scholarly journals Mapping Wheat Dry Matter and Nitrogen Content Dynamics and Estimation of Wheat Yield Using UAV Multispectral Imagery Machine Learning and a Variety-Based Approach: Case Study of Morocco

2021 ◽  
Vol 3 (1) ◽  
pp. 29-49
Author(s):  
Ghizlane Astaoui ◽  
Jamal Eddine Dadaiss ◽  
Imane Sebari ◽  
Samir Benmansour ◽  
Ettarid Mohamed
Keyword(s):  
Random Forest ◽  
Nitrogen Uptake ◽  
Dry Matter ◽  
Vegetation Indices ◽  
Wheat Yield ◽  
Wheat Crop ◽  
Multispectral Imagery ◽  
Biophysical Parameters ◽  
Phenological Stages ◽  
Wheat Varieties

Our work aims to monitor wheat crop using a variety-based approach by taking into consideration four different phenological stages of wheat crop development. In addition to highlighting the contribution of Red-Edge vegetation indices in mapping wheat dry matter and nitrogen content dynamics, as well as using Random Forest regressor in the estimation of wheat yield, dry matter and nitrogen uptake relying on UAV (Unmanned Aerial Vehicle) multispectral imagery. The study was conducted on an experimental platform with 12 wheat varieties located in Sidi Slimane (Morocco). Several flight missions were conducted using eBee UAV with MultiSpec4C camera according to phenological growth stages of wheat. The proposed methodology is subdivided into two approaches, the first aims to find the most suitable vegetation index for wheat’s biophysical parameters estimation and the second to establish a global model regardless of the varieties to estimate the biophysical parameters of wheat: Dry matter and nitrogen uptake. The two approaches were conducted according to six main steps: (1) UAV flight missions and in-situ data acquisition during four phenological stages of wheat development, (2) Processing of UAV multispectral images which enabled us to elaborate the vegetation indices maps (RTVI, MTVI2, NDVI, NDRE, GNDVI, GNDRE, SR-RE et SR-NIR), (3) Automatic extraction of plots by Object-based image analysis approach and creating a spatial database combining the spectral information and wheat’s biophysical parameters, (4) Monitoring wheat growth by generating dry biomass and wheat’s nitrogen uptake model using exponential, polynomial and linear regression for each variety this step resumes the varietal approach, (5) Engendering a global model employing both linear regression and Random Forest technique, (6) Wheat yield estimation. The proposed method has allowed to predict from 1 up to 21% difference between actual and estimated yield when using both RTVI index and Random Forest technique as well as mapping wheat’s dry biomass and nitrogen uptake along with the nitrogen nutrition index (NNI) and therefore facilitate a careful monitoring of the health and the growth of wheat crop. Nevertheless, some wheat varieties have shown a significant difference in yield between 2.6 and 3.3 t/ha.

scholarly journals Spring wheat yield (Triticum aestivum L.) when applying selenium fertilizers in extreme growing conditions

2021 ◽  
Vol 843 (1) ◽  
pp. 012038
Author(s):  
I I Seregina ◽  
I G Makarskaya ◽  
A S Tsygutkin ◽  
I V Kirichkova
Keyword(s):  
Triticum Aestivum ◽  
Water Supply ◽  
Spring Wheat ◽  
Sodium Selenite ◽  
Wheat Yield ◽  
Triticum Aestivum L ◽  
Wheat Crop ◽  
Wheat Varieties ◽  
Negative Effect ◽  
Positive Effect

Abstract To study the effect of sodium Selenite application different methods on the yield of spring wheat varieties, depending on the conditions of water supply, a series of vegetation experiments in accordance with the methodology were carried out. The object of the study is spring wheat of the Zlata variety (Triticum aestivum L.). It was found that the effect of selenium on the yield of wheat of the Zlata variety depended on the method of its application and the conditions of water supply. With optimal water supply, the positive effect of selenium on the yield of spring wheat plants was revealed with both methods of applying sodium selenite. It was found that in conditions of drought, the positive effect of selenium was obtained with both methods of using sodium selenite. The greatest efficiency of selenium is obtained in foliar processing of plants. The increase in grain weight in this variant was 1.4 times. The increase in the share of the agronomic significant part of the wheat crop yield to 36% is shown, which indicates the decrease in the negative effect of drought on the formation of spring wheat yield when using foliar processing of plants.

