Effect of previous crop and herbicides on weed growth and wheat yield

2005 ◽  
Vol 85 (3) ◽  
pp. 735-746 ◽  
Author(s):  
J. R. Moyer ◽  
R. E. Blackshaw ◽  
R. C. Doram ◽  
H. C. Huang ◽  
T. Entz
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Research Centre ◽  
Soil Biology ◽  
Wheat Growth ◽  
Available N ◽  
Previous Crop ◽  
Weed Growth ◽  
Available Soil Moisture

Field experiments were established in 1998, 1999 and 2000 at the Lethbridge Research Centre to examine the effect of preceding annual crops and accompanying recommended herbicides on weed infestations in following winter and spring wheat (Triticum aestivum L.). Seven crops and fallow were established in year 1 with and without herbicides for weed control. In year 2, spring and winter wheat were grown without herbicides and with minimal fertilizer inputs to measure the effect of the previous crop and herbicides on weed and crop growth, available N and P, and available soil moisture. Lentil (Lens culinaris Medic) as a previous crop provided an environment that promoted wheat growth but not weed growth. In contrast, mustard (Brassica juncea L.) as a previous crop inhibited spring and winter wheat growth, but did not inhibit total weed biomass production in year 2. The beneficial effects of lentil and the detrimental effects of mustard were partially explained by available soil moisture and soil N for the second crop but additional factors, such as allelopathic chemicals or changes in soil biology, must be involved to cause the large differences in weed and wheat growth that were observed in year 2. The lack of herbicides with some crops led to dense weed populations in year 2. In addition, N, P, moisture utilization, and possible additional changes in soil biology or chemistry caused by uncontrolled weeds affected wheat yield after lentil and fallow. Key words: Available soil moisture, available soil nitrogen, crop rotation, lentil, mustard, weed density

scholarly journals The Modification of Difference Vegetation Index (DVI) in middle and late growing period of winter wheat and its application in soil moisture inversion

2019 ◽  
Vol 131 ◽  
pp. 01098
Author(s):  
Zhang Hong-wei ◽  
Huai-liang Chen ◽  
Fei-na Zha
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Vegetation Index ◽  
Vegetation Coverage ◽  
Growth Stages ◽  
Wheat Growth ◽  
Inversion Result ◽  
Growing Period ◽  
The Difference ◽  
Different Growth Stages

In the middle and late growing period of winter wheat, soil moisture is easily affected by saturation when using MODIS data to retrieve soil moisture. In this paper, in order to reduce the effect of the saturation caused by increasing vegetation coverage in middle and late stage of winter wheat, the Difference Vegetation Index (DVI) model was modified with different coefficients in different growth stages of winter wheat based on MODIS spectral data and LAI characteristics of variation. LAI was divided into three stages, LAI ≤ 1 < LAI ≤, 3 < LAI, and the adjusting coefficient of α=1, α=3, α=5, were taken to modifying the Difference Vegetation Index(DVI). The results show that the Modified Difference Vegetation Index (MDVIα) can effectively reduce the interference of saturation, and the inversion result of soil moisture in the middle and late period of winter wheat growth is obviously superior to the uncorrected inversion model of DVI.

scholarly journals Joint Assimilation of Leaf Area Index and Soil Moisture from Sentinel-1 and Sentinel-2 Data into the WOFOST Model for Winter Wheat Yield Estimation

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3161 ◽  
Author(s):  
Haizhu Pan ◽  
Zhongxin Chen ◽  
Allard de Wit ◽  
Jianqiang Ren
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Winter Wheat ◽  
Crop Yield ◽  
Wheat Yield ◽  
Crop Growth ◽  
Open Loop ◽  
Yield Estimation ◽  
Spatiotemporal Resolution ◽  
Sentinel 2

