scholarly journals Improvement of Wheat Grain Yield Prediction Model Performance Based on Stacking Technique

2021 ◽  
Vol 11 (24) ◽  
pp. 12164
Author(s):  
Changchun Li ◽  
Yilin Wang ◽  
Chunyan Ma ◽  
Weinan Chen ◽  
Yacong Li ◽  
...  
Keyword(s):  
Prediction Model ◽  
Grain Yield ◽  
Growth Stage ◽  
Prediction Models ◽  
Vegetation Indices ◽  
Model Performance ◽  
Grain Filling ◽  
Growth Stages ◽  
Wheat Grain ◽  
Area Index

Crop growth and development is a dynamic and complex process, and the essence of yield formation is the continuous accumulation of photosynthetic products from multiple fertility stages. In this study, a new stacking method for integrating multiple growth stages information was proposed to improve the performance of the winter wheat grain yield (GY) prediction model. For this purpose, crop canopy hyperspectral reflectance and leaf area index (LAI) data were obtained at the jointing, flagging, anthesis and grain filling stages. In this case, 15 vegetation indices and LAI were used as input features of the elastic network to construct GY prediction models for single growth stage. Based on Stacking technique, the GY prediction results of four single growth stages were integrated to construct the ensemble learning framework. The results showed that vegetation indices coupled LAI could effectively overcome the spectral saturation phenomenon, the validated R2 of each growth stage was improved by 10%, 22.5%, 3.6% and 10%, respectively. The stacking method provided more stable information with higher prediction accuracy than the individual fertility results (R2 = 0.74), and the R2 of the model validation phase improved by 236%, 51%, 27.6%, and 12.1%, respectively. The study can provide a reference for GY prediction of other crops.

Relating active optical sensor measurements to barley yield

2017 ◽  
Vol 8 (2) ◽  
pp. 162-166
Author(s):  
R. Hackett
Keyword(s):  
Grain Yield ◽  
Optical Sensor ◽  
Growth Stage ◽  
Stem Elongation ◽  
Vegetation Indices ◽  
Growth Stages ◽  
N Addition ◽  
Crop Growth Stages ◽  
Elongation Phase ◽  
Reflectance Measurements

The objective of this work was to determine the most appropriate growth stage to make reflectance measurements that would indicate yield in high yielding winter barley crops. The results indicated that where different rates of fertiliser N were applied, at the same crop growth stages, the best relationship between vegetation indices, calculated on the basis of reflectance measurements, and grain yield were found to occur from booting to early grain fill. Where the timing of fertiliser N inputs was different, for a given level of fertiliser N addition, poor correlations between vegetation indices and grain yield during the stem elongation phase were observed.

scholarly journals Growth stage of Phalaris minor Retz. and wheat determines weed control and crop tolerance of four post-emergence herbicides

2017 ◽  
Vol 15 (1) ◽  
pp. e1001
Author(s):  
Rubia Rasool ◽  
Makhan S. Bhullar ◽  
Gurjeet S. Gill
Keyword(s):  
Grain Yield ◽  
Weed Control ◽  
Growth Stage ◽  
Herbicide Tolerance ◽  
Field Studies ◽  
Growth Stages ◽  
Wheat Grain ◽  
Current Recommendation ◽  
Phalaris Minor ◽  
Crop Tolerance

Phalaris minor Retz. has evolved multiple herbicide resistance in wheat growing areas in northwestern India. An understanding of the effect of growth stage on herbicide tolerance of wheat and control of P. minor will help in selecting the most appropriate herbicide for different situations. The weed control and crop safety of four commonly used wheat herbicides (sulfosulfuron, pinoxaden, fenoxaprop plus metribuzin and mesosulfuron plus iodosulfuron), each applied at four different wheat growth stages was investigated in field studies for two years. P. minor plants were at 1, 2-3, 3-4 and 7-8 leaf stages when the herbicides were applied at Zadok 12-Z12, Z13, Z21 and Z23 stages of wheat, respectively. Sulfosulfuron application at Z12 and Z13 wheat stages (before first irrigation), provided >80% control of P. minor and produced wheat grain yield (4.5-4.7 t/ha) similar to the weed-free check (4.9 t/ha) in both years. Pinoxaden, fenoxaprop plus metribuzin and mesosulfuron plus iodosulfuron application at Z12 and Z13 wheat stages recorded significantly lower wheat grain yield (3.62-3.95 t/ha) due to poor weed control, crop toxicity or both. All the four herbicides were equally effective on P. minor when applied at Z21 wheat stage. At Z23 wheat stage, pinoxaden gave >90% control of P. minor and the highest wheat grain yield (4.82 t/ha). The results are expected to allow changes in the current recommendation of the timing of post-emergence herbicides for the management of P. minor in wheat.

