Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model

Nyalala, Innocent; Okinda, Cedric; Nyalala, Luke; Makange, Nelson Richard; Chen, Qi; Liu, Chao; Yousaf, Khurram; Chen, Kunjie

doi:10.1016/j.jfoodeng.2019.07.012

Cited by 102 publications

(55 citation statements)

References 38 publications

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“…The largest dimensions of the fruit are obtained with the dose of 2 t ha -1 (Figure 6), possibly with this dose the balance or sufficient amount of calcium in the soil was achieved to satisfy the needs of the tomato plant, which in turn it could positively influence the plant to absorb it together with other nutrients, in addition the calcium applied to the soil probably influenced the epidermal extensibility and the development of the tissues of the fruit's pericarp, this division and elongation of the tissues of the pericarp of the fruit, are determining for the growth of the tomato. 29,30 In this regard, previous studies, [31][32][33] states that while epidermal cells divide throughout the development of the fruit, the division in the pericarp is limited to a short period of fruit development and it is located in the outer tissues around in the vascular bundles and in the hypodermis. Once the cell division ends, cell expansion begins to increase the size of the fruit.…”

Section: Components Of Tomato Crop Yieldmentioning

confidence: 96%

Effect of the liming on the soil chemical properties and the development of tomato crop in Sucre- Colombia

Herrera¹,

Pérez²

2020

JABB

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The acidity of the soil produces complex interactions on plant growth limiting factors that involve physical, chemical and biological properties of the soil, which can manifest in deficiencies of calcium, magnesium and phosphorus and toxicity of aluminum, iron, and manganese, which could limit plant growth. Based on the above and in order to contribute to better development of tomato crop in soils with a low nutritional offer and acid reaction of the Santa Clara region (Sucre), the following research has been proposed with five (5) commercial lime dose (0, 1, 2, 3 and 4 t ha-1) and its effect on chemical properties, using tomato as an indicator plant. The effect on pH, P, Ca, Mg and K in the soil was evaluated, and in the plant, the yield components were evaluated (weight and dimensions of the fruit, yield). A completely randomized design with three repetitions was used, the information was processed with the statistical software SAS version 9.1. It was found that liming improves soil pH, availability of P, Ca, Mg and K, in the same way, the development and yield of tomato crop with doses of up to 3 t ha-1 of lime on the soil is improved.

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Section: Components Of Tomato Crop Yieldmentioning

confidence: 96%

Effect of the liming on the soil chemical properties and the development of tomato crop in Sucre- Colombia

Herrera¹,

Pérez²

2020

JABB

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“…[8] The fruit size and weight directly influence storage and transport costs, eventually influencing sales and marketing prices. [9,10] Fruit volume and density relate to fruit consistency, carbon consumption, and water content used to forecast harvesting periods. [7,11] The average density, critical in identifying hidden defects such as frost and internal damage, can be determined when the weight is combined with the volume.…”

Section: Introductionmentioning

confidence: 99%

“…[7,11] The average density, critical in identifying hidden defects such as frost and internal damage, can be determined when the weight is combined with the volume. [9] CONTACT Chen Kunjie kunjiechen@njau.edu.cn College of Engineering, Nanjing Agricultural University, Jiangsu, 210031, P. R. China…”

Section: Introductionmentioning

confidence: 99%

“…[12,13] However, in large-scale processing, these manual processes are labor-intensive and costly, besides being invasive, unsanitary, individualized, and susceptible to error. [9,10,14,15] Classifications of size, volume, and weight are essential steps after harvesting in grading and sorting most agricultural products. The sorting operation helps customers effectively recognize product quality and contributes to better-coordinated distribution and delivery of agricultural products.…”

Section: Introductionmentioning

confidence: 99%

“…The efficiency is limited, costly, inconsistent, and unreliable in the conventional approach to adjust to the rise in customer needs. [9,15,16] Image processing is a revolutionary innovation that has seen tremendous improvement in recent years, both practically and theoretically. With the advances in machine vision technologies, numerous researchers have indicated computer vision systems in the weight and size measurement of several agricultural products as a precise, nondestructive, efficient, and non-intrusive technique.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Weight and volume estimation of single and occluded tomatoes using machine vision

Nyalala

Okinda

Chen

et al. 2021

International Journal of Food Properties

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The fundamental characteristics of agricultural products are appearance, size, and weight, which affect their market value, consumer preference, and choice. Thus, food and agricultural industries seek rapid, simple, and nondestructive approaches to assess real-time measurements at the postharvest stage before packaging for the consumer market. While sorting and grading may be performed by humans, it is unreliable, time-consuming, complicated, subjective, onerous, expensive, and easily influenced by surroundings. Therefore, an astute sorting and grading method for tomato fruit is required. We evaluated two tomato configurations on a conveyor belt: single tomatoes (no occlusion) and multi-tomatoes (partially occluded). We used polygon approximation for concave and convex point extraction algorithms to segment the occluded tomatoes. We developed seven models for regression using single-tomato image features. The Bayesian regularization artificial neural network outranked all the trained models in weight estimation with a root-mean-square error (RMSE) of 1.468 g and R 2 of 0.971. For volume estimation, the RBF SVM had the best performance with R 2 of 0.982 and RMSE of 1.2683 cm 3 . It is feasible to implement a proposed system as a noninvasive in-line sorting technique for tomatoes.

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Varietal quality control in the nursery plant industry using computer vision and deep learning techniques

Borraz-Martínez

Tarres

Boqué

et al. 2020

Journal of Chemometrics

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Computer vision coupled to deep learning is a promising technique with multiple applications in the industry. In this work, the potential of this technique has been assessed in the classification of two varieties of almond trees (Prunus dulcis), Soleta and Pentacebas. For that, a convolutional neural network named VGG16 was used. The most appropriate configuration for model training was studied, which included the comparison between two different filling modes (reflect and nearest) in the data augmentation step, the evaluation of the batch size and the analysis of the image sizes. The robustness of the model was also checked, and information was obtained about how the model extracts the information from the images. The results showed that the reflect fill mode was more effective than the nearest one. The best results were obtained using batches with 30 and 40 images, with an image size of (224 × 224) pixels. The verification of the robustness proved the capability of the technique as a promising tool for plant varietal identification.

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Tomato volume and mass estimation using computer vision and machine learning algorithms: Cherry tomato model

Cited by 102 publications

References 38 publications

Effect of the liming on the soil chemical properties and the development of tomato crop in Sucre- Colombia

Effect of the liming on the soil chemical properties and the development of tomato crop in Sucre- Colombia

Weight and volume estimation of single and occluded tomatoes using machine vision

Varietal quality control in the nursery plant industry using computer vision and deep learning techniques

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