Feasibility of SSC Prediction for Navel Orange Based on Origin Recognition Using NIR Spectroscopy

Lyu, Qiang; Liao, Qiuhong; Liu, Yanli; Lan, Yubin

doi:10.1080/10798587.2015.1015775

Cited by 9 publications

(5 citation statements)

References 29 publications

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“…Surface enhanced Raman spectroscopy analysis was used. Liu et al (2015) [20] found imidephosphorus residues on the surface of orange peel. In their search for the insecticide imidophos, they used materials such as Clarite and colloidal silver.…”

Section: Advance Techniques For Orchard Management In Fruit Productionmentioning

confidence: 99%

“…They found that four wavelength groups (550 nm, 640 nm, 680 nm, and 780 nm) were responsible for the nitrogen and chlorophyll content of the leaves during photoreaction. Liu et al (2015) [20] developed a method using spectroscopy to estimate the soluble content in Newhall oranges from seven sources. They used the true recurrence model (PLS) halfway through and found that the predictive model based on the initial analysis was valid.…”

Section: Advance Techniques For Orchard Management In Fruit Productionmentioning

confidence: 99%

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An overview on production constraints, strategies and innovative production technologies of fruit crops

Bisen

2024

Int. J. Adv. Biochem. Res.

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India ranks second in the world fruit production rankings, producing 13% of total fruit production. It is a leading producer of mango, banana, papaya, Sapota, and acid lime. Fruits are essential for human diets and are being researched under ICAR, leading to over 108 million tons of fruit production. The plant improvement programme has developed various fruit crops, including mango, banana, citrus, pineapple, papaya, guava, Sapota, jackfruit, litchi, grape, apple, peach, pear, plum, apricot, almond, walnut, Aonla, Ber, pomegranate, Annona, Phalsa, regular bearing mango hybrids, and export quality grape varieties. Improved propagation techniques have increased production and standardized agrotechniques for large-scale adoption. India has made significant progress in producing lesser-known fruits like Aonla, Ber, bael, Sapota, and pomegranate. The corporate sector is showing interest in fruit crops, and there has been a shift in consumption patterns. Recent fruit production techniques are expensive but profitable for large commercial growers, but most are still in the experimentation stage. Fruit crop management is crucial for producing high-quality fruits, with innovative techniques reducing time and labour requirements, increasing yield, and achieving sustainability goals. This review describes various production methods of fresh fruit. Modern technology related equipment is very expensive but very useful for growers who have a large business. Many of the technologies that benefit the fruit industry are still in the experimental phase. Management of fruit crops is an important factor affecting the time it takes to produce quality fruit for the market. New technologies for different processes in fruit production machines can help growers reduce time and labour, thereby increasing yields by achieving precise targets.

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Section: Advance Techniques For Orchard Management In Fruit Productionmentioning

confidence: 99%

Section: Advance Techniques For Orchard Management In Fruit Productionmentioning

confidence: 99%

An overview on production constraints, strategies and innovative production technologies of fruit crops

Bisen

2024

Int. J. Adv. Biochem. Res.

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“…The prediction performance for cultivar calibration models was assessed using the following indices: root-meansquare errors of calibration (RMSEC) and prediction (RMSEP), and correlation coefficient of calibration (Rc) and prediction (Rp) [44]. The main evaluation indices for the cultivar calibration models are the Rp and RMSEP values.…”

Section: Model Performance Assessmentmentioning

confidence: 99%

Nitrogen Status Assessment for Multiple Cultivars of Strawberries Using Portable FT-NIR Spectrometers Combined With Cultivar Recognition and Multivariate Analysis