Characteristics of the canopy, root system and grain yield of a crop of Lupinus angustifolius cv. Unicrop

1975 ◽  
Vol 26 (3) ◽  
pp. 497 ◽  
Author(s):  
EAN Greenwood ◽  
P Farrington ◽  
JD Beresford
Keyword(s):  
Carbon Dioxide ◽  
Grain Yield ◽  
Leaf Area ◽  
Time Course ◽  
Dry Weight ◽  
Grain Filling ◽  
Main Axis ◽  
Carbon Dioxide Exchange ◽  
Area Index ◽  
Plant Parts

The time course of development of a lupin crop was studied at Bakers Hill, Western Australia. The aim was to gain insight into the crop factors influencing yield. Weekly measurements were made of numbers and weights of plant parts, and profiles of roots, leaf area and light interception. A profile of carbon dioxide in the crop atmosphere was taken at the time of maximum leaf area, and the net carbon dioxide exchange (NCE) of pods was estimated for three successive weeks. The crop took 10 weeks to attain a leaf area index (LAI) of 1 and a further 9 weeks to reach a maximum LAI of 3.75, at which time only 33% of daylight reached the pods on the main axis. Once the maximum LAI was attained at week 19, leaf fall accelerated and rapid grain filling commenced almost simultaneously on all of the three orders of axes which had formed pods. Measurements of NCE between pods on the main axis and the air suggest that the assimilation of external carbon dioxide by the pods contributed little to grain filling. Grain dry weight was 2100 kg ha-1 of which 30%, 60% and 10% came from the main axis, first and second order apical axes respectively. Only 23% of the flowers set pods and this constitutes an important physiological limitation to grain yield.

scholarly journals Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images

Agronomy ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2439
Author(s):  
Haixiao Ge ◽  
Fei Ma ◽  
Zhenwang Li ◽  
Changwen Du
Keyword(s):  
Grain Yield ◽  
Low Cost ◽  
Vegetation Indices ◽  
Model Performance ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Rice Breeding ◽  
Yield Estimation ◽  
Phenological Data ◽  
Significant Difference

The accurate estimation of grain yield in rice breeding is crucial for breeders to screen and select qualified cultivars. In this study, a low-cost unmanned aerial vehicle (UAV) platform mounted with an RGB camera was carried out to capture high-spatial resolution images of rice canopy in rice breeding. The random forest (RF) regression techniques were used to establish yield models by using (1) only color vegetation indices (VIs), (2) only phenological data, and (3) fusion of VIs and phenological data as inputs, respectively. Then, the performances of RF models were compared with the manual observation and CERES-Rice model. The results indicated that the RF model using VIs only performed poorly for estimating yield; the optimized RF model that combined the use of phenological data and color VIs performed much better, which demonstrated that the phenological data significantly improved the model performance. Furthermore, the yield estimation accuracy of 21 rice cultivars that were continuously planted over three years in the optimal RF model had no significant difference (p > 0.05) with that of the CERES-Rice model. These findings demonstrate that the RF model, by combining phenological data and color Vis, is a potential and cost-effective way to estimate yield in rice breeding.

scholarly journals The Influence of Soil Acidity on the Physiological Responses of Two Bread Wheat Cultivars

Plants ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1472
Author(s):  
Brigitta Tóth ◽  
Csaba Juhász ◽  
Maryke Labuschagne ◽  
Makoena Joyce Moloi
Keyword(s):  
Lipid Peroxidation ◽  
Protein Content ◽  
Soil Ph ◽  
Growth Stage ◽  
Grain Filling ◽  
Growth Stages ◽  
Guaiacol Peroxidase ◽  
Antioxidative Capacity ◽  
Wheat Cultivars ◽  
Mda Content

The recent study was conducted to examine the influence of acidic soil on the activities of ascorbate (APX) and guaiacol peroxidase (POD), proline, protein as well as malon-dialdehyde (MDA) content, in two commercial spring wheat cultivars (PAN3497 and SST806) at different growth stages (tillering and grain filling). A cultivar effect was significant only for MDA content, while the treatment effect was highly significant for proline, protein, and MDA. The sampling time effect was significant for most characteristics. MDA, antioxidative capacity, as well as protein content increased with maturity. At grain filling, MDA and proline contents were significantly higher at pH 5 than pH 6 and 7 for both cultivars, with the highest content in SST806. Similarly, SST806 had significantly higher APX and POD when growing at pH 5. There were no significant differences in protein content at grain filling between either genotype or treatments affected by low pH. This study showed that growth stage and soil pH influence the rate of lipid peroxidation as well as the antioxidative capacity of wheat, with a larger effect at grain filling, at pH 5. Although SST806 had higher proline, POD, and APX content than PAN3497 at this growth stage, this coincided with a very high MDA content. This shows that the high antioxidative capacity observed here, was not associated with a reduction of lipid peroxidation under low soil pH. Further research should, therefore, be done to establish the role of the induced antioxidant system in association with growth and yield in wheat.

