scholarly journals Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China

2019 ◽  
Vol 11 (3) ◽  
pp. 706 ◽  
Author(s):  
Xinbing Wang ◽  
Yuxin Miao ◽  
Rui Dong ◽  
Zhichao Chen ◽  
Yanjie Guan ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Experiments ◽  
Management Strategies ◽  
N Fertilizer ◽  
Yield Potential ◽  
Maize Production ◽  
N Management

Precision nitrogen (N) management (PNM) strategies are urgently needed for the sustainability of rain-fed maize (Zea mays L.) production in Northeast China. The objective of this study was to develop an active canopy sensor (ACS)-based PNM strategy for rain-fed maize through improving in-season prediction of yield potential (YP0), response index to side-dress N based on harvested yield (RIHarvest), and side-dress N agronomic efficiency (AENS). Field experiments involving six N rate treatments and three planting densities were conducted in three growing seasons (2015–2017) in two different soil types. A hand-held GreenSeeker sensor was used at V8-9 growth stage to collect normalized difference vegetation index (NDVI) and ratio vegetation index (RVI). The results indicated that NDVI or RVI combined with relative plant height (NDVI*RH or RVI*RH) were more strongly related to YP0 (R2 = 0.44–0.78) than only using NDVI or RVI (R2 = 0.26–0.68). The improved N fertilizer optimization algorithm (INFOA) using in-season predicted AENS optimized N rates better than the N fertilizer optimization algorithm (NFOA) using average constant AENS. The INFOA-based PNM strategies could increase marginal returns by 212 $ ha−1 and 70 $ ha−1, reduce N surplus by 65% and 62%, and improve N use efficiency (NUE) by 4%–40% and 11%–65% compared with farmer’s typical N management in the black and aeolian sandy soils, respectively. It is concluded that the ACS-based PNM strategies have the potential to significantly improve profitability and sustainability of maize production in Northeast China. More studies are needed to further improve N management strategies using more advanced sensing technologies and incorporating weather and soil information.

Development of an algorithm for optimizing nitrogen fertilization in wheat using GreenSeeker proximal optical sensor

2020 ◽  
Vol 56 (5) ◽  
pp. 688-698
Author(s):  
Ali M. Ali
Keyword(s):  
Vegetation Index ◽  
Field Experiments ◽  
N Uptake ◽  
Yield Potential ◽  
N Recovery ◽  
Spatial And Temporal Variability ◽  
Fertilizer N ◽  
Total N ◽  
General Recommendation ◽  
N Management

AbstractProximal plant sensing with active canopy sensors offers a leap in the non-destructive assessment of crop agronomic information. For managing fertilizer nitrogen (N), sensor readings must be translated using functional models or algorithms to fertilizer amounts. Six field experiments were conducted in three wheat seasons in the West Nile Delta in Egypt to develop and validate an algorithm based on GreenSeeker canopy reflectance sensor for field-specific fertilizer N management in wheat, which takes into account both spatial and temporal variability of N during the crop growth season. The proposed algorithm is based on the prediction of total N uptake and response index of N uptake determined from normalized difference vegetation index measured by the sensor from plots differing in yield potential as established by applying a range of fertilizer N levels in the four experiments conducted in the first two wheat seasons. The treatments in the two experiments conducted in the third wheat season were designed to define appropriate fertilizer N management prior to applying a sensor-based dose at Feekes 6 stage (jointing stage). The application of 40 and 60 kg N ha−1 at 10 and 30 days after sowing of wheat and a sensor-guided dose of N estimated by using the algorithm developed in this study resulted in yields similar to those obtained by following the general recommendation, but with an average of 66 kg N ha−1 less fertilizer N. These results were also reflected in a substantial increase in N recovery (21.9%) and agronomic (7.7 kg grain kg−1 N) efficiencies compared with the general recommendation, thereby proving the usefulness of the sensor-based algorithm in optimizing fertilizer N management in wheat.

scholarly journals Response of Desert Lettuce to Controlled-release N Fertilizer

HortScience ◽  
1995 ◽  
Vol 30 (4) ◽  
pp. 769F-769
Author(s):  
C.A. Sanchez
Keyword(s):  
Controlled Release ◽  
Management Practices ◽  
Field Experiments ◽  
Management Practice ◽  
Management Strategies ◽  
N Fertilization ◽  
N Fertilizer ◽  
Marketable Yield ◽  
Potential Threat ◽  
N Management

