Relationship of cotton nitrogen and yield with Normalized Difference Vegetation Index and plant height

Zhou, Guisu; Yin, Xinhua

doi:10.1007/s10705-014-9640-y

Cited by 15 publications

(12 citation statements)

References 24 publications

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“…Iqbal et al (2013) performed a study on the correlation between NDVI and yield over the cotton cycle and observed that in the wettest year (1998) the correlation was smaller ( r = 0.81; p < 0.05) than in the driest year (1999: r = 0.91; p < 0.05). According to Zhou and Yin (2014), local field variations, seasonal climate changes, and soil N content before seeding cause variations in the correlation and the regression parameters of NDVI and cotton fiber yield.…”

Section: Resultsmentioning

confidence: 99%

Soil Chemical Attributes, Soil Type, and Rainfall Effects on Normalized Difference Vegetation Index and Cotton Fiber Yield Variability

2019

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Understanding of how crop yield is influenced by interactions between the soil and environment is needed to minimize agricultural inputs and reduce the impacts of agriculture on the environment. The objective of this study was to determine the effect of soil chemical attributes, soil type, and rainfall on cotton (Gossypium hirsutum L.) yields and yield variability. In this study, the average cotton fiber yield was collected from 101 fields over nine crop seasons. In these fields, located in central Brazil, the average and standard deviation of normalized difference vegetation index (NDVI) were determined. Growing season rainfall and soil nutrients were measured. The variables analyzed were: average cotton fiber yield, NDVI from Landsat images calculated at the boll development phenological stage (enlargement and fiber filling phases), CV of the NDVI, precipitation during the cycle, and soil chemical attributes. The average field NDVI values collected at the boll development phenological stage were correlated to yield (r = 0.50; p < 0.05). Fields with a higher CV for the NDVI values generally had lower yields. The effect of precipitation depends on the cotton phenological stage and soil type. A high rainfall volume at the beginning of the cropping cycle increased plant height variability, which harmed the cotton fiber yield. The highest average values of aluminum content, aluminum saturation, and potential acidity promoted variability in cotton plant growth. Soil chemical attributes related to aluminum were negatively correlated with yield (r = −0.34; p > 0.05). Core Ideas Annual averages of NDVI and yield presented a significant correlation. The effect of precipitation depends on the cotton phenological stage and soil type. Soil chemical variables related to aluminium are negatively correlated with the yield.

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Section: Resultsmentioning

confidence: 99%

Soil Chemical Attributes, Soil Type, and Rainfall Effects on Normalized Difference Vegetation Index and Cotton Fiber Yield Variability

2019

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“…Booker et al (2015) demonstrated that soil and growth parameters required by cotton crops grown in different climatic conditions could be modeled in temporal and spatial resolution to be applied in management practices. Another option for managing crop variability, in corn and cotton, for example, is the application of variable-rate nitrogen to suit the crop needs across different locations (MAHLEIN et al, 2012;HOLLAND;SCHEPERS, 2013;BRAGAGNOLO et al, 2013;ZHOU;YIN, 2014).…”

Section: Resultsmentioning

confidence: 99%

Relationship between cotton productivity and variability of NDVI obtained by landsat images

Baio¹,

Neves²,

Campos³

et al. 2018

Biosci. J.

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The availability of satellite images has generated a large number of regional and global studies on vegetation mapping. Such studies have related the growth parameters, nutrient status, physiological responses, and water resources to the yield of agricultural crops or native vegetation. The NDVI (Normalized Difference Vegetation Index) is associated with parameters of growth and yield with readings at several moments of the crop cycle. The objective of this work was to correlate the yield and variability of the NDVI in cotton fields by analyzing Landsat satellite images acquired over nine growing seasons. The study involved the analysis of 101 cotton production fields located in West-Central Brazil. One Landsat image was used during each crop cycle, and the average yield was computed based on total fiber harvested at each field. The fiber yield ranged from 393 to 2,030 kg ha -1, and its correlation with NDVI was 0.37. The coefficient of variation (CV) had a negative correlation with yield, approximating -58.1 kg ha -1 for every one percent increment of the CV. The CV explained the yield variability over the cotton fields more accurately than the average absolute NDVI value.

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“…In addition, even though there were no significant differences for the first productive PP (Table 5), these results seem to be partially related to the lower accumulated boll number at early fruiting sites. Usually, increased N rates intensify vegetative growth (Gardner and Tucker, 1967;Gerik et al, 1994;Zhou and Yin, 2014), which may result in a lower yield proportion at first PPs. This response was clearly observed in Itapeva, where the two highest N rates resulted in at least 3.19 more bolls per plant compared with the two lowest ones above the 16th PP (Table 6).…”

Section: Discussionmentioning

confidence: 99%

Shading and Nitrogen Effects on Cotton Earliness Assessed by Boll Yield Distribution

2019

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Shading and N fertilization affect fruit distribution in cotton (Gossypium hirsutum L.), but there is no detailed information on earliness of crop maturity according to phenological development. The aim of this work was to evaluate the effect of shading at early flowering and N top‐dressing rates on relative cotton earliness using plant mapping. Field experiments were conducted in Itapeva (16 d of shading; and 0, 60, 120, and 180 kg N ha−1) and Chapadão do Sul (17 d of shading; 0, 80, and 160 kg N ha−1; and early‐ and full‐season cultivars), Brazil. Seed cotton yield was grouped by phenological position (PP) according to the standard phenological scale, for interpolation calculation at each 10% increment in accumulated harvestable yield (Ac), weighted average PP (PPwa) determination, and logistic‐regression analysis. Crop maturity earliness was predicted based on the reduction in PPwa and in PP. Shading increased PP up to 10 and 30% of Ac due to a decrease of 33 and 40% in the number of bolls on early fruiting sites in Itapeva and Chapadão do Sul, respectively, but did not affect PPwa. Increases in PP up to high Ac percentages and in PPwa values were observed at the two higher N rates in both experiments, mainly due to lower and higher boll number at earlier and later fruiting sites, respectively. Short‐term shading during early flowering of cotton changed yield distribution by decreasing boll number on early fruiting sites, but did not affect the earliness of crop maturity. Earliness was decreased by high N rates due to higher cumulative seed cotton yield at later fruiting sites.

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Relationship of cotton nitrogen and yield with Normalized Difference Vegetation Index and plant height

Cited by 15 publications

References 24 publications

Soil Chemical Attributes, Soil Type, and Rainfall Effects on Normalized Difference Vegetation Index and Cotton Fiber Yield Variability

Soil Chemical Attributes, Soil Type, and Rainfall Effects on Normalized Difference Vegetation Index and Cotton Fiber Yield Variability

Relationship between cotton productivity and variability of NDVI obtained by landsat images

Shading and Nitrogen Effects on Cotton Earliness Assessed by Boll Yield Distribution

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