scholarly journals The Response of Maize Lines to Foliar Fertilizing

Agriculture ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 365
Author(s):  
Milan Brankov ◽  
Milena Simić ◽  
Željko Dolijanović ◽  
Miloš Rajković ◽  
Violeta Mandić ◽  
...  
Keyword(s):  
Amino Acids ◽  
Grain Yield ◽  
Leaf Area ◽  
Harvest Index ◽  
Growth Parameters ◽  
Growth Stages ◽  
Fresh Matter ◽  
Area Index ◽  
Positive Effects ◽  
The Impact

The objective of this study was to evaluate the impact of two foliar fertilizers applied on five maize (Zea mays L.) lines. Fertilizers were applied at different growth stages of maize, during three consecutive years (2010–2012) at the experimental field of the Maize Research Institute “Zemun Polje”, Serbia. Maize growth parameters such as fresh matter, height, leaf area and grain yield were recorded. Foliar fertilizer with amino acids (FAA) was more advantageous to maize plants compared to fertilizer containing phosphorus (FP) as a main component. Applied FAA has shown positive effects by increasing fresh matter, leaf area index, and plant height in all three years. In 2012, due to unfavorable meteorological conditions, grain yield and harvest index were very low, compared to the previous two years, although, positive effects on morphological traits were observed 21 days after treatments (DAT), as well as in the anthesis stage. The best results of 30% of grain yield and harvest index increase were recorded in line L1 in 2010 and 2011. The same line had an increase of more than 40% of fresh matter and leaf area on average for all three years. The positive effects that have been noticed in this research could recommend foliar fertilizing with fertilizer containing N in a form of an amino acids complex.

Relative effectiveness of various sources, methods, times and rates of copper fertilizers in improving grain yield of wheat on a Cu-deficient soil

2005 ◽  
Vol 85 (1) ◽  
pp. 59-65 ◽  
Author(s):  
S. S. Malhi ◽  
L. Cowell ◽  
H. R. Kutcher
Keyword(s):  
Grain Yield ◽  
Protein Concentration ◽  
Growth Stage ◽  
Foliar Application ◽  
Leaf Growth ◽  
Flag Leaf ◽  
Relative Effectiveness ◽  
Growing Season ◽  
Growth Stages ◽  
Cu Deficiency

A field experiment was conducted to determine the relative effectiveness of various sources, methods, times and rates of Cu fertilizers on grain yield, protein concentration in grain, concentration of Cu in grain and uptake of Cu in grain of wheat (Triticum aestivum L.), and residual concentration of DTPA-extractable Cu in soil on a Cu-deficient soil near Porcupine Plain in northeastern Saskatchewan. The experiment was conducted from 1999 to 2002 on the same site, but the results for 2002 were not presented because of very low grain yield due to drought in the growing season. The 25 treatments included soil application of four granular Cu fertilizers (Cu lignosulphonate, Cu sulphate, Cu oxysulphate I and Cu oxysulphate II) as soil-incorporated (at 0.5 and 2.0 kg Cu ha-1), seedrow-placed (at 0.25 and 1.0 kg Cu ha-1) and foliar application of four solution Cu fertilizers (Cu chelate-EDTA, Cu sequestered I, Cu sulphate/chelate and Cu sequestered II at 0.25 kg Cu ha-1) at the four-leaf and flag-leaf growth stages, plus a zero-Cu check. Soil was tilled only once to incorporate all designated Cu and blanket fertilizers into the soil a few days prior to seeding. Wheat plants in the zero-Cu treatment exhibited Cu deficiency in all years. For foliar application at the flag-leaf stage, grain yield increased with all four of the Cu fertilizers in 2000 and 2001, and in all but Cu sequestered II in 1999. Foliar application at the four-leaf growth stage of three Cu fertilizers (Cu chelate-EDTA, Cu sequestered I and Cu sulphate/chelate), soil incorporation of all Cu fertilizers at 2 kg Cu ha-1 and two Cu fertilizers (Cu lignosulphonate and Cu sulphate) at 0.5 kg Cu ha-1 rate, and seedrow placement of two Cu fertilizers (Cu lignosulphonate and Cu sulphate) at 1 kg Cu ha-1 increased grain yield of wheat only in 2001. There was no effect of Cu fertilization on protein concentration in grain. The increase in concentration and uptake of Cu in grain from Cu fertilization usually showed a trend similar to grain yield. There was some increase in residual DTPA-extractable Cu in the 0–60 cm soil in Cu lignosulphonate, Cu sulphate and Cu oxysulphate II soil incorporation treatments, particularly at the 2 kg Cu ha-1 rate. In summary, the results indicate that foliar application of Cu fertilizers at the flag-leaf growth stage can be used for immediate correction of Cu deficiency in wheat. Because Cu deficiency in crops often occurs in irregular patches within fields, foliar application may be the most practical and economical way to correct Cu deficiency during the growing season, as lower Cu rates can correct Cu deficiency. Key words: Application time, Cu source, foliar application, granular Cu, growth stage, placement method, rate of Cu, seedrow-placed Cu, soil incorporation

