In‐Season Prediction of Corn Yield Using Plant Height under Major Production Systems

Abstract

The relationship between corn (Zea mays L.) yield and plant height has been poorly documented in major corn production systems. This study was conducted to assess the relationship of corn yield with plant height under four major corn production systems at Milan, TN from 2008 through 2010. Six N treatments at rates of 0, 62, 123, 185, 247, and 308 kg N ha−1 with four replications were evaluated in a randomized complete block design in the following corn production systems: nonirrigated corn after corn, nonirrigated corn after soybean [Glycine max (L.) Merr.], nonirrigated corn after cotton [Gossypium hirsutum (L.)], and irrigated corn after soybean. The regression of corn yield with plant height was significant and positive at 6‐leaf growth stage (V6), 10‐leaf growth stage (V10), and 12‐leaf growth stage (V12), and mostly became stronger as plant growth progressed from V6 to V10 and to V12 under an exponential model in the four corn production systems for all 3 yr. In general, corn yield was strongly related with plant height measurements made at V10 and V12. Factors affecting the responses of plant height measured at V6, V10, and V12 or/and yield to the N treatments may have contributed to the variations of determination coeffient (R 2) values across years. In conclusion, corn yield may be predicted with plant height measurements collected during V10 to V12. This prediction provides a physiological basis for the utilization of high resolution plant height measurements to guide variable‐rate N applications within the field on corn at around V10 and to more accurately estimate yield for earlier grain marketing purposes.

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

“…In precision agriculture, remote sensing has been used to monitor crop growth and health by computing a range of spectral vegetation indices [2][3][4][5][6][7][8][9]. However, recently more attention has been given to the use of crop height modelling for yield estimation [10][11][12]. In this context, several studies have shown that crop productivity, in certain crop types (e.g., maize, potato, barley, wheat, corn, rice, sunflower and poppy [11,[13][14][15][16][17][18][19][20][21][22], can be assessed from biophysical characteristics, such as crop height and biomass.…”

“…Crop height is an important factor for yield estimation and crop management [11,[19][20][21][22][23]. Crop height is a significant indicator of yield estimation in maize [10], whereas, in barley, crop height has been utilised to estimate biomass [11]. In the case of poppy crops, only a single study has looked at the use of remote sensing methods, in which crop height and Leaf Area Index (LAI) were found to be two suitable indicators for estimating opium yield [21].…”

Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

“…Recent studies found a high correlation of corn plant height and corn grain yield at early-to mid-season growth stages [36][37][38]. Yin et al [37] also showed that linear regression models for the prediction of corn grain yield may be the preferred ones, because of their simplicity.…”

Describing the Height Growth of Corn Using Logistic and Gompertz Model

“…There are many researches in corn growth that have been done : Williams II (2008) made an evaluation about the effect of planting date on height growth using analysis of variance, and to determine sweet corn height growth using logistic model. Estimating maize leaf area index and developing leaf area growth has been done by researchers (Karadavut et al, 2010); Yin et al, (2011) about improving a regression models between corn yield and corn plant height ; the result showed that there was a relationship between corn yield and plant height especially in multiple cropping system. Another research done was about a competition between pigweed redroot and the economic threshold in corn, where the result of the experiment showed that an increase of the corn density would increase the corn height; before 70 days after the plantation, the pigweed redroot was higher than that of corn plant but after that period the height was inversed and the height of corn tended to be sigmoid compared to the weed (Vazin, 2012).…”

“…At the case, the result showed that the best fitted growth model such as : Richards, Logistic and Gompertz (Karadavut, et al, 2010). And it is also said that plant height is a key indicator of plant growth and is linked to N nutrition during vegetative of corn development (Yin et al, 2011) In relation with the growth model, statistic model would be applied to the data on corn plant height. The ability to estimate the mathematical model of plant height individually would benefit growers as they can plan the time when they must apply such an important treatment to have healthier plant in order to have good quality of corn yield and, thus, maximize their profits.…”