Use of nondestructive sensors to quantify ornamental kale nitrogen status

Dunn, Bruce L.; Shrestha, Arjina; Goad, Carla L.

doi:10.1080/01904167.2015.1069342

Cited by 12 publications

(12 citation statements)

References 26 publications

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“…However, all three variables increased with increasing fertilizer rates with the 10-and 15-g treatments not showing differences for height and dry weight and the 5-, 10-, and 15-g treatments not showing any difference for plant width (Table 3). Dunn et al (2014) also reported similar findings for ornamental kale 'Nagoya Red' in which 10-, 15-, and 20-g fertilizer rates were not different for height and width and no difference was observed for fresh weight among the 5-, 10-, 15-, and 20-g fertilizer rates at 53 d after treatment. Gibson and Whipker (2000) reported no differences in height among fertilizer rates and differences between the lowest fertilizer rate of 150 mg • L -1 and the two higher rates of 200 and 250 mg • L -1 after B-Nine foliar applications for ornamental kale.…”

Section: Plantsupporting

confidence: 66%

“…For SPAD, week effects were not different, but for atLEAF, weeks were significant indicating greater accuracy in detecting changes in leaf N concentration (Tables 1, 2, and 4). Cultivar differences, sampling location, and number of readings can effect accuracy, because Dunn et al (2014) (Table 4). Leaf N concentration increased with increasing fertilizer rates (Table 4).…”

Section: Resultsmentioning

confidence: 99%

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Effect of Foliar Nitrogen and Optical Sensor Sampling Method and Location for Determining Ornamental Cabbage Fertility Status

Dunn¹,

Goad²

2015

horts

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Leaf nitrogen (N) and contact optical sensor sampling methods vary in the literature. Thus, the objective of this study was to determine the best sampling procedure for correlating leaf N concentration to contact optical sensor readings. To investigate this, fertilizer rates of 0, 5, 10, or 15 g of 16N–9P–12K were applied as a topdress application on ornamental cabbage (Brassica oleracea L.) ‘Tokyo Red’. Soil plant analysis development (SPAD) and atLEAF chlorophyll meters were used every week for 5 weeks starting 30 days after planting. For each pot, SPAD and atLEAF measurements were taken from a single mature leaf from the middle to upper level of the plant at the leaf tip, blade, or base of the leaf not including the midrib. Weekly leaf foliar analysis consisted of collecting either fully developed leaves from a single plant, five plants, or 10 plants per, using only the tip, blade, or base of three leaves for total leaf N concentration per treatment. A significant position affect was seen in both SPAD and atLEAF sensors. For SPAD, sensor readings taken from the tip and blade of a leaf were not significantly different from each other but were significantly different from the base of the leaf. All three positions for atLEAF were significantly different from each other. This indicates that sensor sampling location within a leaf will affect readings. A significant difference was observed among leaf sampling methods. Taking leaf samples from the tip and base had the highest leaf N concentrations and were not significantly different from each other but were significantly different from all other sampling methods, which were not significantly different from each other. Significant correlations were seen among all combinations of sensor positions and leaf N sampling methods except SPAD readings taken from the tip and leaf sampling from a single plant. Highest correlations (r = 0.7 to 0.8) were seen when SPAD readings were taken from the base of the leaf irrespective of leaf sampling method. Based on this experiment, either sensor could be used for correlating leaf N; however, growers should consistently collect sensor readings from the same location on a leaf to achieve consistent values and correlations.

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Section: Plantsupporting

confidence: 66%

Section: Resultsmentioning

confidence: 99%

Effect of Foliar Nitrogen and Optical Sensor Sampling Method and Location for Determining Ornamental Cabbage Fertility Status

Dunn¹,

Goad²

2015

horts

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“…However, cabbage or other vegetables often deliver some unique characteristics, such as dispersed distribution, various varieties, short-term growth cycle and complicated canopy architecture; and few studies have directly examined the practical utilization of Greenseeker hand-held optical sensor in vegetable production systems. Limited studies such as Sanderson et al (2012) found that Greenseeker had the potential to be an in-situ carrot health assessment tool and Dunn et al (2015) reported that the NDVI measurements of ornamental kale showed good correlations with leaf N content [ 31 , 32 ]. Nevertheless, these studies didn’t build any yield prediction or nitrogen recommendation algorithm for vegetable.…”

