Effect of pre-season management and in-crop herbicdes on weed seedling numbers and triticale grain yield

1988 ◽  
Vol 39 (5) ◽  
pp. 783 ◽  
Author(s):  
PM Dowling
Keyword(s):  
Crop Yield ◽  
Similar Pattern ◽  
Seed Set ◽  
Crop Yields ◽  
Sowing Time ◽  
Polygonum Aviculare ◽  
Herbicide Treatments ◽  
Annual Grasses ◽  
Grass Weed ◽  
Potential Level

Six pre-season treatments which aimed to reduce seed set of annual grasses were imposed at Orange, N.S.W., during spring 1985. Five in-crop treatments (cultivation plus trifluralin, trifluralin, oryzalin plus trifluralin, chlorsulfuron, nil - all direct-drilled) were superimposed over the pre-season treatments at sowing time. Triticale was sown 8 days after application of glyphosate (0.72 kg a.i. ha-1) in May 1986. All pre-season treatments reduced potential grass seedling numbers (89-94% reduction), with the grazing treatments being less effective then the herbicide treatments. Actual grass seedling numbers (those emerging within the crop) followed a similar pattern to potential seedling numbers, but at 10-20% of the potential level. Species not targeted for pre-season management (legume spp., Polygonum aviculare, Poa annua) tended to he present in larger numbers on those pre-season treatments where reduction of the topped grasses was greater. In-crop herbicides did not consistently reduce grass weed seedling numbers further. Grass weeds were more effectively controlled by the cultivation plus trifluralin treatment. Triticale crop yield was reduced as seedling numbers of topped grasses increased. In the direct-drilled situation, it was concluded that satisfactory crop yields will be obtained only after imposition of some form of pre-season management. For longer term grass control, these treatments would need to be imposed in at least two consecutive years.

Effect of row width on herbicide and cultivation requirements in row crops

1992 ◽  
Vol 7 (4) ◽  
pp. 161-167 ◽  
Author(s):  
Frank Forcella ◽  
Mark E. Westgate ◽  
Dennis D. Warnes
Keyword(s):  
Weed Control ◽  
Crop Yield ◽  
Crop Yields ◽  
Row Crops ◽  
Low Input ◽  
Application Rates ◽  
Row Width ◽  
Herbicide Treatments ◽  
Herbicide Use

AbstractCrops grown in narrow rows (NR, 0.25 to 0.38 m) shade weed seedlings more than do those grown in traditional wide rows (WR, 0.76 m). NR crops may require less herbicide and interrow cultivation than WR crops for equally effective weed control. This hypothesis was tested by comparing weed control and crop yield in NR and WR crops when the following percentages of recommended application rates (RAR) of standard herbicides were applied: soybean, 0, 50 and 100%; sunflower, 0, 25, 50, and 100%; and corn, 0, 33, and 100% in three separate sets of experiments conducted over 2, 3, and 4 years, respectively. In all treatments with 100% RAR, excellent weed control prevented reductions in crop yield. When only 25 to 50% RAR was applied, weed control was consistently high in NR (82 to 99% control), but variable in WR (42 to 99% control). Weed control and crop yields typically were lowest in NR without herbicides. Interrow cultivation controlled 0 to 81% of weeds in WR crops. In reduced herbicide treatments (25 to 50% RAR), yields of NR soybean and sunflower typically were about equal to those in WR with 100% RAR, but NR corn yields were about 10% less. Considering the reduced herbicide use and lower weed control costs, planting corn, soybean, and sunflower in narrow rows may represent a practical form of low-input production of these important crops.

scholarly journals Site and hybrid-specific agrotechnical models in sweet corn production

2011 ◽  
pp. 105-108
Author(s):  
Ádám Lente
Keyword(s):  
Crop Yield ◽  
Plant Density ◽  
Sweet Corn ◽  
Crop Yields ◽  
Density Level ◽  
Higher Plant ◽  
Sowing Time ◽  
Corn Production ◽  
High Plant Density ◽  
Crop Density