scholarly journals Criteria for Decision Making and Economic Threshold Level for Wild Radish in Wheat Crop

2019 ◽  
Vol 37 ◽  
Author(s):  
L.C. TAVARES ◽  
E.S. LEMES ◽  
Q. RUCHEL ◽  
N.R. WESTENDORFF ◽  
D. AGOSTINETTO
Keyword(s):  
Dry Matter ◽  
Competitive Ability ◽  
Soil Cover ◽  
Wheat Cultivar ◽  
Wheat Yield ◽  
Threshold Level ◽  
Wheat Crop ◽  
Wild Radish ◽  
Raphanus Raphanistrum ◽  
Economic Threshold

ABSTRACT: Weed competition limits wheat yield by reducing the availability of essential resources for its growth and development. In this sense, this study aimed to estimate the economic threshold level (ETL) of wild radish (Raphanus raphanistrum) in competition with wheat cultivars. Treatments were arranged in a factorial scheme. The factor wheat cultivar consisted of early (BRS 328), medium (BRS 177), and late (BRS Umbu) cycles and the factor wild radish population ranged from 0 to 564 plants m-2 (10 populations) for the cultivar BRS 328, 0 to 472 plants m-2 for the cultivar BRS 177 (11 populations), and 0 to 724 plants m-2 for the cultivar BRS Umbu (10 populations). The early-cycle BRS 328 presented a higher competitive ability when compared to the medium-cycle BRS 177 and late-cycle BRS Umbu. Yield losses of wheat grains due to wild radish interference can be satisfactorily estimated by the rectangular hyperbola model using the variables plant population, shoot dry matter, soil cover, and leaf area of the weed. ETL values varied as a function of the cultivar cycle, being higher for the cultivar BRS 328 (early) > BRS 177 (medium) > BRS Umbu (late). Wild radish is competitive in wheat crop, requiring at least 1.6 plants m-2 for control to be justified.

scholarly journals Estimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imagery

Drones ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 80 ◽  
Author(s):  
Kaori Otsu ◽  
Magda Pla ◽  
Andrea Duane ◽  
Adrián Cardil ◽  
Lluís Brotons
Keyword(s):  
Random Forest ◽  
Large Scale ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Thaumetopoea Pityocampa ◽  
Multispectral Imagery ◽  
Mixed Stands ◽  
Crown Defoliation ◽  
Total Study Area ◽  
Pine Species

Periodical outbreaks of Thaumetopoea pityocampa feeding on pine needles may pose a threat to Mediterranean coniferous forests by causing severe tree defoliation, growth reduction, and eventually mortality. To cost–effectively monitor the temporal and spatial damages in pine–oak mixed stands using unmanned aerial systems (UASs) for multispectral imagery, we aimed at developing a simple thresholding classification tool for forest practitioners as an alternative method to complex classifiers such as Random Forest. The UAS flights were performed during winter 2017–2018 over four study areas in Catalonia, northeastern Spain. To detect defoliation and further distinguish pine species, we conducted nested histogram thresholding analyses with four UAS-derived vegetation indices (VIs) and evaluated classification accuracy. The normalized difference vegetation index (NDVI) and NDVI red edge performed the best for detecting defoliation with an overall accuracy of 95% in the total study area. For discriminating pine species, accuracy results of 93–96% were only achievable with green NDVI in the partial study area, where the Random Forest classification combined for defoliation and tree species resulted in 91–93%. Finally, we achieved to estimate the average thresholds of VIs for detecting defoliation over the total area, which may be applicable across similar Mediterranean pine stands for monitoring regional forest health on a large scale.

scholarly journals Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine

2015 ◽  
Vol XL-7/W3 ◽  
pp. 39-44 ◽  
Author(s):  
A. Kolotii ◽  
N. Kussul ◽  
A. Shelestov ◽  
S. Skakun ◽  
B. Yailymov ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Crop Yield ◽  
Wheat Yield ◽  
Biophysical Model ◽  
Wheat Crop ◽  
Biophysical Parameters ◽  
Model Based ◽  
Winter Wheat Crop ◽  
Yield Forecasting ◽  
Crop Yield Forecasting

