Model of Color Parameters Variation and Correction in Relation to “Time-View” Image Acquisition Effects in Wheat Crop

Sala, F.; Popescu, Cosmin; Herbei, Mihai Valentin; Rujescu, Ciprian

doi:10.3390/su12062470

Cited by 6 publications

(4 citation statements)

References 57 publications

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“…where: Carcarotenoid content; x -Chl, chlorophyll content Variable doses of fertilization were studied for different agricultural crops, in the reference area, from the perspective of optimizing technologies and yields, and imaging analysis methods were used to describe the wheat crop under field conditions (Sala and Boldea, 2011;Sala et al, 2020). Recent studies on the distribution of Chl and Car along the length of wheat leaves (Jurjescu and Sala, 2023).…”

Section: Figure 4 the Distribution Of The Residual Values In The Anal...mentioning

confidence: 99%

Nitrogen Variable Rate Influence on Photosynthetic Pigments in Wheat Flag Leaf

GHERBAN,

SALA

2023

LSSD

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The study evaluated the variation of photosynthetic pigments (chlorophyll, carotenoids) in wheat flag leaves in relation to the nitrogen variation rate. The PG102 winter wheat variety was cultivated, in non-irrigated conditions, on a chernozem type soil. Nitrogen was applied in doses of 0 - 280 kg ha-1 a.s., in a variation rate of 40 kg ha-1 a.s. (active substances). The field experiments took place in ULS "King Mihai I" from Timisoara, Romania. At the time of flowering (BBCH code 6), random samples of flag leaves were taken on each experimental variant. The chlorophyll content (Chl) varied between Chl = 43.73±1.04 (V1) and Chl = 58.92±1.21 (V6). The carotenoid content (Car) varied between Car = 10.12±0.59 (V1) and Car = 21.56±0.49 (V6). Based on the Chl and Car values, the Chl/Car and Car/Chl ratios were calculated for each experimental variant. According to Kruskal-Wallis test, resulted significant difference between sample medians (p (same) = 1.56E-05 in case of Chl data series; p (same) = 2.616E-09 in case of Car data series). The variation of Chl and Car pigments in relation to nitrogen (N) was described by polynomial equations of the 3rd degree, under statistical safety conditions (R2 = 0.981 in the case of Chl; R2 = 0.986 in the case of Car; p<0.001). The variation of Car in relation to Chl was described by a polynomial equation of degree 3 (R2 = 0.978, p<0.001).

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Section: Figure 4 the Distribution Of The Residual Values In The Anal...mentioning

confidence: 99%

Nitrogen Variable Rate Influence on Photosynthetic Pigments in Wheat Flag Leaf

GHERBAN,

SALA

2023

LSSD

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“…Modern total stations and GPS receivers have their own applications with which, working on codes, you can get the plan and map directly to the field. They are then downloaded to the computer and can be plotted from there (Sala et al, 2020).…”

Section: Figure 3 Support Network (S1 S2 S3 S4 S5)mentioning

confidence: 99%

Study Regarding the Necessary Topographic Works Drawing on the Field of the Main Topographic Elements of Agritouristic Construction

CĂLINA¹,

CĂLINA²

2020

AAMC

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The paper presents a modern method of field application of an agrotourism reception structure using a high-performance topographic equipment of the latest generation, with the help of which a series of completely new procedures and tracing operations could be applied on the field. The construction will be located in the beautiful and dynamic agrotourism area Bulzești - Măldărești, in the South-West Oltenia development region, an area that has a rich and valuable natural and anthropic tourist potential, which has not been capitalized on its true value, due to the lack of main of the tourist reception structures. The aim of the paper was to prepare in the best conditions the technical documentation necessary primarily for the design of the construction, but at the same time it can be used further in the next phases of its drawing and actual execution. From the presented, it was found that the work performed fully complies with the precision requirements and legal regulations imposed on such a work, and tracing as the main method of field application of the main elements of a construction could be performed according to the requirements of precision, detail and accuracy by the designer and the beneficiary.

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“…In wheat crop, imaging analysis based on different types of images (satellite, aerial or terrestrial) was frequently used to analyze and characterize the state of plant vegetation in relation to soil, climatic and technological conditions (Constantinescu et al, 2018;Sala et al, 2020;Cheng et al, 2022) The estimation of wheat production based on remote sensing techniques has also been the subject of numerous studies, which have developed statistical safety estimation models (Aranguren et al, 2020;Cheng et al, 2022;Saad El Imanni et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Wheat Crop and Production Estimation Based on Remote Sensing

HERBEI,

JURJESCU,

SALA

2023

LSSD

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Based on remote sensing, the study analyzed the dynamics of a wheat crop using regression analysis to estimate production in relation to the NDMI, NDVI, MSAVI and NBR indices. The wheat crop considered in the study, was located in the area of Sacalaz, Timis county, Romania. Seven series of satellite images were taken, between February and June 2021. Based on the spectral information, the NDMI, NDVI, MSAVI and NBR indices were calculated and series of 595 values were obtained for each index. Very strong correlations were recorded between NBR and NDMI (r=0.999***), between MSAVI and NDVI (r=0.994***), between NBR and MSAVI (r=0.919**), between NDVI and NDMI ( r=0.911) and between NBR and NDVI (r=0.909**). Polynomial equations described the variation of NBR in relation to NDMI (R2=0.987), in relation to MSAVI (R2=0.794) and in relation to NDVI (R2=0.795). The variation of indices in relation to time, during the study period, was described by polynomial equations of the 2nd and 3rd degree, under statistical accuracy conditions (R2=0.854 for NDMI; R2=0.919 for NDVI; R2=0.956 for MSAVI, and R2=0.873 for NBR). Through the regression analysis, the wheat production was predicted, based on the calculated indices, and in different combinations of indices. The highest level of accuracy in the prediction of wheat production was recorded in the case of using the NDMI and NBR indices (p<0.001, RMSPE=0.24847), followed by the analysis variant in which the NDVI and MSAVI indices were considered (p=0.0002, RMSEP=1.59084) and the analysis variant in which NDVI and NBR indices were used (p=0.00081, RMSEP=5.20218). Graphical models, in 3D format and in the form of isoquants, have described the variation of wheat production in relation to the NDMI, NDVI, MSAVI and NBR indices.

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Model of Color Parameters Variation and Correction in Relation to “Time-View” Image Acquisition Effects in Wheat Crop

Cited by 6 publications

References 57 publications

Nitrogen Variable Rate Influence on Photosynthetic Pigments in Wheat Flag Leaf

Nitrogen Variable Rate Influence on Photosynthetic Pigments in Wheat Flag Leaf

Study Regarding the Necessary Topographic Works Drawing on the Field of the Main Topographic Elements of Agritouristic Construction

Evaluation of the Wheat Crop and Production Estimation Based on Remote Sensing

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