It is well known that timely crop growth monitoring and accurate crop yield estimation at a fine scale is of vital importance for agricultural monitoring and crop management. Crop growth models have been widely used for crop growth process description and yield prediction. In particular, the accurate simulation of important state variables, such as leaf area index (LAI) and root zone soil moisture (SM), is of great importance for yield estimation. Data assimilation is a useful tool that combines a crop model and external observations (often derived from remote sensing data) to improve the simulated crop state variables and consequently model outputs like crop total biomass, water use and grain yield. In spite of its effectiveness, applying data assimilation for monitoring crop growth at the regional scale in China remains challenging, due to the lack of high spatiotemporal resolution satellite data that can match the small field sizes which are typical for agriculture in China. With the accessibility of freely available images acquired by Sentinel satellites, it becomes possible to acquire data at high spatiotemporal resolution (10–30 m, 5–6 days), which offers attractive opportunities to characterize crop growth. In this study, we assimilated remotely sensed LAI and SM into the Word Food Studies (WOFOST) model to estimate winter wheat yield using an ensemble Kalman filter (EnKF) algorithm. The LAI was calculated from Sentinel-2 using a lookup table method, and the SM was calculated from Sentinel-1 and Sentinel-2 based on a change detection approach. Through validation with field data, the inverse error was 10% and 35% for LAI and SM, respectively. The open-loop wheat yield estimation, independent assimilations of LAI and SM, and a joint assimilation of LAI + SM were tested and validated using field measurement observation in the city of Hengshui, China, during the 2016–2017 winter wheat growing season. The results indicated that the accuracy of wheat yield simulated by WOFOST was significantly improved after joint assimilation at the field scale. Compared to the open-loop estimation, the yield root mean square error (RMSE) with field observations was decreased by 69 kg/ha for the LAI assimilation, 39 kg/ha for the SM assimilation and 167 kg/ha for the joint LAI + SM assimilation. Yield coefficients of determination (R2) of 0.41, 0.65, 0.50, and 0.76 and mean relative errors (MRE) of 4.87%, 4.32%, 4.45% and 3.17% were obtained for open-loop, LAI assimilation alone, SM assimilation alone and joint LAI + SM assimilation, respectively. The results suggest that LAI was the first-choice variable for crop data assimilation over SM, and when both LAI and SM satellite data are available, the joint data assimilation has a better performance because LAI and SM have interacting effects. Hence, joint assimilation of LAI and SM from Sentinel-1 and Sentinel-2 at a 20 m resolution into the WOFOST provides a robust method to improve crop yield estimations. However, there is still bias between the key soil moisture in the root zone and the Sentinel-1 C band retrieved SM, especially when the vegetation cover is high. By active and passive microwave data fusion, it may be possible to offer a higher accuracy SM for crop yield prediction.

Cereal cover crops for weed suppression in a summer fallow-wheat cropping sequence

2000 ◽  
Vol 80 (2) ◽  
pp. 441-449 ◽  
Author(s):  
J. R. Moyer ◽  
R. E. Blackshaw ◽  
E. G. Smith ◽  
S. M. McGinn
Keyword(s):  
Winter Wheat ◽  
Weed Control ◽  
Cover Crops ◽  
Soil Conservation ◽  
Cover Crop ◽  
Wheat Yield ◽  
Weed Suppression ◽  
Wheat Crop ◽  
Weed Growth ◽  
Summer Fallow

Cropping systems in western Canada that include summer fallow can leave the soil exposed to erosion and require frequent weed control treatments. Cover crops have been used for soil conservation and to suppress weed growth. Experiments were conducted under rain-fed conditions at Lethbridge, Alberta to determine the effect of short-term fall rye (Secale cereale L.), winter wheat (Triticum aestivum L.) and annual rye cover crops in the fallow year on weed growth and subsequent wheat yield. Under favorable weather conditions fall rye was as effective as post-harvest plus early spring tillage or herbicides in spring weed control. Winter wheat and fall rye residues, after growth was terminated in June, reduced weed biomass in September by 50% compared to no cover crop in 1993 but had little effect on weeds in 1995. Fall-seeded cover crops reduced the density of dandelion (Taraxacum officinale Weber in Wiggers) and Canada thistle [Cirsium arvense (L.) Scop.] but increased the density of downy brome (Bromus tectorum L.), wild buckwheat (Polygonum convolvulus L.), and thyme-leaved spurge (Euphorbia serpyllifolia Pers.) in the following fall or spring. Wheat yields after fall rye and no cover crop were similar but yields after spring-seeded annual rye were less than after no cover crop. Spring-seeded annual rye did not adequately compete with weeds. Cover crops, unlike the no cover crop treatment, always left sufficient plant residue to protect the soil from erosion until the following wheat crop was seeded. Key words: Allelopathies, fall rye, nitrogen, soil conservation, soil moisture, weed control, spring rye, winter wheat

