Analysis of Soil and Crop Properties for Precision Agriculture for Winter Wheat

Vrindts, Els; Reyniers, M.; Darius, Paul; Baerdemaeker, Josse De; Gilot, M.; Sadaoui, Y.; Frankinet, Marc; Hanquet, Bernard; Destain, Marie‐France

doi:10.1016/s1537-5110(03)00040-0

Cited by 31 publications

(21 citation statements)

References 7 publications

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“…The estimated increase in yield by the VNR treatments was close to zero. The findings have been similar for several other tests of algorithms by for example, Berntsen et al 2006;Vrindts et al 2003, whereas Raun et al (2002 reported variable N application to be profitable.…”

Section: Resultssupporting

confidence: 63%

Uniformity of wheat yield and quality using sensor assisted application of nitrogen

Jørgensen

2007

Precision Agric

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Proximal sensing, or obtaining information from close range, is a potentially useful tool for measuring the crop nitrogen status in real-time The objective of this study was to use proximal sensing of crop canopy spectral reflectance to evaluate variable-rate application of nitrogen in terms of its effect on yield and grain quality of winter wheat (Triticum aestivum L.). The sensor used was the Hydro-Precise N-Sensor System. Yield and grain quality maps were used as a basis for full-scale field trials with winter wheat growing under four nitrogen application treatments: a large (274 kg ha -1 ), recommended (167 kg ha -1 ) and two sensor-assisted (167 kg ha -1 ) rates. The recommended rate of 167 kg N ha -1 was given in a three-split application that meets the present Danish regulations to reduce nitrogen leaching. These require arable farmers to decrease nitrogen fertilizer application to 90% of the economically optimal level. Each farm's baseline is calculated to take into account land quality, land allocated to each crop, and crop rotation. In the two sensor-assisted applications the Hydro-Precise N-Sensor System directs the last two of the three-split N application. Grain samples were collected directly from the grain flow of a combine harvester and analysed for protein, water and starch content. Grain data were related to and compared with combine yield meter registrations. Within the field, the variances of protein yield (698-1208 kg ha -1 ) and grain protein (9.5-13.4%) were large. The nitrogen application treatments affected the average protein content (10.5-12.3%) and grain yield (9.87-10.42 t ha -1 ) strongly. The grain starch content was largest in the uniform and sensor applied systems and smallest in the high nitrogen application treatment. Applying nitrogen according to the

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Section: Resultssupporting

confidence: 63%

Uniformity of wheat yield and quality using sensor assisted application of nitrogen

Jørgensen

2007

Precision Agric

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“…Pedersen, 2002). In addition, several other tests of algorithms showed no increase in yield (e.g., Ebertseder, Gutser, Hege, Brandhuber, & Schmidhalter 2003;Flowers et al, 2003;Hansen et al, 2003;Vrindts et al, 2003). In a review of 17 studies of variable N, P and K application rates by Lowenberg and Swinton (1997) five were unprofitable, six were intermediate and six were profitable.…”

Section: Discussionmentioning

confidence: 98%

“…Jiang & Thelen, 2004;Yang et al 1998;Vrindts et al 2003) have observed significant relations between yield and topography within a field. However, those observed in our study were both positive and negative (data not shown) and there was no general significant interaction between N application and most topographic indices.…”

Section: Discussionmentioning

confidence: 99%

Algorithms for sensor-based redistribution of nitrogen fertilizer in winter wheat

Berntsen¹,

Thomsen²,

Schelde³

et al. 2006

Precision Agric

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Several methods were developed for the redistribution of nitrogen (N) fertilizer within fields with winter wheat (Triticum aestivum L.) based on plant and soil sensors, and topographical information. The methods were based on data from nine field experiments in nine different fields for a 3-year period. Each field was divided into 80 or more subplots fertilized with 60, 120, 180 or 240 kg N ha )1 . The relationships between plot yield, N application rate, sensor measurements and the interaction between N application and sensor measurements were investigated. Based on the established relations, several sensorbased methods for within-field redistribution of N were developed. It was shown that plant sensors predicted yield at harvest better than soil sensors and topographical indices. The methods based on plant sensors showed that N fertilizer should be moved from areas with low and high sensor measurements to areas with medium values.The theoretical increase in yield and N uptake, and the reduced variation in grain protein content resulting from the application of the above methods were estimated. However, the estimated increases in crop yield, N-uptake and reduced variation in grain protein content were small.

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“…Sensors that quantify crop parameters, such as the quantity of the biomass and photosynthesis activity, are already available on the market. Sensors used to evaluate plant stress90, 91 or spectral analysis of the crop canopy parameters92–94 would open the way towards more target‐oriented spraying for crop protection purposes. Smaller treatment units could be achieved in the field95, 96 using these methods.…”

Section: Actionsmentioning

confidence: 99%

Combining novel monitoring tools and precision application technologies for integrated high‐tech crop protection in the future (a discussion document)

Zijlstra¹,

Lund

Justesen

et al. 2011

Pest Management Science

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The possibility of combining novel monitoring techniques and precision spraying for crop protection in the future is discussed. A generic model for an innovative crop protection system has been used as a framework. This system will be able to monitor the entire cropping system and identify the presence of relevant pests, diseases and weeds online, and will be location specific. The system will offer prevention, monitoring, interpretation and action which will be performed in a continuous way. The monitoring is divided into several parts. Planting material, seeds and soil should be monitored for prevention purposes before the growing period to avoid, for example, the introduction of disease into the field and to ensure optimal growth conditions. Data from previous growing seasons, such as the location of weeds and previous diseases, should also be included. During the growing season, the crop will be monitored at a macroscale level until a location that needs special attention is identified. If relevant, this area will be monitored more intensively at a microscale level. A decision engine will analyse the data and offer advice on how to control the detected diseases, pests and weeds, using precision spray techniques or alternative measures. The goal is to provide tools that are able to produce high-quality products with the minimal use of conventional plant protection products. This review describes the technologies that can be used or that need further development in order to achieve this goal.

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Analysis of Soil and Crop Properties for Precision Agriculture for Winter Wheat

Cited by 31 publications

References 7 publications

Uniformity of wheat yield and quality using sensor assisted application of nitrogen

Uniformity of wheat yield and quality using sensor assisted application of nitrogen

Algorithms for sensor-based redistribution of nitrogen fertilizer in winter wheat

Combining novel monitoring tools and precision application technologies for integrated high‐tech crop protection in the future (a discussion document)

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