chlorophyll index (CIgreen), red-edge chlorophyll index (CIRE), normalized difference vegetation index (NDVI), and normalized difference red-edge index (NDRE). The fitting overall accuracies of the models were greater than 80%. Among the investigated VIs, the CIRE exhibited the best performance both for the VD1 (OA = 91.7%, Kappa = 0.83) and VD2 (OA = 80.0%, Kappa = 0.59). For the same type of VI, the VIs including a red-edge band obtained a better performance than that excluding a red-edge band. A simulation of imagery with different spatial resolutions (i.e., 0.5-m, 1-m, 2-m, 5-m, and 10-m resolutions) showed that good identification accuracy of Fusarium wilt was obtained when the resolution was higher than 2 m. As the resolution decreased, the identification accuracy of Fusarium wilt showed a decreasing trend. The findings indicate that UAV-based remote sensing with a red-edge band is suitable for identifying banana Fusarium wilt disease. The results of this study provide guidance for detecting the disease and crop planting adjustment.

Reaction and growth of cucumber hybrids grafted on hybrid squash in response to infection with Fusarium wilt disease

2017 ◽  
Vol 35 (1) ◽  
pp. 027-035
Author(s):  
Alaa Ibrahim ◽  
◽  
Omar Hmmoudi ◽  
George Asmar ◽  
Naser Sheikh Suleiman ◽  
...  
Keyword(s):  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

Biocontrol of tomato Fusarium wilt disease by a new Moringa endophytic Aspergillus isolates

2021 ◽  
Author(s):  
Ahmed M. Aldinary ◽  
Amer Morsy Abdelaziz ◽  
Ayman A. Farrag ◽  
Mohamed S. Attia
Keyword(s):  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

scholarly journals Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery

2021 ◽  
Vol 13 (14) ◽  
pp. 2755
Author(s):  
Peng Fang ◽  
Nana Yan ◽  
Panpan Wei ◽  
Yifan Zhao ◽  
Xiwang Zhang
Keyword(s):  
Aboveground Biomass ◽  
Production Management ◽  
Vegetation Index ◽  
Net Primary Productivity ◽  
Vegetation Indices ◽  
Biophysical Parameters ◽  
Edge Information ◽  
Casa Model ◽  
Red Edge ◽  
Biomass Mapping

The net primary productivity (NPP) and aboveground biomass mapping of crops based on remote sensing technology are not only conducive to understanding the growth and development of crops but can also be used to monitor timely agricultural information, thereby providing effective decision making for agricultural production management. To solve the saturation problem of the NDVI in the aboveground biomass mapping of crops, the original CASA model was improved using narrow-band red-edge information, which is sensitive to vegetation chlorophyll variation, and the fraction of photosynthetically active radiation (FPAR), NPP, and aboveground biomass of winter wheat and maize were mapped in the main growing seasons. Moreover, in this study, we deeply analyzed the seasonal change trends of crops’ biophysical parameters in terms of the NDVI, FPAR, actual light use efficiency (LUE), and their influence on aboveground biomass. Finally, to analyze the uncertainty of the aboveground biomass mapping of crops, we further discussed the inversion differences of FPAR with different vegetation indices. The results demonstrated that the inversion accuracies of the FPAR of the red-edge normalized vegetation index (NDVIred-edge) and red-edge simple ratio vegetation index (SRred-edge) were higher than those of the original CASA model. Compared with the reference data, the accuracy of aboveground biomass estimated by the improved CASA model was 0.73 and 0.70, respectively, which was 0.21 and 0.13 higher than that of the original CASA model. In addition, the analysis of the FPAR inversions of different vegetation indices showed that the inversion accuracies of the red-edge vegetation indices NDVIred-edge and SRred-edge were higher than those of the other vegetation indices, which confirmed that the vegetation indices involving red-edge information can more effectively retrieve FPAR and aboveground biomass of crops.

scholarly journals Palmitic acid mediated change of rhizosphere and alleviation of Fusarium wilt disease in watermelon

2021 ◽  
Author(s):  
Kexin Ma ◽  
Jinming Kou ◽  
Muhammad Khashi U Rahman ◽  
Wenting Du ◽  
Xingyu Liang ◽  
...  
Keyword(s):  
Palmitic Acid ◽  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

scholarly journals The tomato xylem sap protein XSP10 is required for full susceptibility to Fusarium wilt disease

