Effect of Delayed Emergence on Corn Grain Yields

Lawles, Kyle D.; Raun, W. R.; Desta, Kefyalew Girma; Freeman, K. W.

doi:10.1080/01904167.2012.639926

Cited by 14 publications

(8 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Increased growth and development of early-emerging plants increased competitive ability compared to later emerging plants; late emerging plants that did not receive SF were able to compete with early emerging plants more. This tends to agree with the results of (Edmeades and Daynard, 1979;Ford and Hicks, 1992;Lawles et al, 2012;Tollenaar and Wu, 1999) in that later emerging plants were less able to compete with plants that emerged earlier. However, SF enhanced the competitive ability of early-emerging plants.…”

Section: Discussionsupporting

confidence: 89%

“…showed that replanting due to variable emergence delays of up to 2 weeks were not likely to be economical; however, when 25% of the plants were delayed by 3 weeks or more, they suggested replanting may be justified. Similar to these results, other agronomists showed that plants that were planted 2, 5, and 8 days after others were able to compete with earlier planted plants; but plants that were planted 12 days after others were unable to compete with neighboring plants planted earlier (Lawles et al, 2012). Grain yield reductions of 0.225 to 1.379 Mg•ha -1 •day -1 occurred for each day delay in emergence (Lawles et al, 2012).…”

Section: Introductionsupporting

confidence: 72%

See 1 more Smart Citation

The effects of starter fertilizer on root and shoot growth of corn hybrids and seeding rates and plant-to-plant variability in growth and grain yield

Pierson

View full text Add to dashboard Cite

CHAPTER 1: GENERAL INTRODUCTION Starter fertilizer (SF) often increases early-season growth and reduces time to maturity for corn (Zea mays L.) (Bermudez and Mallarino, 2002; Bullock et al., 1993). Effects of starter fertilizer on corn grain yield have varied with some researchers finding that hybrids responded differently to starter fertilizer application (Gordon et al., 1997), while others have found that hybrids responded similarly (Buah et al., 1999). Agronomists that found differences in hybrids response to starter fertilizer also found that the root systems of hybrids that responded to SF were generally smaller than those that did not respond to SF (Gordon and Pierzynski, 2006; Rhoads and Wright, 1998). Many farmers in central Iowa abandoned SF applications due to the cost and weight of placement units, costs associated with handling the fertilizer, and lack of grain yield responses in their fields. Plant-to-plant variability in corn growth and grain yield is often associated with reduced grain yield (Muldoon and Daynard, 1981). Increased variability in growth is often associated with plant spacing standard deviation, however, grain yield responses to plant spacing uniformity are variable. While some researchers have found that reduced plant spacing standard deviation increases yield (Nielson, 2001), others have found that plant spacing is not important in grain yield (Liu et al., 2004b). Variability in emergence is important in final yield and agronomists have developed recommendations for replanting based on variation in emergence within a field (Liu et al., 2004a; Nafziger et al., 1991). Uniformity in seeding depth and soil factors such as moisture, temperature, residue cover, and crusting often affect uniformity in plant emergence (Alessi and Power, 1971; Nafziger et al., 1991).

show abstract

Section: Discussionsupporting

confidence: 89%

Section: Introductionsupporting

confidence: 72%

The effects of starter fertilizer on root and shoot growth of corn hybrids and seeding rates and plant-to-plant variability in growth and grain yield

Pierson

View full text Add to dashboard Cite

show abstract

“…High saline levels may inhibit the water uptake of seeds, making germination not possible, while the lower level of salinity induces a state of dormancy (IBRAHIM, 2016). Delayed and reduced seedling emergence causes non-uniform stand establishment, which results in reduced crop yields (LAWLES et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Seed priming improves the germination and growth rate of melon seedlings under saline stress

et al. 2019

View full text Add to dashboard Cite

The germination and growth of melon (Cucumis melo L.) plants can be severely affected by excess salts in the soil or irrigation water; however, negative effects of salt stress can be attenuated using appropriate methods of seed priming. Thus, effects of osmopriming as inducer of salt stress tolerance in melon seeds exposed to salinity levels were investigated in this study. Seeds were soaked for 22 h at 25 °C in the dark in distilled water (hydropriming) or 0.5% KNO3 solution (osmopriming), and after drying, were distributed in plastic boxes with blotter paper containing different NaCl solutions prepared with osmotic pressure of 0.0 MPa (control), -0.3 MPa (mild stress), and -0.6 MPa (severe stress). Unprimed dry seeds were taken as control. The plastic boxes were kept into a seed germinator, at 25 °C for 14 days. A completely randomized design in a 3 × 3 factorial schemes with four replicates of 25 seeds was used. Results showed that the seed priming with water and KNO3 may be successfully applied on melon seeds to alleviate the adverse effects of saline stress in initial stages of plant growth. However, under severe salt stress conditions, hydropriming should be used because it results in higher germination and initial growth rate of the seedlings when compared to the osmopriming. Use of unprimed seeds should not be adopted in cultivation areas affected by salinity because they result in low germination rate and reduced initial plant growth.

show abstract

“…Emergence is important because a vigorous and uniform crop stand is needed to compete for moisture, nutrients, and sunlight. Plants that emerge late will have a lower yield than the early emerging ones due to the increase in competition for sunlight and essential nutrients [21]. Determining biomass in different crop varieties is important because it is correlated with yield [32] and photosynthetic activity, and is an indicator of overall plant health [12].…”

Section: Introductionmentioning

confidence: 99%

DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning

Aich¹,

Josuttes²,

Ovsyannikov³

et al. 2018

2018 IEEE Winter Conference on Applications of Computer Vision (WACV)

View full text Add to dashboard Cite

In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots. We employ a state-of-the-art deconvolutional network for segmentation and convolutional architectures, with residual and Inception-like layers, to estimate traits via high dimensional nonlinear regression. Evaluation was performed on two different species of wheat, grown in field plots for an experimental plant breeding study. Our framework achieves satisfactory performance with mean and standard deviation of absolute difference of 1.05 and 1.40 counts for emergence and 1.45 and 2.05 for biomass estimation. Our results for counting wheat plants from field images are better than the accuracy reported for the similar, but arguably less difficult, task of counting leaves from indoor images of rosette plants. Our results for biomass estimation, even with a very small dataset, improve upon all previously proposed approaches in the literature.

show abstract

Effect of Delayed Emergence on Corn Grain Yields

Cited by 14 publications

References 28 publications

The effects of starter fertilizer on root and shoot growth of corn hybrids and seeding rates and plant-to-plant variability in growth and grain yield

The effects of starter fertilizer on root and shoot growth of corn hybrids and seeding rates and plant-to-plant variability in growth and grain yield

Seed priming improves the germination and growth rate of melon seedlings under saline stress

DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning

Contact Info

Product

Resources

About