Lettuce produced in the desert typically shows large yield responses to N fertilization. However, concern about the potential threat of nitrate-N to ground-water has prompted additional studies aimed at developing improved N management practices. Field experiments were conducted between 1992 and 1995 to evaluate the response of crisphead lettuce to controlled-release N fertilizer (CRN). The use of CRN was compared to a soluble N fertilizer applied preplant (PP), and a soluble N fertilizer applied in split-sidedress applications (SD). Rates of N fertilizer application ranged from 0 to 300 kg·ha–1. Lettuce generally showed significant responses to N rate and N management practice. However, response to management practice varied by site-season. When conditions for N loss were high, SD and CRN management strategies were superior. However, in other site-seasons, SD management sometimes resulted in inferior head quality and marketable yield when compared to other management strategies. Data averaged over six site-seasons shoed improved yield and quality to CRN management strategies compared to PP and SD strategies.

scholarly journals Nitrogen management in wheat based on the normalized difference vegetation index (NDVI)

2018 ◽  
Vol 48 (9) ◽  
Author(s):  
André Luis Vian ◽  
Christian Bredemeier ◽  
Marcos Alexandre Turra ◽  
Cecília Paz da Silva Giordano ◽  
Elizandro Fochesatto ◽  
...  
Keyword(s):  
Technical Efficiency ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Experiments ◽  
Shoot Biomass ◽  
Sensor Field ◽  
N Dose ◽  
Plant Emergence ◽  
The Moment ◽  
The Relationship

ABSTRACT: Biomass production and nitrogen (N) accumulated in wheat shoots may be used for quantifying optimal topdressing nitrogen doses. The objective of this study was to develop and validate models for estimating the amount of biomass and nitrogen accumulated in shoots and the N topdressing dose of maximum technical efficiency in wheat using the normalized difference vegetation index (NDVI) measured by an active optical canopy sensor. Field experiments were carried out in two years and treatments consisted of N doses applied at plant emergence and as topdressing. NDVI, shoot biomass and N accumulated in shoots at the growth stage of six fully expanded leaves and grain yield were evaluated, being determined the topdressing N dose of maximum technical efficiency (DMTE). The NDVI was positively correlated to shoot biomass and N content in shoots and models for the relationship between these variables were developed and validated. The DMTE was negatively correlated with the NDVI value evaluated at the moment of N topdressing application. Thus, NDVI evaluation by an active optical canopy sensor can be used for nitrogen fertilization in variable rate, allowing the adjustment of applied N doses in different areas within a field.

scholarly journals Assessing Snow Phenology and Its Environmental Driving Factors in Northeast China

2022 ◽  
Vol 14 (2) ◽  
pp. 262
Author(s):  
Hui Guo ◽  
Xiaoyan Wang ◽  
Zecheng Guo ◽  
Siyong Chen
Keyword(s):  
Snow Cover ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Water Cycle ◽  
Water Source ◽  
Driving Factors ◽  
Change Rate ◽  
Mean Temperature ◽  
Forested Areas

Snow cover is an important water source and even an Essential Climate Variable (ECV) as defined by the World Meteorological Organization (WMO). Assessing snow phenology and its driving factors in Northeast China will help with comprehensively understanding the role of snow cover in regional water cycle and climate change. This study presents spatiotemporal variations in snow phenology and the relative importance of potential drivers, including climate, geography, and the normalized difference vegetation index (NDVI), based on the MODIS snow products across Northeast China from 2001 to 2018. The results indicated that the snow cover days (SCD), snow cover onset dates (SCOD) and snow cover end dates (SCED) all showed obvious latitudinal distribution characteristics. As the latitude gradually increases, SCD becomes longer, SCOD advances and SCED delays. Overall, there is a growing tendency in SCD and a delayed trend in SCED across time. The variations in snow phenology were driven by mean temperature, followed by latitude, while precipitation, aspect and slope all had little effect on the SCD, SCOD and SCED. With decreasing temperature, the SCD and SCED showed upward trends. The mean temperature has negatively correlation with SCD and SCED and positively correlation with SCOD. With increasing latitude, the change rate of the SCD, SCOD and SCED in the whole Northeast China were 10.20 d/degree, −3.82 d/degree and 5.41 d/degree, respectively, and the change rate of snow phenology in forested areas was lower than that in nonforested areas. At the same latitude, the snow phenology for different underlying surfaces varied greatly. The correlations between the snow phenology and NDVI were mainly positive, but weak correlations accounted for a large proportion.