2010 ◽  
Vol 62 (3) ◽  
pp. 963-973 ◽  
Author(s):  
Vladimir Krasikov ◽  
Henk L. Dekker ◽  
Martijn Rep ◽  
Frank L.W. Takken
Keyword(s):  
Fusarium Wilt ◽  
Xylem Sap ◽  
Wilt Disease ◽  
Fusarium Wilt Disease

Biocontrol of Fusarium wilt disease in tomato by Paenibacillus ehimensis KWN38

2014 ◽  
Vol 31 (1) ◽  
pp. 165-174 ◽  
Author(s):  
Kyaw Wai Naing ◽  
Xuan Hoa Nguyen ◽  
Muhammad Anees ◽  
Yong Seong Lee ◽  
Yong Cheol Kim ◽  
...  
Keyword(s):  
Fusarium Wilt ◽  
Wilt Disease ◽  
Fusarium Wilt Disease ◽  
Paenibacillus Ehimensis

PERANAN TRICHOKOMPOS DAN PUPUK KCL DALAM MENGENDALIKAN PENYAKIT LAYU FUSARIUM PADA TANAMAN BAWANG MERAH DI TANAH BERPASIR (The Role of Trichokompos and KCL Fertilizer to Control Fusarium Will Disease on Onion in Sandy Soil)

AgriPeat ◽  
2019 ◽  
Vol 20 (01) ◽  
pp. 19-26
Author(s):  
Admin Journal
Keyword(s):  
Research Design ◽  
Fusarium Wilt ◽  
Sandy Soil ◽  
Incubation Time ◽  
Block Design ◽  
Wilt Disease ◽  
Single Factor ◽  
Fusarium Wilt Disease ◽  
Randomized Block Design

ABSTRACTThe role of Trichocompost and KCl fertilizer to control Fusarium wilt disease on onion in sandy soil. Fusarium wilt on onion is an interesting disease it is can loss the onion yield. The purpose of research to study trichocompost and KCl fertilizer role to control Fusarium wilt disease on ann onion. The research design used a Factorial Randomized Block Design with 2 factors. The first factor is 4 levels trichocompost, it is: without trichocompost (T0), trichocompost 10 t.ha-1 dosage (T1), trichocompost 20 t.ha-1 dosage (T2), trichocompost 30 t.ha-1 dosage (T3). The second factor is 3 levels KCl fertilizer, it is: without KCl (K0), KCl 100 kg.ha-1 dosage (K1), KCl 200 kg.ha-1 dosage (K2). Result of this research showed the application of trichocompost 10 t.ha-1 dosage and KCl 100 kg.ha-1 dosage can inhibit Fusarium wilt incubation time, can inhibit the patogen development with effective value 89,23%, the single factor it is aplication trichocompost 10 t.ha-1 dosage and trichocompost 30 t.ha-1 dosage not significant to dried onion bulb weight per clump of onion plant.Key words: Trichocompost, KCl fertilizer, Fusarium wilt disease, onion, sandy soil.ABSTRAKPenyakit layu Fusarium merupakan salah satu penyakit penting dapat menurunkan produksi bawang merah hingga 50%. Tujuan penelitian untuk mengetahui peranan trichokompos dan pupuk KCl dalam mengendalikan penyakit layu fusarium pada tanaman bawang merah. Penelitian menggunakan Rancangan Acak Kelompok faktorial dua faktor perlakuan. Faktor pertama 4 taraf dosis trichokompos yaitu: tanpa trichokompos (T0), trichokompos dosis 10 t.ha-1 (T1), trichokompos dosis 20 t.ha-1 (T2), trichokompos dosis 30 t.ha-1 (T3). Faktor kedua 3 taraf dosis pupuk KCl yaitu: tanpa pupuk KCl (K0), pupuk KCl dosis 100 KCl kg.ha-1 (K1), pupuk KCl dosis 200 KCl kg.ha-1 (K2). Hasil penelitian menunjukkan pemberian trichokompos 10 t.ha-1 dan pupuk KCl 100 kg.ha-1 dapat memperpanjang masa inkubasi penyakit, menekan serangan penyakit layu Fusarium dengan nilai efektivitas sangat baik (89,23%), perlakuan tunggal trichokompos dosis 10 t.ha-1 tidak berbeda nyata dengan dosis 30 t.ha-1 terhadap bobot umbi kering per rumpun tanaman bawang merah.Kata kunci: penyakit layu Fusarium, pupuk KCl, tanah berpasir, tanaman bawang merah, trichokompos.

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