Interseeding berseem clover in winter wheat

2017 ◽  
Vol 32 (6) ◽  
pp. 573-575
Author(s):  
Randy L. Anderson
Keyword(s):  
Winter Wheat ◽  
Seedling Survival ◽  
Seedling Emergence ◽  
Wheat Yield ◽  
Planting Dates ◽  
Wheat Growth ◽  
Drought Tolerant ◽  
Winter Wheat Yield ◽  
Berseem Clover ◽  
Preceding Winter

AbstractInterseeding annual clovers in cereal grains may help organic producers reduce use of tillage following cereal harvest. Using clovers that winterkill would minimize need for tillage in the spring also. The objective of this study was to evaluate seedling emergence and survival of berseem clover (Trifolium alexandrinum L.) in winter wheat (Triticum aestivum L.). Berseem clover (hereafter, referred to as berseem) was planted 0, 2 and 4 weeks after initiation of winter wheat growth in the spring. Berseem density was highest when planted on April 12, 2 weeks after winter wheat broke dormancy. Establishment density was 40–80% less with the other planting dates. A dry interval during the 5 weeks preceding winter wheat harvest reduced seedling survival of berseem, killing more than 80% of seedlings. Winter wheat yield was reduced at the last planting date of berseem, which was attributed to mechanical injury to winter wheat by the drill when planting berseem. Berseem may not be viable for interseeding at this location or in drier regions. Clover species that are more drought tolerant will be needed.

Fall-seeded cover crops after dry bean and potato in Southern Alberta

2009 ◽  
Vol 89 (1) ◽  
pp. 133-139 ◽  
Author(s):  
J. R. Moyer ◽  
R. E. Blackshaw
Keyword(s):  
Cover Crops ◽  
Solanum Tuberosum L ◽  
Wheat Yield ◽  
Ground Cover ◽  
Plant Residue ◽  
Research Centre ◽  
Dry Bean ◽  
Available N ◽  
Southern Alberta ◽  
Winter Annual

Dry bean (Phaseolus vulgaris L.) and potato (Solanum tuberosum L.) usually provide insufficient plant residue cover after harvest to protect the soil from wind erosion. Experiments were conducted at the Lethbridge Research Centre to determine the potential beneficial effects of planting cereal cover crops after Russett Burbank potato, which is harvested in late September or October, and dry bean, which is harvested in mid- to late September at Lethbridge, Alberta. Annual cereals planted after potato provided insufficient ground cover to protect the soil from erosion in the fall or spring. Winter annual cereals after potato and dry bean and annual cereals after dry bean usually provided enough residue in the spring (> 30% ground cover). However, winter cereals killed with glyphosate just before seeding spring wheat (Triticum aestivum L.) consistently reduced wheat yield. Reductions in available N and soil moisture due to winter annual cereals were small, and likely did not reduce wheat yield. None of the cover crops provided enough ground cover to reduce weed density. Additional research is required to assess the benefits of seeding annual cereals after early-maturing potato varieties and after dry bean, which matures earlier at lower elevations in southern Alberta, with more heat units. Key words: Fall rye, ground cover, soil erosion, winter triticale

Response of Wheat to Sewage Sludge Applied Under Two Different Moisture Regimes

1995 ◽  
Vol 31 (3) ◽  
pp. 355-360 ◽  
Author(s):  
W. A. Al-Mustafa ◽  
A. A. El-Shall ◽  
A. E. Abdallah ◽  
A. S. Modaihsh
Keyword(s):  
Soil Moisture ◽  
Sewage Sludge ◽  
Field Experiment ◽  
Grain Yield ◽  
Wheat Yield ◽  
Nutrient Content ◽  
Significant Response ◽  
Irrigation Regimes ◽  
Moisture Regimes ◽  
Available Soil Moisture

SummaryA field experiment was conducted from 1989 to 1992 to investigate the effect of sewage sludge applications on wheat yield under different irrigation regimes. The sewage sludge was applied at rates equivalent to 0, 20 or 60 t ha-1 whenever the available soil moisture reached 30 or 70%. The results showed a significant response in grain yield and its nutrient content with no significant differences between rates of sewage sludge applied. Much higher responses were obtained under the wet than under the dry regime.

scholarly journals Evaluation of Drought Monitoring Effect of Winter Wheat in Henan Province of China Based on Multi-Source Data

2020 ◽  
Vol 12 (7) ◽  
pp. 2801
Author(s):  
Yuan Li ◽  
Yi Dong ◽  
Dongqin Yin ◽  
Diyou Liu ◽  
Pengxin Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Growth Period ◽  
Henan Province ◽  
Agricultural Drought ◽  
Individual Growth ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Winter Wheat Yield