Winter wheat crop yield forecasting at national, regional and local scales is an extremely important task. This paper aims at assessing the efficiency (in terms of prediction error minimization) of satellite and biophysical model based predictors assimilation into winter wheat crop yield forecasting models at different scales (region, county and field) for one of the regions in central part of Ukraine. Vegetation index NDVI, as well as different biophysical parameters (LAI and fAPAR) derived from satellite data and WOFOST crop growth model are considered as predictors of winter wheat crop yield forecasting model. Due to very short time series of reliable statistics (since 2000) we consider single factor linear regression. It is shown that biophysical parameters (fAPAR and LAI) are more preferable to be used as predictors in crop yield forecasting regression models at each scale. Correspondent models possess much better statistical properties and are more reliable than NDVI based model. The most accurate result in current study has been obtained for LAI values derived from SPOT-VGT (at 1 km resolution) on county level. At field level, a regression model based on satellite derived LAI significantly outperforms the one based on LAI simulated with WOFOST.

scholarly journals Role of agronomic manipulations in modification of wheat microclimate under central Punjab

2016 ◽  
Vol 8 (4) ◽  
pp. 1905-1911
Author(s):  
Sarabjot Kaur Sandhu ◽  
L. K. Dhaliwal
Keyword(s):  
Dry Matter ◽  
Canopy Temperature ◽  
Short Wave ◽  
Wave Radiation ◽  
Wheat Crop ◽  
Row Spacing ◽  
Dry Matter Accumulation ◽  
Short Wave Radiation ◽  
Wheat Varieties ◽  
Radiation Interception

Wheat crop is influenced by different microclimatic parameters like solar radiation, canopy temperature etc. Agronomic manipulation like change in row spacing and row direction can be used as a strategy to modify the microclimate of crop. Keeping these facts in view, field trials were conducted during rabi 2012-13 and 2013-14 under two experiments in first experiment wheat varieties HD 2967, PBW 550 and PBW 343 were sown under three row spacing viz. 15 cm, 22.5 cm and 30 cm. In second experiment, wheat varieties HD 2967, PBW 550 and PBW 343 were sown under two row direction viz. North-South (N-S) and East-West (E-W). Short wave radiation interception and canopy temperature was recorded under different treatments at 15 days interval. Among different row spacing, short wave radiation interception and canopy temperature was maximum at 30 cm row spacing (77.7% and 25.1oC) followed by 22.5 cm (75.7% and 24.2oC) and 15 cm row spacing (73.9% and 23.2oC), whereas under row directions short wave radiation interception and canopy temperature was more (76.5% and 23.9oC) in E-W row direction as compared to N-S row direction (75% and 23.2oC). Relationships were developed between dry matter accumulation and canopy temperature. Polynomial relationships gave significant R2 value (0.66 & 0.69) under different treatments. This two year study indicated that agronomic manipulations play an important role in microclimate modification and canopy temperature significantly influence dry matter accumulation under different crop geometry.

scholarly journals On the Potentiality of UAV Multispectral Imagery to Detect Flavescence dorée and Grapevine Trunk Diseases

2018 ◽  
Vol 11 (1) ◽  
pp. 23 ◽  
Author(s):  
Johanna Albetis ◽  
Anne Jacquin ◽  
Michel Goulard ◽  
Hervé Poilvé ◽  
Jacques Rousseau ◽  
...  
Keyword(s):  
Roc Curve ◽  
Vegetation Indices ◽  
Carotenoid Content ◽  
Multispectral Imagery ◽  
Biophysical Parameters ◽  
Wine Production ◽  
Flavescence Dorée ◽  
Grapevine Trunk Diseases ◽  
Spectral Bands ◽  
Trunk Diseases

