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

Wang, Xinbing; Miao, Yuxin; Dong, Rui; Chen, Zhichao; Guan, Ying; Yue, Xuezhi; Fang, Zheng; Mulla, D. J.

doi:10.3390/su11030706

Cited by 28 publications

(18 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Working with rain-fed maize in North-east China, Wang et al [135] found that rather than GreenSeeker measured NDVI alone, using plant height information together with NDVI improved the prediction of potential yield (with no additional fertilizer N) as well as RI. The improved NFOA (INFOA) based on NDVI combined with relative plant height guided fertilizer N doses for maize better than the NFOA in both black and aeolian sandy soils.…”

Section: Canopy Reflectance Sensor Based Fertilizer Nitrogen Managemementioning

confidence: 99%

Using Hand-Held Chlorophyll Meters and Canopy Reflectance Sensors for Fertilizer Nitrogen Management in Cereals in Small Farms in Developing Countries

Bijay‐Singh

Ali

2020

Sensors

View full text Add to dashboard Cite

To produce enough food, smallholder farmers in developing countries apply fertilizer nitrogen (N) to cereals, sometimes even more than the local recommendations. During the last two decades, hand-held chlorophyll meters and canopy reflectance sensors, which can detect the N needs of the crop based on transmission and reflectance properties of leaves through proximal sensing, have been studied as tools for optimizing crop N status in cereals in developing countries. This review aims to describe the outcome of these studies. Chlorophyll meters are used to manage fertilizer N to maintain a threshold leaf chlorophyll content throughout the cropping season. Despite greater reliability of the sufficiency index approach, the fixed threshold chlorophyll content approach has been investigated more for using chlorophyll meters in rice and wheat. GreenSeeker and Crop Circle crop reflectance sensors take into account both N status and biomass of the crop to estimate additional fertilizer N requirement but only a few studies have been carried out in developing countries to develop N management strategies in rice, wheat and maize. Both chlorophyll meters and canopy reflectance sensors can increase fertilizer N use efficiency by reduction of N rates. Dedicated economic analysis of the proximal sensing strategies for managing fertilizer N in cereals in developing countries is not adequately available.

show abstract

Section: Canopy Reflectance Sensor Based Fertilizer Nitrogen Managemementioning

confidence: 99%

Using Hand-Held Chlorophyll Meters and Canopy Reflectance Sensors for Fertilizer Nitrogen Management in Cereals in Small Farms in Developing Countries

Bijay‐Singh

Ali

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…However, over-application of N is common in Chinese agriculture, resulting in many environmental problems [2,3]. Precision N management strategies aiming to apply the optimal amount of N fertilizer at the right time and place can help increase crop yield and N use efficiency, as well as reduce N surplus and environmental impacts [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

et al. 2020

Self Cite

View full text Add to dashboard Cite

Nitrogen (N) is one of the most essential nutrients that can significantly affect crop grain yield and quality. The implementation of proximal and remote sensing technologies in precision agriculture has provided new opportunities for non-destructive and real-time diagnosis of crop N status and precision N management. Notably, leaf fluorescence sensors have shown high potential in the accurate estimation of plant N status. However, most studies using leaf fluorescence sensors have mainly focused on the estimation of leaf N concentration (LNC) rather than plant N concentration (PNC). The objectives of this study were to (1) determine the relationship of maize (Zea mays L.) LNC and PNC, (2) evaluate the main factors influencing the variations of leaf fluorescence sensor parameters, and (3) establish a general model to estimate PNC directly across growth stages. A leaf fluorescence sensor, Dualex 4, was used to test maize leaves with three different positions across four growth stages in two fields with different soil types, planting densities, and N application rates in Northeast China in 2016 and 2017. The results indicated that the total leaf N concentration (TLNC) and PNC had a strong correlation (R2 = 0.91 to 0.98) with the single leaf N concentration (SLNC). The TLNC and PNC were affected by maize growth stage and N application rate but not the soil type. When used in combination with the days after sowing (DAS) parameter, modified Dualex 4 indices showed strong relationships with TLNC and PNC across growth stages. Both modified chlorophyll concentration (mChl) and modified N balance index (mNBI) were reliable predictors of PNC. Good results could be achieved by using information obtained only from the newly fully expanded leaves before the tasseling stage (VT) and the leaves above panicle at the VT stage to estimate PNC. It is concluded that when used together with DAS, the leaf fluorescence sensor (Dualex 4) can be used to reliably estimate maize PNC across growth stages.