Monitoring agricultural drought is important to food security and the sustainable development of human society. In order to improve the accuracy of soil moisture and winter wheat yield estimation, drought monitoring effects of optical drought index data, meteorological drought data, and passive microwave soil moisture data were explored during individual and whole growth periods of winter wheat in 2003–2011, taking Henan Province of China as the research area. The model of drought indices and relative meteorological yield of winter wheat in individual and whole growth periods was constructed based on multiple linear regression. Results showed a higher correlation between Moderate-Resolution Imaging Spectroradiometer (MODIS) drought indices and 10 cm relative soil moisture (RSM10) than 20 cm (RSM20) and 50 cm (RSM50). In the whole growth period, the correlation coefficient (R) between vegetation supply water index (VSWI) and RSM10 had the highest correlation (R = −0.206), while in individual growth periods, the vegetation temperature condition index (VTCI) was superior to the vegetation health index (VHI) and VSWI. Among the meteorological drought indices, the 10-day, 20-day, and 30-day standard precipitation evapotranspiration indices (SPEI1, SPEI2, and SPEI3) were all most relevant to RSM10 during individual and whole growth periods. RSM50 and SPEI3 had a higher correlation, indicating that deep soil moisture was more related to drought on a long time scale. The relationship between Advanced Microwave Scanning Radiometer for EOS soil moisture (AMSR-E SM) and VTCI was stable and significantly positive in individual and whole growth periods, which was better compared to VHI and VSWI. Compared with the drought indices and the relative meteorological yield in the city, VHI had the best monitoring effect during individual and whole growth periods. Results also showed that drought occurring at the jointing–heading stage can reduce winter wheat yield, while a certain degree of drought occurring at the heading–milk ripening stage can increase the yield. In the whole growth period, the combination of SPEI1, SPEI2, and VHI had the best performance, with a coefficient of determination (R2) of 0.282 with the combination of drought indices as the independent variables and relative meteorological yield as the dependent variable. In the individual growth period, the model in the later growth period of winter wheat performed well, especially in the returning green–jointing stage (R2 = 0.212). Results show that the combination of multiple linear drought indices in the whole growth period and the model in the returning green–jointing period could improve the accuracy of winter wheat yield estimation. This study is helpful for effective agricultural drought monitoring of winter wheat in Henan Province.

scholarly journals Zonal Tillage as Innovative Element of the Technology of Growing Winter Wheat: A Field Experiment under Low Rainfall Conditions

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 105 ◽  
Author(s):  
Iwona Jaskulska ◽  
Dariusz Jaskulski ◽  
Marek Różniak ◽  
Maja Radziemska ◽  
Lech Gałęzewski
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Field Experiment ◽  
Grain Yield ◽  
Yield Components ◽  
Growth And Yield ◽  
Soil Tillage ◽  
Positive Dependence ◽  
Previous Crop ◽  
Plant Emergence

Zonal tillage, including strip-till, can have a positive effect on soil properties, seed germination, plant emergence, growth, and yield of crops. The aim of this two-factor field experiment was to compare different technologies of basic soil tillage, fertilisation, and sowing of winter wheat carried out after two post-harvest agrotechnical practises in a region with low rainfall. The three treatments of the first factor were: conventional technology (CT)—plough tillage, pre-sowing fertilisation, seedbed preparation and sowing; reduced technology (RT)—plough tillage replaced with deep loosening and (ST)—one pass strip-till technology using a hybrid machine. Agrotechnical practises carried out after the harvest of the previous crop were the second factor treatments, i.e., crushed straw and shallow tillage (TS), mulch from crushed straw (MS). The measurement of the treatment effects included changes in soil moisture, plant emergence, yield components and their correlation, grain yield, and the dependence of the yield components on soil moisture. Wheat growing in ST technology resulted in a higher soil moisture than in RT and CT. Only immediately after winter was the soil moisture similar. Grain yield in ST was similar as in CT and significantly, up to 10.4%, higher than in RT. The higher ST grain yield resulted from uniform plant emergence, greater ear density, and grain weight per ear. The correlation between yield components was weaker in ST than in CT and RT. The positive dependence of the size of the crop components on soil moisture was also weaker. The agrotechnical practises performed right after the previous crop harvest affected neither the soil moisture during the growing season of winter wheat, nor the grain yield and its components.

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