Wu¹,

Jiang²,

Bai

et al. 2020

IEEE Access

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The nondestructive assessment of nitrogen status in strawberry was performed to analyze its growth and provide guidance for precise management of N fertilizer using Fourier transform near-infrared reflectance (FT-NIR) spectroscopy with leaf spectral reflectance. The leaf soil plant analysis development (SPAD) value is considered as an indicator that indirectly reflects the nitrogen status in strawberry. However, the variation of cultivars leads to differences in the cell structure and light scattering and/or reflection effects of strawberry leaves during strawberry N status assessment, which means, leaf SPAD threshold value and the specific N demand will vary with different cultivars. As a result, accurate measurement of SPAD values and N status in strawberries with multiple cultivars is still challenging. In this study, the individual-cultivar, hybrid-cultivar, and multi-cultivar models were developed for the determination of SPAD values, and the performance of the models in lessening the impact of cultivar variation was studied and compared. The individual-cultivar model was constructed on the basis of a single cultivar of strawberry leaf. The hybridcultivar model was developed by merging the spectrum reflectance data and SPAD values of all studied leaf samples, and a multi-cultivar model was built in combination with cultivar identification, individual-cultivar models, and model search strategy. The results indicated that the multi-cultivar model was superior to the other two models for SPAD value estimation of strawberry leaves from different cultivars, with the overall Rp and RMSEP values of 0.966 and 0.468, respectively. We demonstrate that the leaf N content of strawberry is profoundly affected by cultivar variation, and establishing a multi-cultivar model is useful in monitoring the nitrogen status and guiding N fertilization recommendations for different strawberry cultivars.

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“…The prediction performance for cultivar calibration models were assessed by the following indices: root-mean-square errors of the calibration (RMSEC) and prediction (RMSEP), and correlation coefficient of calibration (Rcal) and prediction (Rpre) [44].…”

Section: Model Performance Assessmentmentioning

confidence: 99%

Nitrogen status assessment for multiple cultivars of strawberries using portable NIR spectrometers combined with cultivar recognition and multivariate analysis

Jiang

Bai

et al. 2019

Preprint

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Background The assessment of nitrogen status non-destructively in strawberry was performed to indicate its growth and provide guidance for precise management of N fertilizer using near-infrared reflectance (NIR) spectroscopy with leaf spectral reflectance. The Leaf soil plant analysis development (SPAD) value was thought as an indicator data that indirectly reflects nitrogen status in strawberry. However, the variation of cultivars would lead to differences in the cell structure and light scattering and/or reflection effects of strawberry leaves when assessed strawberry N status, which caused that no single leaf SPAD threshold value or same N demand can be applied for all strawberry cultivars. As a result, accurate detection of SPAD values and N status in strawberries with multiple cultivars is still challenging.Results In this study, Individual-cultivar model, hybrid-cultivar model and multi-cultivar model were developed for the determination of SPAD values, and the performance of the models in lessening the impact of cultivar variation were studied and compared. Individual-cultivar model was constructed on the basis of the single cultivar of strawberry leaf; hybrid-cultivar model was developed by merging the spectrum reflectance data and SPAD values of all studied leaf samples, and multi-cultivar model was built in combination with cultivar identification, individual-cultivar models, and model search strategy.Conclusion The results indicated that multi-cultivar model was more superior to the other two models for SPAD values estimation of strawberry leaves from different cultivars, with the overall Rp and RMSEP value respectively being 0.966 and 0.468. We demonstrate that the leaf N content per strawberry is profoundly affected by cultivar variation, and establishing a multi-cultivar model might be more useful in monitoring nitrogen status and guiding N fertilization recommendations for different strawberry cultivars.

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Feasibility of SSC Prediction for Navel Orange Based on Origin Recognition Using NIR Spectroscopy

Cited by 9 publications

References 29 publications

An overview on production constraints, strategies and innovative production technologies of fruit crops

An overview on production constraints, strategies and innovative production technologies of fruit crops

Nitrogen Status Assessment for Multiple Cultivars of Strawberries Using Portable FT-NIR Spectrometers Combined With Cultivar Recognition and Multivariate Analysis

Nitrogen status assessment for multiple cultivars of strawberries using portable NIR spectrometers combined with cultivar recognition and multivariate analysis

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