The effect of three agrotechnical factors (sowing time, fertilization, plant density) and two genotypes on the crop yield of sweet corn was examined on chernozem soil in the Hajdúság region in two different crop years. Compared to the 30-year average, the climate was dry and warm in 2009 and humid in 2010. The experiments were conducted at the Látókép Research Site of the University of Debrecen. In the experiments we applied two sowing times (end of April, end of May), six fertilization levels (control, N30+PK, N60+PK, N90+PK, N120+PK, N150+PK) and two crop density levels (45 thousand ha-1, 65 thousand ha-1). The hybrids we used were Jumbo and Enterprise. As regards the requirements of sweet corn production, the crop year of 2009 was dry and warm. The effect of moisture deficiency was more adverse on the crop yields with the second sowing time. On the contrary, the other examined year (2010) was significantly humid; the precipitation was 184 mm above the 30-year average and the temperature was average.In the dry and hot crop year, the best yields were obtained with the hybrid Jumbo (25677 kg-1) at 65 thousand ha-1 plant density level on the average of the fertilization levels. The crop yields of Enterprise were also the highest at high plant density level (24444 kg ha-1). With the second sowing time the highest yields were obtained at the higher plant density level (65 thousand ha-1) with both hybrids (Jumbo 18978 kg ha-1, Enterprise 18991 kg ha-1), which confirmed the good adaptation capability of these hybrids at high plant density level. In humid crop year with early sowing time the highest yielding hybrid was Enterprise (at 45 thousand ha-1 crop density level 20757 kg-1), at the same time, Jumbo was best yielding at the higher plant density level (18781 kg-1). With the second sowing time the highest crop yield was obtained with Enterprise again (20628 kg ha-1 at 65 thousand ha-1 plant density level). With this sowing time the average yields of Jumbo, was 18914 kg ha-1 respectively. We found that dry crop year and early sowing time provided the best conditions for sweet corn production; the highest yields were obtained under these circumstances, which might be the results of the outstanding water management of chernozem  soils.

Weed control in peanuts in north Queensland

1981 ◽  
Vol 21 (109) ◽  
pp. 218
Author(s):  
D Hawton ◽  
IDG Johnson
Keyword(s):  
Adverse Effects ◽  
Weed Control ◽  
Crop Yield ◽  
Active Ingredient ◽  
Crop Yields ◽  
Single Application ◽  
Monetary Value ◽  
Hyptis Suaveolens ◽  
Herbicide Treatments ◽  
Foliar Damage

Experiments conducted over two seasons with Virginia Bunch peanuts on krasnozem soils in north Queensland showed that cultivation controlled weeds sufficiently to prevent significant reduction of crop value. In one of these experiments two cultivations made 2 and 5 weeks after sowing increased the percentage of edible kernel by a mean of 4.8%. A range of herbicides tested in conjunction with cultivation did not significantly increase crop yields or weed control over that obtained by cultivation. Most of the herbicide treatments had no adverse effects on crop yield although some foliar damage occurred on plants treated with vernolate, MCPB, 2,4-DB and dinoseb. Vernolate, incorporated before planting at 4.78 kg active ingredient ha-1 caused a reduction in yield of nut-in-shell and in crop value when compared with the hand weeded, cultivated control. In both experiments, uncontrolled weeds markedly reduced crop yields (by a mean of 69%) and their monetary value (by a mean of 68%). In a third experiment a single application of 2,4-DB plus dinbseb (0.5 kg acid equivalent ha-1 each) made 3 weeks after sowing, with or without multiple applications of 2,4-DB (0.5 kg acid equivalent ha-1) made at 6,9 and 12 weeks, did not significantly reduce crop yields or values, and increased the control of Hyptis suaveolens and other broad-leaved weeds when compared with a standard trifluralin-plus cultivation treatment.

Control of annual grasses by spraytopping and the effect on triticale grain yield

1993 ◽  
Vol 44 (8) ◽  
pp. 1959 ◽  
Author(s):  
PM Dowling ◽  
HI Nicol
Keyword(s):  
Grain Yield ◽  
Seed Set ◽  
Application Rate ◽  
Wetting Agent ◽  
Annual Grass ◽  
Annual Grasses ◽  
Total Seed ◽  
Main Component ◽  
Grass Sward ◽  
Grass Weed