Among grapevine diseases affecting European vineyards, Flavescence dorée (FD) and Grapevine Trunk Diseases (GTD) are considered the most relevant challenges for viticulture because of the damage they cause to vineyards. Unmanned Aerial Vehicle (UAV) multispectral imagery could be a powerful tool for the automatic detection of symptomatic vines. However, one major difficulty is to discriminate different kinds of diseases leading to similar leaves discoloration as it is the case with FD and GTD for red vine cultivars. The objective of this paper is to evaluate the potentiality of UAV multispectral imagery to separate: symptomatic vines including FD and GTD (Esca and black dead arm) from asymptomatic vines (Case 1) and FD vines from GTD ones (Case 2). The study sites are localized in the Gaillac and Minervois wine production regions (south of France). A set of seven vineyards covering five different red cultivars was studied. Field work was carried out between August and September 2016. In total, 218 asymptomatic vines, 502 FD vines and 199 GTD vines were located with a centimetric precision GPS. UAV multispectral images were acquired with a MicaSense RedEdge® sensor and were processed to ultimately obtain surface reflectance mosaics at 0.10 m ground spatial resolution. In this study, the potentiality of 24 variables (5 spectral bands, 15 vegetation indices and 4 biophysical parameters) are tested. The vegetation indices are selected for their potentiality to detect abnormal vegetation behavior in relation to stress or diseases. Among the biophysical parameters selected, three are directly linked to the leaf pigments content (chlorophyll, carotenoid and anthocyanin). The first step consisted in evaluating the performance of the 24 variables to separate symptomatic vine vegetation (FD or/and GTD) from asymptomatic vine vegetation using the performance indicators from the Receiver Operator Characteristic (ROC) Curve method (i.e., Area Under Curve or AUC, sensibility and specificity). The second step consisted in mapping the symptomatic vines (FD and/or GTD) at the scale of the field using the optimal threshold resulting from the ROC curve. Ultimately, the error between the level of infection predicted by the selected variables (proportion of symptomatic pixels by vine) and observed in the field (proportion of symptomatic leaves by vine) is calculated. The same methodology is applied to the three levels of analysis: by vineyard, by cultivar (Gamay, Fer Servadou) and by berry color (all red cultivars). At the vineyard and cultivar levels, the best variables selected varies. The AUC of the best vegetation indices and biophysical parameters varies from 0.84 to 0.95 for Case 1 and 0.74 to 0.90 for Case 2. At the berry color level, no variable is efficient in discriminating FD vines from GTD ones (Case 2). For Case 1, the best vegetation indices and biophysical parameter are Red Green Index (RGI)/ Green-Red Vegetation Index (GRVI) (based on the green and red spectral bands) and Car (linked to carotenoid content). These variables are more effective in mapping vines with a level of infection greater than 50%. However, at the scale of the field, we observe misclassified pixels linked to the presence of mixed pixels (shade, bare soil, inter-row vegetation and vine vegetation) and other factors of abnormal coloration (e.g., apoplectic vines).

Effects of subterranean, rose and cupped clovers on soil nitrogen and on a subsequent cereal crop

1980 ◽  
Vol 20 (104) ◽  
pp. 354 ◽  
Author(s):  
ER Watson ◽  
P Lapins ◽  
RJW Barron
Keyword(s):  
Soil Nitrogen ◽  
Nitrogen Uptake ◽  
Dry Matter ◽  
Inorganic Nitrogen ◽  
Nitrogen Concentration ◽  
Subterranean Clover ◽  
Trifolium Subterraneum ◽  
Wheat Crop ◽  
Cereal Crop ◽  
Nitrogen Concentrations

Three annual clover species : subterranean clover, Trifolium subterraneum (cv. Geraldton), rose clover, T. hirtum (cv. Kondinin), and cupped clover, T. cherleri (cv. Yamina) were compared for yield of dry matter, for their effects on soil nitrogen, dry matter yield, and nitrogen uptake by a subsequent cereal crop. In one experiment, the three clover species and annual ryegrass (Lolium rigidum), were grown in lysimeters to provide measurements of dry matter and nitrogen yields of plant tops and roots. Half of the lysimeters, from which the plant roots had not been removed, were later sown with wheat. Rose clover produced the highest yield of root nitrogen, and this was reflected in higher nitrogen uptake in the succeeding wheat crop. Nitrogen yield of wheat after ryegrass was 60% of the average yield after clovers. The three clover species were also included in a pasture experiment, which was grazed by sheep for five years. Samples were taken from the field plots to provide soil for a glasshouse pot experiment, and for chemical analysis. In the pasture experiment, build up of soil nitrogen over six years did not differ significantly between the subterranean and rose clover treatments, although there were large differences in clover plant numbers and herbage production, and botanical composition of the pastures. However, inorganic nitrogen concentrations were much higher in soil from the subterranean clover plots than in soil from the rose or cupped clover plots, particularly in the later stages of the field experiment. Total nitrogen increase and mineral nitrogen concentration were lowest in soil from the cupped clover plots, although herbage yield was comparable with that of rose clover

scholarly journals Effect of genotype and phenological stages on the accumulation rate of dry matter in wheat