In-Season Prediction of Corn Grain Yield Potential Using Normalized Difference Vegetation Index

2006 ◽  
Vol 98 (6) ◽  
pp. 1488-1494 ◽  
Author(s):  
R. K. Teal ◽  
B. Tubana ◽  
K. Girma ◽  
K. W. Freeman ◽  
D. B. Arnall ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Yield Potential ◽  
Corn Grain ◽  
Corn Grain Yield

scholarly journals Using QUEFTS model for estimating nutrient requirements of maize in the Northeast China

2017 ◽  
Vol 63 (No. 11) ◽  
pp. 498-504 ◽  
Author(s):  
Jiang Wenting ◽  
Liu Xiaohu ◽  
Qi Wen ◽  
Xu Xiaonan ◽  
Zhu Yucui
Keyword(s):  
Northeast China ◽  
Field Experiments ◽  
Nutrient Use Efficiency ◽  
Maize Yield ◽  
Yield Potential ◽  
Nutrient Requirements ◽  
Plant Nitrogen ◽  
Nutrient Use ◽  
Supply Surplus ◽  
Use Efficiency

Accurate estimating of the balanced nutrition for maize is necessary for optimizing fertilizer management to prevent nutrient supply surplus or deficiency. Data from 300 field experiments in the Northeast China conducted between 2006 and 2011 were gathered to study the characteristics of maize yield, and using the QUEFTS model to estimate the balanced nutrition at different yield potential. The average grain yield was 10 427 kg/ha, and average internal efficiencies were 54.3, 251.5 and 78.2 kg grain per kg plant nitrogen (N), phosphorus (P) and potassium (K), respectively. With the harvest index values < 0.40 as outliers were excluded, the model simulated a linear-parabolic-plateau curve for the balanced N, P and K uptake when the initial yield target increased to the yield potential levels of 10 000 to 14 000 kg/ha. When the yield target reached approximately 60–70% of the yield potential, 16.7 kg N, 3.8 kg P, and 11.4 kg K were required to produce 1000 kg grain. The corresponding internal efficiencies were 60.0, 265.7 and 88.0 kg grain per kg plant N, P and K, respectively. These results contributed to improving nutrient use efficiency, and to demonstrate that the QUEFTS model could be a promising approach for estimating the balanced nutrition.

scholarly journals Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

2017 ◽  
Vol 21 (8) ◽  
pp. 513-518 ◽  
Author(s):  
Alberto C. de C. Bernardi ◽  
Célia R. Grego ◽  
Ricardo G. Andrade ◽  
Ladislau M. Rabello ◽  
Ricardo Y. Inamasu
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Exchange Capacity ◽  
Soil Parameters ◽  
Forage Production ◽  
Soil P ◽  
Livestock System

ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

scholarly journals Nitrogen Fertilization of a High Yielding White-Kernel Corn in Oxisols and Ultisols in Puerto Rico

1969 ◽  
Vol 60 ◽  
pp. 336-343
Author(s):  
H. Talleyrand ◽  
R. H. Fox ◽  
M. A. Lugo-López
Keyword(s):  
Puerto Rico ◽  
Nitrogen Fertilization ◽  
Field Experiments ◽  
Sandy Loam ◽  
N Uptake ◽  
N Fertilizer ◽  
Yield Potential ◽  
Severe Drought ◽  
Optimum Level ◽  
Grain Yields

