Late-season Prediction Of Wheat Grain Yield And Grain Protein

2003 ◽  
Vol 34 (13-14) ◽  
pp. 1837-1852 ◽  
Author(s):  
K. W. Freeman ◽  
W. R. Raun ◽  
G. V. Johnson ◽  
R. W. Mullen ◽  
M. L. Stone ◽  
...  
Keyword(s):  
Grain Yield ◽  
Grain Protein ◽  
Wheat Grain ◽  
Late Season

Effect of weeds and nitrogen fertiliser on yield and grain protein concentration of wheat

1996 ◽  
Vol 36 (4) ◽  
pp. 443 ◽  
Author(s):  
MG Mason ◽  
RW Madin
Keyword(s):  
Grain Yield ◽  
Weed Control ◽  
Dry Matter ◽  
Protein Concentration ◽  
The Other ◽  
Grain Protein ◽  
Dry Matter Yield ◽  
Wheat Grain ◽  
Grain Protein Concentration ◽  
Nitrogen Fertiliser

Field trials at Beverley (19911, Salmon Gums (1991; 2 sites) and Merredin (1992; 2 sites), each with 5 rates of nitrogen (N) and 3 levels of weed control, were used to investigate the effect of weeds and N on wheat grain yield and protein concentration during 1991 and 1992. Weeds in the study were grasses (G) and broadleaf (BL). Weeds reduced both vegetative dry matter yield and grain yield of wheat at all sites except for dry matter at Merredin (BL). Nitrogen fertiliser increased wheat dry matter yield at all sites. Nitrogen increased wheat grain yield at Beverley and Merredin (BL), but decreased yield at both Salmon Gums sites in 1991. Nitrogen fertiliser increased grain protein concentration at all 5 sites-at all rates for 3 sites [Salmon Gums (G) and (BL) and Merredin (G)] and at rates of 69 kg N/ha or more at the other 2 sites [Beverley and Merredin (BL)]. However, the effect of weeds on grain protein varied across sites. At Merredin (G) protein concentration was higher where there was no weed control, possibly due to competition for soil moisture by the greater weed burden. At Salmon Gums (G), grain protein concentration was greater when weeds were controlled than in the presence of weeds, probably due to competition for N between crop and weeds. In the other 3 trials, there was no effect of weeds on grain protein. The effect of weeds on grain protein appears complex and depends on competition between crop and weeds for N and for water at the end of the season, and the interaction between the two.

Nitrogen Rate and Timing Effects on Winter Wheat Grain Yield, Grain Protein, and Economics

jpa ◽  
1990 ◽  
Vol 3 (3) ◽  
pp. 324-328 ◽  
Author(s):  
B. Vaughan ◽  
D. G. Westfall ◽  
K. A. Barbarick
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Grain Protein ◽  
Wheat Grain ◽  
Nitrogen Rate ◽  
Timing Effects

scholarly journals Multi-Temporal and Spectral Analysis of High-Resolution Hyperspectral Airborne Imagery for Precision Agriculture: Assessment of Wheat Grain Yield and Grain Protein Content

2018 ◽  
Vol 10 (6) ◽  
pp. 930 ◽  
Author(s):  
Francelino A. Rodrigues ◽  
Gerald Blasch ◽  
Pierre BlasDefournych ◽  
J. Ivan Ortiz-Monasterio ◽  
Urs Schulthess ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
High Resolution ◽  
Grain Yield ◽  
Protein Content ◽  
Precision Agriculture ◽  
Grain Protein Content ◽  
Grain Protein ◽  
Wheat Grain ◽  
Multi Temporal

Yield and grain protein of wheat following phased perennial grass, lucerne, and annual pastures

2004 ◽  
Vol 55 (7) ◽  
pp. 775 ◽  
Author(s):  
B. S. Dear ◽  
G. A. Sandral ◽  
J. M. Virgona ◽  
A. D. Swan
Keyword(s):  
Grain Yield ◽  
Soil Water ◽  
Subterranean Clover ◽  
Perennial Grasses ◽  
Annual Rainfall ◽  
Grain Protein ◽  
Wheat Grain ◽  
Total N ◽  
Protein Levels ◽  
Early Removal