2020 ◽  
Vol 44 (2) ◽  
pp. 7647-7655
Keyword(s):  
Dry Matter ◽  
Accumulation Rate ◽  
Matter Content ◽  
Dry Matter Content ◽  
Phenological Stages ◽  
Wheat Varieties ◽  
Seed Filling ◽  
Wheat Development ◽  
High Yields ◽  
Phenological Phases

Considering that wheat occupies a primary place in human food, it is important to find varieties of wheat that, in addition to their high yields, are characterized by high nutritive and mineral qualities. The aim of this study was to determine dry matter content in genetically divergent wheat varieties, to identify varieties with a higher dry matter content, as well as to determine the accumulation rate of dry matter in different phenological phases. The highest increase in the amount of dry matter occurred in the phase of seed filling (16.31%). The fastest accumulation of dry matter for a period of one week was recorded in the phenological phase of milk maturation. Based on the results, it was concluded that phenological phase of seed filling is an important period of the wheat development for the accumulation of dry matter. The amount of accumulated dry matter depends on the variety of wheat. Varieties with higher amount of accumulated dry matter can be possibly used for selection and hybridization.

scholarly journals Biomass as a factor contributing to winter wheat yield increase

2019 ◽  
Vol 24 ◽  
pp. 265-270
Author(s):  
V. V. Morgun ◽  
G. A. Priadkina ◽  
O. O. Stasik ◽  
O. V. Zborіvskaіa
Keyword(s):  
Winter Wheat ◽  
Dry Matter ◽  
Stem Elongation ◽  
Wheat Yield ◽  
Wheat Varieties ◽  
Plant Parts ◽  
Early Stages ◽  
Grain Productivity ◽  
Dry Matter Weight ◽  
Winter Wheat Varieties

Aim. The search of factors influencing grain productivity, based on the comparison of the mass of dry matter in the aboveground parts of modern winter wheat varieties at the early stages of ontogenesis. Methods. Morphometric determination of biomass of the above-ground plant parts. Results. The varieties and lines of winter wheat with higher yields exceeded the less productive ones by the number of shoots per 1 m2 of soil on 8–12 % and by the dry matter weight of the above-ground plant parts on 23–34 % at the early stages of spring vegetation. According to two-year experiments, it was established a linear positive correlation (r = 0.85–0.86) of the dry matter weight of the above-ground plant parts per 1 m2 of soil during the period of stem elongation (BBCH 31-49) with the yield. Conclusions. The close relationship between yield and dry matter weight of the above-ground plant parts at the early stages of spring vegetation makes it possible to rank winter wheat varieties by potential yield. Keywords: Triticum aestivum L., grain productivity, biomass, early stages of ontogenesis.

Effects of spray application of urea fertilizer at stem extension on winter wheat yield

2002 ◽  
Vol 139 (1) ◽  
pp. 1-10 ◽  
Author(s):  
R. J. READMAN ◽  
P. S. KETTLEWELL ◽  
C. P. BECKWITH
Keyword(s):  
Winter Wheat ◽  
Ammonium Nitrate ◽  
Harvest Index ◽  
Dry Matter ◽  
Wheat Yield ◽  
Environmental Benefits ◽  
Urea Solution ◽  
Wheat Crop ◽  
Physiological Basis ◽  
Stem Extension

Supplying a proportion of the N requirement of a wheat crop via the foliage would potentially reduce immobilization of fertilizer N in the soil organic matter and N losses by leaching or denitrification. A field experiment was carried out at Harper Adams in Shropshire to investigate the effect on crop yield of supplying the spring N application to winter wheat as different proportions of urea as a solution rather than as conventional soil-applied urea, and to determine the physiological basis of any yield differences. A solid ammonium nitrate treatment was included to represent alternative commercial practice to solid urea. Treatments were repeated on the same plots over the 3 years 1992, 1993 and 1994. Solid fertilizer was applied as a single dressing, whereas urea sprays were split over a number of days to reduce scorch. Nitrogen as urea sprays produced similar grain yields to N applied conventionally to the soil as solid ammonium nitrate or urea, but effects on above-ground dry matter production and harvest index depended on the time of application. Application of a large proportion of N as urea sprays, such that some of the N as urea solution was applied later in relation to crop development, produced less above-ground dry matter, but compensated by increasing harvest index. It is concluded that application of N as urea sprays could be successfully used to substitute for soil-applied N fertilizer at stem extension in winter wheat without loss of yield. Extra application costs, however, are likely to outweigh any efficiency or environmental benefits, except where applications of solid N are made to dry soils.

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