show abstract

“…Finally, the N topdressing requirement is estimated by dividing the yield gap (YP N − YP 0 ) by the average AE of topdressing N (AE topdressing ) [10]. The AE topdressing should be higher than the one for the whole season, and will be predicted during the growing season using the predicted RI Harvest [30].…”

Section: Development and Evaluation Of Rapidscan-based Precision Nitr...mentioning

confidence: 99%

“…As a result, the PNM strategy making two in-season N recommendations at stem elongation and heading stages only using NDVI had the worst performance among all the PNM strategies evaluated in the scenario analysis. One approach to overcome the NDVI saturation problem is to combine NDVI with relative plant height data [30]. Another approach is to replace NDVI with other VIs that can overcome the saturation effect [32].…”

Section: Selection Of Vegetation Indices For Precision N Management S...mentioning

confidence: 99%

Developing a Proximal Active Canopy Sensor-based Precision Nitrogen Management Strategy for High-Yielding Rice

Miao

Chen

et al. 2020

Remote Sensing

Self Cite

View full text Add to dashboard Cite

RapidSCAN is a portable active canopy sensor with red, red-edge, and near infrared spectral bands. The objective of this study is to develop and evaluate a RapidSCAN sensor-based precision nitrogen (N) management (PNM) strategy for high-yielding rice in Northeast China. Six rice N rate experiments were conducted from 2014 to 2016 at Jiansanjiang Experiment Station of China Agricultural University in Northeast China. The results indicated that the sensor performed well for estimating rice yield potential (YP0) and yield response to additional N application (RIHarvest) at the stem elongation stage using normalized difference vegetation index (NDVI) (R2 = 0.60–0.77 and relative error (REr) = 6.2–8.0%) and at the heading stage using normalized difference red edge (NDRE) (R2 = 0.70–0.82 and REr = 7.3–8.7%). A new RapidSCAN sensor-based PNM strategy was developed that would make N recommendations at both stem elongation and heading growth stages, in contrast to previously developed strategy making N recommendation only at the stem elongation stage. This new PNM strategy could save 24% N fertilizers, and increase N use efficiencies by 29–35% as compared to Farmer N Management, without significantly affecting the rice grain yield and economic returns. Compared with regional optimum N management, the new PNM strategy increased 4% grain yield, 3–10% N use efficiencies and 148 $ ha−1 economic returns across years and varieties. It is concluded that the new RapidSCAN sensor-based PNM strategy with two in-season N recommendations using NDVI and NDRE is suitable for guiding in-season N management in high-yield rice management systems. Future studies are needed to evaluate this RapidSCAN sensor-based PNM strategy under diverse on-farm conditions, as well as to integrate it into high-yield rice management systems for food security and sustainable development.

show abstract

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

Cited by 28 publications

References 59 publications

Using Hand-Held Chlorophyll Meters and Canopy Reflectance Sensors for Fertilizer Nitrogen Management in Cereals in Small Farms in Developing Countries

Using Hand-Held Chlorophyll Meters and Canopy Reflectance Sensors for Fertilizer Nitrogen Management in Cereals in Small Farms in Developing Countries

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

Developing a Proximal Active Canopy Sensor-based Precision Nitrogen Management Strategy for High-Yielding Rice

Contact Info

Product

Resources

About