The effect of using 4 perennial grasses or lucerne (Medicago sativa L.) in the pasture phase on subsequent wheat grain yield, protein, and grain hardness was investigated at 2 sites (Kamarah and Junee) in the south-eastern Australian cereal belt. The 6 perennial treatments were 5 mixtures of subterranean clover (Trifolium subterraneum L.), with one of lucerne, phalaris (Phalaris aquatica L.), cocksfoot (Dactylis glomerata L), wallaby grass (Austrodanthonia richardsonii (Cashm.) H.P. Linder), or lovegrass (Eragrostis curvula (Schrader) Nees cv. Consol), or one mixture of cocksfoot, phalaris, and lucerne. The results were compared with wheat after one of 3 annual pastures consisting of either pure subterranean clover, subterranean clover with annual volunteer broadleaf and grass weeds, or yellow serradella (Ornithopus compressus L.). The duration of the pasture phase was 3 years at the drier Kamarah site (av. annual rainfall 430 mm) and 4 years at Junee (550 mm). The effect of time of removal of the pastures in the year prior to cropping (28 August–3 September or 6–7 November) and the effect of nitrogen (N) fertiliser application were also examined. In the absence of applied N, wheat grain yields at Kamarah were highest (4.7–4.9 t/ha) and grain protein lowest (10.3–11.1%) following phalaris, wallaby grass, and cocksfoot. Grain protein levels were highest (12.9–13.9%) in wheat following the 3 annual legume swards at both sites. Previous pasture type had no effect on wheat yields at the Junee site. Wheat grain protein and total N taken up by the crop were positively related to available soil N to 100 cm measured at sowing at both sites. Grain protein was inversely related to grain yield at both sites where additional N fertiliser was added, but not in the absence of fertiliser N. There was a positive response in grain protein to delayed time of pasture removal in second year wheat at Junee. The application of additional N fertiliser increased grain protein of wheat following all 9 pasture types at the drier Kamarah site, but at the Junee site there was only a positive grain protein response following phalaris, cocksfoot, and wallaby grass. Early removal of the pasture prior to cropping increased soil water (10–130 cm) at sowing by 18 mm, delayed wheat senescence, and increased crop yield by 11% (0.44 t/ha) at the drier Kamarah site. Early removal of the pasture at Junee increased soil water by 29 mm, crop yields by 2% (0.14 t/ha), and increased grain protein in wheat following cocksfoot, wallaby grass, and phalaris, but not following the 3 annual legume treatments. The study demonstrated that perennial grasses can be successfully incorporated into phased rotations with wheat without affecting grain yield, but protein levels may be lower and timing of pasture removal will be important to limit the effect of water deficits on grain yield.

Site-specific variation in wheat grain protein concentration and wheat grain yield measured on an Australian farm using harvester-mounted on-the-go sensors

2009 ◽  
Vol 60 (9) ◽  
pp. 808 ◽  
Author(s):  
Brett M. Whelan ◽  
James A. Taylor ◽  
James A. Hassall
Keyword(s):  
Spatial Variability ◽  
Grain Yield ◽  
Spatial Variation ◽  
Protein Concentration ◽  
Spatial Coherence ◽  
Grain Protein ◽  
Wheat Grain ◽  
Field Scale ◽  
Grain Protein Concentration ◽  
Nitrogen Inputs

Accurately measuring and understanding the fine-scale relationship between wheat grain yield (GY) and the concomitant grain protein concentration (GPC) should provide valuable information to improve the management of nitrogen inputs. Here, GPC and GY were monitored on-harvester for three seasons across 27 paddocks on an Australian farming enterprise using two independent, on-the-go sensing systems. A Zeltex Accuharvest measured GPC (%) and a John Deere GreenStar system measured GY (t/ha). Local calibration in each season for Australian spring wheat significantly improved the prediction accuracy, precision, and bias of the Zeltex Accuharvest when compared with the initial factory calibration. Substantial variation in GPC and GY was recorded at the field scale, with the least variation recorded in both parameters in the wetter season. GY (CV = 38%) was twice as variable on average as GPC (CV = 19%) across the enterprise. At this enterprise scale, a negative correlation between GPC and GY was observed for a composite of the field data from all seasons (r = –0.48); however, at the within-field scale the relationship was shown to vary from positive (max. = +0.41) to negative (min. = –0.65). Spatial variation in GPC and GY at the within-field scale was described best in the majority of cases by an exponential semivariogram model. Within-field spatial variability in GPC is more strongly autocorrelated than GY but on average they share a similar autocorrelated range (a′ = ~190 m). This spatial variability in GPC and GY gave rise to local spatial variation in the correlation between GPC and GY, with 85% of the fields registering regions of significant negative correlations (P < 0.01) and significant positive correlations observed in 70% of fields. The spatial pattern in these regions of significantly different correlations is shown to display spatial coherence from which inferences regarding the relative availability of soil nitrogen and moisture are suggested. The results point to the suitability of these on-the-go sensors for use in more sophisticated agronomic and environmentally targeted nitrogen-use analysis.

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