Sugar Beet Yield and Quality Prediction at Multiple Harvest Dates Using Active-Optical Sensors

被引:22
|
作者
Bu, Honggang [1 ]
Sharma, Lakesh K. [2 ]
Denton, Anne [3 ]
Franzen, David W. [1 ]
机构
[1] N Dakota State Univ, Dept Soil Sci, Dep 7180,POB 6050, Fargo, ND 58108 USA
[2] Univ Maine, 57 Houlton Rd, Pesque Isle, ME 04769 USA
[3] N Dakota State Univ, Dept Comp Sci, Dep 2740,POB 6050, Fargo, ND 58108 USA
基金
美国国家科学基金会;
关键词
IN-SEASON PREDICTION; REMOTE-SENSING DATA; LEAF-AREA INDEX; OPTIMIZATION ALGORITHM; VEGETATION INDEXES; NITROGEN UPTAKE; RED EDGE; GROWTH; REFLECTANCE; CORN;
D O I
10.2134/agronj2015.0268
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Yield prediction in sugar beet (Beta vulgaris L.) is important as a basis for in-season N application. Active optical sensors have been researched in sugar beet for yield estimation. A common field method for using active-optical sensors is to establish an N non-limiting area, and compare the yield predicted from sensor readings with readings from the rest of the field. Yield difference is the basis for calculation of N rate. Sugar beet gains root mass and sugar content with time. The objectives of these experiments were to utilize two active-optical sensors at two timings with canopy height measurements and relate readings to root yield and recoverable sugar yield at consecutive harvest dates. A 2-yr study in the Red River Valley of North Dakota and Minnesota was conducted on four sites to compare two active-optical sensors, GreenSeeker and Holland Crop Circle, red normalized differential vegetative index (NDVI), red edge NDVI, with and without canopy height for use in sugar beet yield prediction. The red NDVI and red edge NDVI, used at V 6-8 and V 12-14 were similar in their relationship to sugar beet yield over several harvest dates. The r(2) of sensor measurement and yield relationships at V 6-8 improved when canopy height was considered but not at V 12-14. Active-optical sensors when canopy height is considered could be used to predict sugar beet root yield and recoverable sugar yield over a range of harvest dates, which would be useful in developing algorithms for in-season N fertilization.
引用
收藏
页码:273 / 284
页数:12
相关论文
共 44 条
  • [1] INFLUENCE OF SOWING AND HARVEST DATES ON SUGAR BEET YIELD
    Pavlu, Klara
    Chochola, Jaromir
    LISTY CUKROVARNICKE A REPARSKE, 2016, 132 (7-8): : 216 - 223
  • [2] EFFECTS OF PLANTING AND HARVEST DATES ON QUANTITY AND QUALITY OF SUGAR BEET SEED IN IRAN
    Fakhari, Rasoul
    Tobeh, Ahmad
    Khanzade, Hassan
    Mammadova, Ruhangiz
    Benab, Ghader Alizadeh
    LISTY CUKROVARNICKE A REPARSKE, 2015, 131 (5-6): : 181 - 187
  • [3] Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, USA
    Sharma, Lakesh K.
    Bu, Honggang
    Denton, Anne
    Franzen, David W.
    SENSORS, 2015, 15 (11) : 27832 - 27853
  • [4] An active-optical reflectance sensor in-field testing for the prediction of winter wheat harvest metrics
    Kostic, Marko Milan
    Ljubicic, Natasa
    Acin, Vladimir
    Mirosavljevic, Milan
    Budjen, Masa
    Rajkovic, Milos
    Dedovic, Nebojsa
    JOURNAL OF AGRICULTURAL ENGINEERING, 2024, 55 (01)
  • [5] Yield and quality of sugar beet as a function of region, plant density and harvest time
    Tirczka, I
    Kondora, C
    NOVENYTERMELES, 1999, 48 (03): : 289 - 299
  • [6] Sunflower Type Influences Yield Prediction using Active Optical Sensors
    Franzen, D. W.
    Schultz, E. C.
    DeSutter, T. M.
    Sharma, L. K.
    Ashley, R.
    Bu, H.
    AGRONOMY JOURNAL, 2019, 111 (02) : 881 - 888
  • [7] Yield prediction of sugar beet using agricultural spatial information
    1600, Japan Society for Precision Engineering, Kudan Seiwa Bldg, 1-5-9 Kudan-Kita, Chiyoda-ku, Tokyo, 102-0073, Japan (79):
  • [8] THE EFFECT OF SOME, PHYSIOLOGICALLY ACTIVE SUBSTANCES ON THE YIELD AND QUALITY OF SUGAR-BEET
    BAJCI, P
    SUTORIS, V
    SEKERKA, V
    ROSTLINNA VYROBA, 1985, 31 (08): : 817 - 830
  • [9] INFLUENCE OF PENETRATION RESISTANCE AND OF SOIL COMPACTION DEGREE ON YIELD, HARVEST QUALITY AND TECHNOLOGIC QUALITY OF SUGAR-BEET
    ZAHRADNICEK, J
    HRDINA, S
    DUFFEK, M
    PROKUPEK, P
    SVACHULA, V
    HEFNER, S
    SMRCKA, S
    SUBIK, M
    LISTY CUKROVARNICKE A REPARSKE, 1988, 104 (02): : 31 - 37
  • [10] Prediction of sugar beet yield and quality parameters using Stacked-LSTM model with pre-harvest UAV time series data and meteorological factors
    Wang, Qing
    Shao, Ke
    Cai, Zhibo
    Che, Yingpu
    Chen, Haochong
    Xiao, Shunfu
    Wang, Ruili
    Liu, Yaling
    Li, Baoguo
    Ma, Yuntao
    ARTIFICIAL INTELLIGENCE IN AGRICULTURE, 2025, 15 (02): : 252 - 265