Narrow-waveband spectral indices for prediction of yield loss in frost-damaged winter wheat during stem elongation

2021 ◽  
Vol 124 ◽  
pp. 126240
Author(s):  
Yongfeng Wu ◽  
Ying Ma ◽  
Xin Hu ◽  
Juncheng Ma ◽  
Haigen Zhao ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Yield Loss ◽  
Stem Elongation ◽  
Spectral Indices

Predicting yield loss in winter wheat due to frost damage during stem elongation in the central area of Huang-huai plain in China

2022 ◽  
Vol 276 ◽  
pp. 108399
Author(s):  
Yongfeng Wu ◽  
Binhui Liu ◽  
Zhihong Gong ◽  
Xin Hu ◽  
Juncheng Ma ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Yield Loss ◽  
Stem Elongation ◽  
Central Area ◽  
Frost Damage

Response of winter wheat to prolonged waterlogging under outdoor conditions

1981 ◽  
Vol 97 (3) ◽  
pp. 557-568 ◽  
Author(s):  
R. K. Belford
Keyword(s):  
Winter Wheat ◽  
Water Table ◽  
Stem Elongation ◽  
Soil Surface ◽  
Root Production ◽  
Or Efficiency ◽  
Plant Nitrogen ◽  
Stages Of Growth ◽  
Nodal Root ◽  
Waterlogging Treatment

SUMMARYThe response of winter wheat cv. Maris Huntsman to waterlogging was studied in two experiments in soil columns outdoors. Winter waterlogging treatments increased nodal root production and the proportion of aerenchyma within roots, but caused chlorosis and premature senescence of leaves, and decreased tillering. For all treatments, grain losses were much less than expected from the extent of tiller loss in winter; losses after single waterlogging events ranged from 2% (after 47 days with the water-table at 5 cm) to 16% (after 80 days with the water-table at the soil surface). Yield losses after three waterloggings at the seedling, tillering and stem elongation stages of growth were additive, and totalled 19%. In many treatments, grain loss was associated with lighter individual grain weights, suggesting that the size of the root system or efficiency of water and nutrient uptake by roots at the later stages of growth may have been less after earlier waterlogging. The importance of nitrogen fertilizer in maintaining a satisfactory plant nitrogen status was shown when nitrogen was with held before a 3-week waterlogging treatment during stem elongation; tiller and floret survival was subsequently greatly restricted and grain yields decreased 22% below those of plants waterlogged at the same stage of growth but supplied with nitrogen.

Estimating Yield Losses Due to Barley Yellow Dwarf on Winter Wheat in Kansas Using Disease Phenotypic Data

2015 ◽  
Vol 16 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Genna M. Gaunce ◽  
William W. Bockus
Keyword(s):  
Winter Wheat ◽  
Yield Loss ◽  
Disease Incidence ◽  
Relative Yield ◽  
Yellow Dwarf ◽  
Wheat Cultivars ◽  
Grain Yields ◽  
Barley Yellow Dwarf ◽  
Winter Wheat Cultivars ◽  
The Impact

Barley yellow dwarf (BYD) is one of the most important wheat diseases in the state of Kansas. Despite the development of cultivars with improved resistance to BYD, little is known about the impact that this resistance has on yield loss from the disease. The intent of this research was to estimate yield loss in winter wheat cultivars in Kansas due to BYD and quantify the reduction in losses associated with resistant cultivars. During seven years, BYD incidence was visually assessed on numerous winter wheat cultivars in replicated field nurseries. When grain yields were regressed against BYD incidence scores, negative linear relationships significantly fit the data for each year and for the combined dataset covering all seven years. The models showed that, depending upon the year, 19–48% (average 33%) of the relative yields was explained by BYD incidence. For the combined dataset, 29% of the relative yield was explained by BYD incidence. The models indicated that cultivars showing the highest disease incidence that year had 25–86% (average 49%) lower yield than a hypothetical cultivar that showed zero incidence. Using the models, the moderate level of resistance in the cultivar Everest was calculated to reduce yield loss from BYD by about 73%. Therefore, utilizing visual BYD symptom evaluations in Kansas coupled with grain yields is useful to estimate yield loss from the disease. Accepted for publication 1 December 2014. Published 9 January 2015.

scholarly journals UAV-Based Hyperspectral and Ensemble Machine Learning for Predicting Yield in Winter Wheat

Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 202
Author(s):  
Zhen Chen ◽  
Qian Cheng ◽  
Fuyi Duan ◽  
Xiuqiao Huang ◽  
Honggang Xu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Winter Wheat ◽  
Prediction Model ◽  
Grain Filling ◽  
Yield Prediction ◽  
Spectral Indices ◽  
Learner Model ◽  
Ensemble Machine Learning ◽  
Base Learner

Winter wheat is a widely-grown cereal crop worldwide. Using growth-stage information to estimate winter wheat yields in a timely manner is essential for accurate crop management and rapid decision-making in sustainable agriculture, and to increase productivity while reducing environmental impact. UAV remote sensing is widely used in precision agriculture due to its flexibility and increased spatial and spectral resolution. Hyperspectral data are used to model crop traits because of their ability to provide continuous rich spectral information and higher spectral fidelity. In this study, hyperspectral image data of the winter wheat crop canopy at the flowering and grain-filling stages was acquired by a low-altitude unmanned aerial vehicle (UAV), and machine learning was used to predict winter wheat yields. Specifically, a large number of spectral indices were extracted from the spectral data, and three feature selection methods, recursive feature elimination (RFE), Boruta feature selection, and the Pearson correlation coefficient (PCC), were used to filter high spectral indices in order to reduce the dimensionality of the data. Four major basic learner models, (1) support vector machine (SVM), (2) Gaussian process (GP), (3) linear ridge regression (LRR), and (4) random forest (RF), were also constructed, and an ensemble machine learning model was developed by combining the four base learner models. The results showed that the SVM yield prediction model, constructed on the basis of the preferred features, performed the best among the base learner models, with an R2 between 0.62 and 0.73. The accuracy of the proposed ensemble learner model was higher than that of each base learner model; moreover, the R2 (0.78) for the yield prediction model based on Boruta’s preferred characteristics was the highest at the grain-filling stage.

scholarly journals Environmental Conditions Associated with Stripe Rust in Kansas Winter Wheat

Plant Disease ◽  
2016 ◽  
Vol 100 (11) ◽  
pp. 2306-2312 ◽  
Author(s):  
B. S. Grabow ◽  
D. A. Shah ◽  
E. D. DeWolf
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Stripe Rust ◽  
Yield Loss ◽  
Initial Step ◽  
Disease Forecasting ◽  
Estimation Equations ◽  
Forecasting System ◽  
Moisture Conditions ◽  
General Estimation

Stripe rust has reemerged as a problematic disease in Kansas wheat. However, there are no stripe rust forecasting models specific to Kansas wheat production. Our objective was to identify environmental variables associated with stripe rust epidemics in Kansas winter wheat as an initial step in the longer-term goal of developing predictive models for stripe rust to be used within the state. Mean yield loss due to stripe rust on susceptible varieties was estimated from 1999 to 2012 for each of the nine Kansas crop reporting districts (CRD). A CRD was classified as having experienced a stripe rust epidemic when yield loss due to the disease equaled or exceeded 1%, and a nonepidemic otherwise. Epidemics were further classified as having been moderate or severe if yield loss was 1 to 14% or greater than 14%, respectively. The binary epidemic categorizations were linked to a matrix of 847 variables representing monthly meteorological and soil moisture conditions. Classification trees were used to select variables associated with stripe rust epidemic occurrence and severity (conditional on an epidemic having occurred). Selected variables were evaluated as predictors of stripe rust epidemics within a general estimation equations framework. The occurrence of epidemics within CRD was linked to soil moisture during the fall and winter months. In the spring, severe epidemics were linked to optimal (7 to 12°C) temperatures. Simple environmentally based stripe rust models at the CRD level may be combined with field-level disease observations and an understanding of varietal reaction to stripe rust as part of an operational disease forecasting system in Kansas.

Increasing of wheat grain yield by use of a liquid fertilizer

2020 ◽  
Vol 1 (1) ◽  
pp. 45-49
Author(s):  
Tsotne Samadashvili ◽  
Gulnari Chkhutiashvili ◽  
Mirian Chokheli ◽  
Zoia Sikharulidze ◽  
Qetevan Nacarishvili
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Stem Elongation ◽  
Organic Fertilizer ◽  
Wheat Yield ◽  
Mineral Fertilizer ◽  
Field Trials ◽  
Early Spring ◽  
Wheat Grain ◽  
Liquid Fertilizer