The effect of foliar copper application on grain yield and quality of wheat

2004 ◽  
Vol 84 (1) ◽  
pp. 47-56 ◽  
Author(s):  
R. E. Karamanos ◽  
Q. Pomarenski ◽  
T. B. Goh ◽  
N. A Flore
Keyword(s):  
Grain Yield ◽  
Growth Stage ◽  
Foliar Application ◽  
Growing Season ◽  
Quality Parameters ◽  
Growth Stages ◽  
Appreciable Effect ◽  
Cu Deficiency ◽  
Seed Placement ◽  
Grain Yield And Quality

Available Cu concentrations in prairie soils (DTPA-extractable Cu) are extremely variable, thus resulting in areas within fields that are Cu deficient. These areas are difficult to characterize by a soil test based on a composite field sample; thus, when they are identified in the growing season, foliar Cu application possibly represents the only method of correcting them. A project, carried out over a period of 8 yr that consisted of four experiments and a total of 22 trials, was designed to ascertain whether foliar Cu applications indeed provide a satisfactory means of correcting Cu deficiency. Experiments included comparison of foliar applications at Feekes growth stages 6 (first node of stem visible at base of shoot) and 6 plus 10 (sheath of last leaf completely grown out) to soil broadcast and incorporation of 4 to 5.5 kg Cu ha-1 as copper sulphate (CuSO4·5H2O) or seed placement of 2 kg Cu ha-1 in three forms (two oxysulphates and one sulphate); foliar application of a variety of products representing different chemistries (chelate, lignin sulphonate, humic acid, oxychloride and citric acid) on a number of wheat cultivars at Feekes growth stage 10 or one cultivar at Feekes growth stages 2 (beginning of tillering), 6, 10 and 2 plus 10. Foliar applications appear to provide a solution to Cu deficiency that is identified during the growing season. However, foliar applications were not always as effective as broadcast and incorporation of at least 4 kg Cu ha-1 in the form of CuSO4·5H2O, which still remains the preferred method to correct a Cu deficiency. Foliar application at Feekes growth stage 2 was ineffective, whereas a single foliar application at Feekes growth stage 10 was not as satisfactory as a single one at Feekes growth stage 6. Thus, the latter stage appears to be preferable; however, maximum grain yield in some cases was obtained by the combination of two foliar Cu applications, one each at Feekes growth stages 6 and 10. Responses of wheat to foliar Cu application were obtained on soils that contained DTPA-extractable Cu concentration of less than 0.4 mg kg-1. Foliar Cu applications did not have an appreciable effect on grain quality parameters, such as hectolitre weight, moisture or protein content. Key words: DTPA-extractable, Feekes growth stage, deficient, marginal, plant tissue

scholarly journals Improved protein contact prediction using dimensional hybrid residual networks and singularity enhanced loss function

2021 ◽  
Author(s):  
Yunda Si ◽  
Chengfei Yan
Keyword(s):  
Prediction Model ◽  
Loss Function ◽  
Prediction Models ◽  
Model Performance ◽  
Great Success ◽  
Contact Prediction ◽  
Reference Models ◽  
Residual Learning ◽  
Model Training ◽  
Residual Block

Deep residual learning has shown great success in protein contact prediction. In this study, a new deep residual learning-based protein contact prediction model was developed. Comparing with previous models, a new type of residual block hybridizing 1D and 2D convolutions was designed to increase the effective receptive field of the residual network, and a new loss function emphasizing the easily misclassified residue pairs was proposed to enhance the model training. The developed protein contact prediction model referred to as DRN-1D2D was first evaluated on 105 CASP 11 targets, 76 CAMEO hard targets and 398 membrane proteins together with two in house-developed reference models based on either the standard 2D residual block or the traditional BCE loss function, from which we confirmed that that the dimensional hybrid residual block and the singularity enhanced loss function can both be employed to improve the model performance for protein contact prediction. DRN-1D2D was further evaluated on 39 CASP 13 and CASP 14 free modeling targets together with the two reference models and four state-of-the-art protein contact prediction models including DeepCov, DeepCon, RaptorX-Contact and TripleRes. The result shows that DRN-1D2D consistently achieved the best performance among all these models.

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