Abstract
Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-limiting standard area indicate a need for supplemental N. Active-optical sensor algorithms for predicting corn (Zea mays, L.) yield to direct in-season nitrogen (N) fertilization in corn utilize red NDVI (normalized differential vegetative index). Use of red edge NDVI might improve corn yield prediction at later growth stages when corn leaves cover the inter-row space resulting in “saturation” of red NDVI readings. The purpose of this study was to determine whether the use of red edge NDVI in two active-optical sensors (GreenSeeker™ and Holland Scientific Crop Circle™) improved corn yield prediction. Nitrogen rate experiments were established at 15 sites in North Dakota (ND). Sensor readings were conducted at V6 and V12 corn. Red NDVI and red edge NDVI were similar in the relationship of readings with yield at V6. At V12, the red edge NDVI was superior to the red NDVI in most comparisons, indicating that it would be most useful in developing late-season N application algorithms.
Highlights
The objective of this study was to determine the performance of red edge Normalized Differential Vegetative Index (NDVI) in yield prediction in corn compared to the yield prediction of red NDVI at early (V6) and later (V12) growth stages
In high clay sites at V6 using the CircleTM A470 sensor (CC), the red edge NDVI-based in-season estimation of yield (INSEY) was significantly related to yield whereas both
The INSEY derived from wavelengths of both active-sensors at both growth stages were significantly related to yield (Table 4)
Summary
Numerous methods have been used to manage N application to crops, including zone soil sampling [1], soil and plant analysis [2], use of nitrogen credit from the influence of previous crops [3], tissue analysis [4], fertilizer application timing and placement [5,6,7,8], leaf area index [9,10,11,12,13], and the use of spectral sensors [2,14,15,16,17,18,19,20,21]. The use of active-optical sensors to direct in-season N application is being used in wheat (Triticum aestivum, L.) and corn (Zea mays, L.) growing areas of the USA. The algorithms developed to direct in-season N application use one of two methods. One method is to establish an N non-limiting area within the field at the time of preplant N application [20] or an N-rate “ramp” consisting of a continuous series of increasing N rates with the highest N rate designed to be non-limiting to the crop [23]. Once an NDVI measurement is performed on the N non-limiting standard, by either method, the result is that the greatest yield possible for the variety within the soil where the N non-limiting area is located is predicted. The yield difference is used to calculate the N required to increase yield from its predicted value if no additional
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