IA range of pre-season management treatments was imposed on a mixed annual grass sward in October 1987, prior to planting triticale into a cultivated and a direct-drilled seedbed in June 1988. The management treatments included three rates of glyphosate: Roundup� (110, 180, 360 g a.i./ha); two rates of paraquat: Gramoxone� (100, 200 g a.i. ha); and one rate of fluazifop-butyl: Fusilade� (53 g a.i./ha � Pulse� wetting agent). All treatments decreased potential grass regeneration, with V. bromozdes being the least affected. Improved control was achieved by increasing application rate, and by adding a wetting agent to fluazifop. Actual grass seedlings emerging within the crop followed a similar pattern to potential grass regeneration. Grass emergence, particularly of V. bromoides and L. rigidum, was always greater on the direct-drilled seedbed. Grain yield was greater on the prepared seedbed. On both seedbeds, yield was inversely related to grass DM 97 days after sowing (DAS) and grass weed seedling numbers 50 DAS. The effectiveness of the herbicides appeared to be related to maturity dates of the target species. The high potential seed-set of the annual grasses present (> 500 000/m2), of which V. bromozdes was the main component, highlights the difficulty of controlling such species. It is suggested that the large apparent decline from total seed-set to potential seedling numbers (14000/m2) resulted from the high stocking pressure by sheep over summer. For a number of annual grasses, a more rapid method for determining seed number based on seed weight and seedhead number is proposed, providing a more informed basis for decision making. We conclude that spraytopping to maximize yield of later sown direct-drilled crops (e.g. triticale) is essential, despite the difficulty in optimizing timing of spraytopping in mixed pasture swards.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

scholarly journals The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Production ◽  
Yield Loss ◽  
Crop Yields ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Arable Farming ◽  
Herbicide Use ◽  
The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

A Comparison of Subjective and Historical Crop Yield Probability Distributions

1992 ◽  
Vol 24 (2) ◽  
pp. 23-32 ◽  
Author(s):  
James W. Pease
Keyword(s):  
Crop Yield ◽  
Subjective Probability ◽  
Crop Yields ◽  
Probability Distributions ◽  
Geographical Location ◽  
Subjective Expectations ◽  
Grain Farms ◽  
Western Kentucky ◽  
Relative Variability

AbstractForecast distributions based on historical yields and subjective expectations for 1987 expected crop yields were compared for 90 Western Kentucky grain farms. Different subjective probability elicitation techniques were also compared. In many individual cases, results indicate large differences between subjective and empirical moments. Overall, farmer expectations for 1987 corn yields were below those predicted from their past yields, while soybean expectations were above the historical forecast. Geographical location plays a larger role than crop in comparisons of relative variability of yield. Neither elicitation technique nor manager characteristics have significant effects on the comparisons of the forecasts.

Annual Grass Control in Alfalfa (Medicago sativa) with Postemergence Graminicides

1992 ◽  
Vol 6 (4) ◽  
pp. 938-948 ◽  
Author(s):  
Chester L. Foy ◽  
Harold L. Witt
Keyword(s):  
Medicago Sativa ◽  
Field Experiments ◽  
Annual Grass ◽  
Giant Foxtail ◽  
Herbicide Treatments ◽  
Highly Effective ◽  
Annual Grasses ◽  
Large Crabgrass

Field experiments were conducted during 1982 to 1988 in Virginia to evaluate BAS 517, CGA 82725, clethodim, cloproxydim, fenoxaprop, fluazifop, fluazifop-P, haloxyfop, paraquat, quizalofop, SC-1084, sethoxydim, sethoxydim plus thifensulfuron, and terbacil for control of annual grasses in alfalfa. Herbicides were applied to alfalfa and grasses 2 to 30 cm in height after the first and/or second cuttings. Overall, the herbicides were highly effective in controlling fall panicum, giant foxtail, barnyardgrass, and large crabgrass. Alfalfa yields were not increased with herbicide treatments in several experiments. Only paraquat, applied later than recommended after cutting in one experiment, and sethoxydim plus thifensulfuron at one location reduced alfalfa yields.

scholarly journals Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 9-18 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Marcio Koiti Chiba ◽  
Célia Regina Grego
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spherical Model ◽  
Exponential Model ◽  
Spatial And Temporal Variability ◽  
No Tillage ◽  
Yield Data ◽  
The North ◽  
Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

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