Wheat is a vital crop in Georgia and in the world. Because of the increase in the rate of population growth, improving the grain yield is the way to meet food demand. Proper crop nutrition plays a vital role in maintaining the world’s food supply. Fertilizer is essential for accomplishing this.One of the most important means for increasing the wheat yield is fertilizer, especially, organic fertilizer. The present research was carried out to study the effects of different doses (150ml, 200ml and 300 ml on ha) of humic organic fertilizer “Ecorost” on yield of winter wheat cultivar “Tbilisuri 15”. The humic liquid fertilizer "Ecorost" is a peat-based organic-mineral fertilizer. The product is active and saturated due to the use of the latest technology and living bacteria found in peat. The field trials were conducted in 2017-2019 at the Experimental Site of Scientific Research Center of Agriculture in Dedopliskharo- arid region (Eastern Georgia).Liquid fertilizer was applied two times: in tillering stage in early spring and two weeks after - in stem elongation stage. Results indicated that the highest wheat grain yield (4t/ha) was achieved when the plants were fertilized with 300 ml on 1 ha ofEcorost. Applications of liquid fertilizer “Ecorost” increased grain yield of winter wheat by 16.2% in comparison with standard nitrogen fertilization. Thus, liquid fertilizer “Ecorost” had a significant effect on wheat grain yield compared to control standard nitrogen fertilizer.

Downy Brome (Bromus tectorum) Interference and Economic Thresholds in Winter Wheat (Triticum aestivum)

Weed Science ◽  
1990 ◽  
Vol 38 (3) ◽  
pp. 224-228 ◽  
Author(s):  
Phillip W. Stahlman ◽  
Stephen D. Miller
Keyword(s):  
Winter Wheat ◽  
Bromus Tectorum ◽  
Yield Loss ◽  
Wheat Yield ◽  
Dry Weight ◽  
Quadratic Equation ◽  
Downy Brome ◽  
Economic Threshold ◽  
Weed Density ◽  
Economic Thresholds

Densities up to 100 downy brome m2were established in winter wheat in southeastern Wyoming and west-central Kansas to quantify wheat yield loss from downy brome interference and to approximate economic threshold levels. A quadratic equation best described wheat yield loss as a function of weed density when downy brome emerged within 14 days after wheat emergence. Densities of 24, 40, and 65 downy brome m2reduced wheat yield by 10, 15, and 20%, respectively. Wheat yield was not reduced when downy brome emerged 21 or more days later than wheat. Economic thresholds varied with changes in downy brome density, cost of control, wheat price, and potential wheat yield. In a greenhouse experiment, dry weight of 72-day-old wheat plants grown in association with downy brome was not affected by the distance between the weeds and wheat, whereas downy brome plant dry weight increased with increasing distance between the weeds and wheat.

Influence of end-grazing forage residual and grazing management on lamb growth performance and crop yield from irrigated dual-purpose winter wheat

2010 ◽  
Vol 50 (6) ◽  
pp. 508 ◽  
Author(s):  
D. R. Miller ◽  
G. J. Dean ◽  
P. D. Ball
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Body Condition Score ◽  
Stem Elongation ◽  
Rotational Grazing ◽  
Dual Purpose ◽  
Continuous Grazing ◽  
Condition Score ◽  
Lamb Growth

The effects of end-grazing forage residual and continuous v. rotational grazing systems on prime lamb performance, grain yield and quality were examined in an irrigated dual-purpose winter wheat (cv. Mackellar) crop in Tasmania. The design was a two end-grazing residual (400 and 800 kg/ha of dry matter (DM) at Zadoks Growth Stage 30, Low and High respectively, 0.2 ha plots) × two grazing system (continuously, or rotationally grazed in four subplots) factorial, replicated three times. Mixed-sex, second-cross lambs [37 kg liveweight (LW), 2.5 body condition score, 45 kg DM/head initial feed allowance] grazed for a total of 46 days before removal. Initial feed availability was 1875 kg DM/ha, with final residuals of 520 ± 57 and 940 ± 70 kg DM/ha for the Low and High treatments respectively. Particularly for the Low residual, in vitro DM digestibility and crude protein at stem elongation were reduced (P < 0.05) by rotational compared with continuous grazing. The weekly lamb growth rate (g/day) during the first 5 weeks of grazing was linearly related to average weekly available DM in kg/ha (GR = 0.35 ± 0.041 × DM – 194 ± 49.0, P < 0.01, R2 = 0.56). Total LW produced (336 ± 11.7 kg/ha), and grain yield (6.9 ± 0.21 t/ha), protein (11.4%), screenings <2.2 mm (10.9%) and 100 grain weights (3.82 g DM) were not different between treatments. There were no advantages of rotational grazing compared with continuous grazing. Irrigated dual-purpose winter wheat can be continuously grazed by lambs up to a 500 kg DM/ha residual at stem elongation without compromising total LW produced, grain yields or grain quality.

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