Field experiments with a high-yielding white-kernel hybrid corn. Funk's G-795W, were conducted on four typical soils of Puerto Rico: two Oxisols (Bayamón sandy loam at Manatí and Catalina clay at Barranquitas) and two Ultisols (Humatas clay at Corozal and Torres clay at Cidra). The main objectives of this study were to determine the yield potential and the optimum level of N fertilizer for this hybrid in these soils. Auxiliary objectives were to determine the N supplying power of these soils and the apparent recovery of fertilizer N by the crop. High corn yields (8.4 tons/ha) were obtained on the Humatas clay with 60 to 120 kg/ha of N fertilizer. Only 5.4 tons/ha of corn were obtained on Bayamón sandy loam at the same rate of fertilization. Apparent N recoveries were 60 to 72% at these rates. Grain/stover ratios averaged 1.20 on Humatas and only 0.72 on Bayamón. The low grain/stover ratio and the lower grain yields at this site probably could be attributed to late planting and the damage done to the plants by Helminthosporium maydis. There were no yield or N uptake responses to applied N fertilizer on the nonirrigated Catalina and Torres soils. A severe drought reduced stover yields to less than half of those of the irrigated treatments. Maximum nonirrigated grain yields on these soils (4.8 tons/ha) were well below the 8.3 tons/ha obtained on Humatas. The N supplying power of these soils was enough to provide 70 to 90 kg/ha of plant N.

scholarly journals CANOPY REFLECTANCE MEASUREMENTS USED TO ESTIMATE LATE BLIGHT (PHYTOPHTHORA INFESTANS) INFLUENCE ON POTATO YIELD CANOPY REFLECTANCE MEASUREMENTS USED TO ESTIMATE LATE BLIGHT (PHYTOPHTHORA INFESTANS) INFLUENCE ON POTATO YIELD

2020 ◽  
Vol 13 ◽  
pp. 21-27
Author(s):  
Manuela Hermeziu
Keyword(s):  
Late Blight ◽  
Phytophthora Infestans ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Experiments ◽  
Block Design ◽  
Potato Yield ◽  
Planting Density ◽  
Canopy Reflectance ◽  
Reflectance Measurements

"The present study was conducted to investigate potato late blight (Phytophtora infestans) influence on leaf chlorophyll level using datasets extracted from multispectral data captured at the canopy level. Field experiments were carried out to the National Institute of Research and Development for Potato and Sugar Beet Brasov, Romania in 2014-2016 period. It was used a complete randomized block design with four replicates, two planting distances between plants on row (25 and 30cm) and different fungicides, control technologies. Normalized Difference Vegetation Index (NDVI) was introduced to achieve a spectral vegetation index that can separate the vegetation from the uncovered ground. It is defined as the ratio between the infrared bands-red differences and sum them. Due to the different growth conditions, the effects of resulting variants from combinations of factors -varieties-planting density-late blight control technology-on the tubers yield have manifested with different intensity. In two of three years, the average NDVI value of plants grown at a density of 53.3 thousands hill/ha was significantly lower than the values determined at a density of 44.4 thousands hill/ha (NDVI 0.817 compared to 0.859 in 2014 and 0.905 compared to 0.895 in 2015). The correlation between the average values of NDVI yields and tubers were positive."

scholarly journals Consequences of climate-induced vegetation changes exceed those of human disturbance for wild impala in the Serengeti ecosystem

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
L Hunninck ◽  
R May ◽  
C R Jackson ◽  
R Palme ◽  
E Røskaft ◽  
...  
Keyword(s):  
Human Disturbance ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Forage Quality ◽  
Serengeti Ecosystem ◽  
Human Land Use ◽  
Faecal Samples ◽  
Dry Seasons ◽  
Positive Effect

Abstract In East Africa, climate change is predicted to reduce vegetation quality, and pervasive human disturbance has already resulted in significant declines in biodiversity. We studied the combined effects of reduced forage quality and human disturbance on faecal glucocorticoid metabolite (FGM) concentrations. We predicted that decreasing nutritional quality and increasing human disturbance would have an additive positive effect on FGM levels in wild impala (Aepyceros melampus). Employing a space-for-time approach, we used normalized difference vegetation index (NDVI) as a measure of forage quality, combined with spatially explicit proxies of human disturbance across areas of different protection management strategies in the Serengeti ecosystem. We collected 639 faecal samples, spread over 4 years, including both wet and dry seasons. Impala FGM levels increased significantly with declining NDVI and, to a lesser extent, with increasing proxies for human disturbance. However, we found no interaction between the two, such that impala had elevated FGM levels with low NDVI and low FGM levels with high NDVI regardless of human disturbance levels. This implies that impala will have high FGM levels if forage quality is poor, even with significant protection and reduced human disturbance. Understanding how animals respond to and cope with changes in forage quality and human land use across different protected areas is important for conservationists and managers to better protect species at risk and predict population viability.

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