Section: Introductionmentioning

confidence: 99%

In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor

Jiang

Wang

et al. 2017

Sensors

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Efficient and precise yield prediction is critical to optimize cabbage yields and guide fertilizer application. A two-year field experiment was conducted to establish a yield prediction model for cabbage by using the Greenseeker hand-held optical sensor. Two cabbage cultivars (Jianbao and Pingbao) were used and Jianbao cultivar was grown for 2 consecutive seasons but Pingbao was only grown in the second season. Four chemical nitrogen application rates were implemented: 0, 80, 140, and 200 kg·N·ha−1. Normalized difference vegetation index (NDVI) was collected 20, 50, 70, 80, 90, 100, 110, 120, 130, and 140 days after transplanting (DAT). Pearson correlation analysis and regression analysis were performed to identify the relationship between the NDVI measurements and harvested yields of cabbage. NDVI measurements obtained at 110 DAT were significantly correlated to yield and explained 87–89% and 75–82% of the cabbage yield variation of Jianbao cultivar over the two-year experiment and 77–81% of the yield variability of Pingbao cultivar. Adjusting the yield prediction models with CGDD (cumulative growing degree days) could make remarkable improvement to the accuracy of the prediction model and increase the determination coefficient to 0.82, while the modification with DFP (days from transplanting when GDD > 0) values did not. The integrated exponential yield prediction equation was better than linear or quadratic functions and could accurately make in-season estimation of cabbage yields with different cultivars between years.

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“…Tissue testing, such as petiole nitrate concentration, assessed by selective electrodes (Vitosh and Silva 1994;Sims et al 1995) or test strips (Sims et al 1995;Rodrigues 2004;Rodrigues et al 2005) and also chlorophyll measurements through portable tools (Schepers et al 1992; Rodrigues et al 2006;Arrobas, Aguiar, and Rodrigues 2016) may be valuable alternatives. The reflectance properties of the canopy, assessed by handheld spectroradiometers (Basyouni, Dunn, and Goad 2015;Dunn, Shrestha, and Goad 2016), imagery from satellite sensors (Gitelson, Peng, and Huemmrich 2014;Zhang et al 2014) or digital cameras (Hardin et al 2012;L opez-Bellido et al 2012) have also been used to estimate nutritional status of plants. Tissue tests are, however, more popular since they are available to a large research community as well as farmers.…”

Section: Introductionmentioning

confidence: 99%

Assessing the potential use of two portable chlorophyll meters in diagnosing the nutritional status of plants

Afonso

Arrobas

Ferreira

et al. 2017

Journal of Plant Nutrition

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The SPAD-502 and the FieldScout CM 1000 chlorophyll meters were compared in their performance in diagnosing the nutritional status of plants.Leaves of a wide range of greenness were used to push the sensitivity of the tools to their limits. Both devices showed high reproducibility when used by different operators. The SPAD-readings were well-correlated with leaf nitrogen (N) concentrations, since leaves from heavily fertilized plants were not included in the sample population. The FieldScout-readings showed a marked saturation curve with the leaf N concentration, thus it cannot be used as a reliable N nutritional status index. The results also showed that the use of SPAD-502 in the diagnosis of the nutritional status of an orchard requires the establishment of specific critical concentrations for cultivars and sampling dates. The SPAD-502 appeared to have potential in the diagnosis of the nutritional status of the orchard for nutrients other than N.

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Use of nondestructive sensors to quantify ornamental kale nitrogen status

Cited by 12 publications

References 26 publications

Effect of Foliar Nitrogen and Optical Sensor Sampling Method and Location for Determining Ornamental Cabbage Fertility Status

Effect of Foliar Nitrogen and Optical Sensor Sampling Method and Location for Determining Ornamental Cabbage Fertility Status

In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor

Assessing the potential use of two portable chlorophyll meters in diagnosing the nutritional status of plants

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