Applying a digital method for measuring leaf area index of tomato plants

Abdelkader, Mostafa; Puchkov, Mikhail; Loktionova, Elena

doi:10.2991/ispc-19.2019.2

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…Forage samples were dried in a forced air oven at 60 • C for 48 h, until constant weight. To obtain the green LAI, leaf samples were scanned and digitally processed in the Image J software [39], which is a very common way to estimate the foliar area [40][41][42]. Finally, the FVC was estimated from the zenithal photographs using a supervised classification performed in PCI Geomatics Banff software, which allowed the segmentation of green/dry covers, bare soil and shadows [43].…”

Section: Field and Laboratory Estimationsmentioning

confidence: 99%

UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations

et al. 2021

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The capability of UAVs imagery to monitor and predict the evolution of several forage associations was assessed during the whole growing cycle of 2019–20. For this purpose, eight different forage associations grown in triplicate were used: vetch-barley-triticale (VBT), vetch-triticale (VT), vetch-rye (VR), vetch-oats (VO), pea-barley-triticale (PBT), pea-triticale (PT), pea-rye (PR) and pea-oats (PO). Six biophysical parameters were monitored through six vegetation indices on seven measurements dates distributed along the growing cycle. The experiments were carried out on the organic farm “Gallegos de Crespes” located in the municipality of Larrodrigo (Salamanca, Spain). The results obtained in the exploratory and the correlation analysis suggested that a predictive model (PLS regression) could be performed. Overall, vetch-based associations showed slightly higher values for both the field parameters and the vegetation indices than pea-based ones. Correlations were very strong and significant for each association throughout their growing cycle, suggesting that the evolution of the associations would be monitored from the spectral indices. Integrating these multispectral observations in the PLS model, the agronomic parameters of forage associations were predicted with a reliability of more than 50%. A single combination of VNIR (or even only visible) bands was able to feed the regression model, leading to a successful prediction of the agronomic parameters.

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Section: Field and Laboratory Estimationsmentioning

confidence: 99%

UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations

et al. 2021

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“…Penggaris dipilih karena tingkat akurat yang lebih tinggi [8]. Pengambilan gambar dilakukan dua kali dengan posisi yang sama untuk menghitung tingkat error pada foto pertama dan kedua.…”

Section: A B Gambar 1 A) Tempat Pengambilan Citra B) Hasil Pengambila...unclassified

“…Laju pertumbuhan tanaman dipengaruhi oleh laju asimilasi bersih dan indeks luas daun. Laju asimilasi bersih yang tinggi dan indeks luas daun daun yang optimum meningkatkan pertumbuhan tanaman, indeks luas daun (LAI) merupakan variabel penting yang digunakan untuk mengevaluasi banyak proses seperti kanopi, fotosintesis dan evapotranspirasi yang berperan peran penting dalam transformasi energi dan massa antara atmosfer dan kanopi tanaman [8].…”

Section: Introductionunclassified

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Penerapan Metode Digital Untuk Mengukur Indeks Luas Daun Tanaman Sawi Caisim (Brassica Juncae L.)

Nurholis

Umam

Syafii

et al. 2023

JPP

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Tujuan dari penelitian ini adalah untuk mengetahui perbandingan luas daun sawi caisim dari beberapa dosis nutrisi menggunakan software ImageJ. Dalam perhitungan luas daun menggunakan objek referensi sebagai perbandingan dalam input nilai luas daun dalam bentuk pixel yang kemudian diubah dalam bentuk centimeter. Setelah itu, citra gambar diubah ke dalam bentuk citra biner (0 dan 1). Kemudian tahap akhirnya dengan memilih gambar daun untuk mengetahui luasannya. Pada penelitian ini proses pengambilan gambar dilakukan dua kali untuk melihat tingat error pada pengambilan pertama dan kedua. Metode pengukuran luas area daun yang diusulkan mendapatkan tingkat akurasi dan presisi yang tinggi sehingga dapat menghemat waktu, tenaga, serta biaya. Pengujian menggunakan ANOVA mendapatkan hasil tidak berbeda nyata sehingga pengambilan gambar sebanyak apapun tidak akan berpengaruh pada perhitungan luas area daun.

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“…The dry weight of whole plants was obtained after washing with deionized water and drying in an oven at 60 °C for more than 48 hours (10 samples per replicate). The average leaf area was measured using the Image J program as described by Abdelkader et al (2019a). The relative growth rate (RGR) was calculated according to the formula: RGR = (ln 𝑊2 − ln 𝑊1)/(𝑡2 − 𝑡1), and expressed as g•g -1 •week -1 .…”

Section: Biometric Parametersmentioning

confidence: 99%

The Influence of Biostimulants on Tomato Plants Cultivated under Hydroponic Systems

Abdelkader

Gaplaev

Terekbaev

et al. 2021

Journal of Horticultural Research

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Two biostimulants, RutfarmMaxifol (Ascophyllum nodosum extract 17.5%, amino acids, macro- and microelements, Agromaster, Russia) and Radifarm (polysaccharides, glycosides, amino acids, and micro-elements; Valagro, Italy), were applied at different concentrations on tomato plants of the hybrid cultivar ‘Merlice’, grown under a hydroponic system. Biostimulants were applied in the form of seed soaking and twice as foliar sprayings at flowering and at the initial fruit development stages. Biostimulants were applied as water solutions at concentrations of 2.5, 5.0, and 7.5 mg·L−1. Plant growth, productivity, and fruit quality parameters were determined at three points: 35, 70, and 105 days after seeding. All biostimulant treatments resulted in higher values of growth parameters and yield productivity in relation to the control. The application of biostimulants improved the parameters of the fruits’ quality by increasing the total soluble solids and antioxidants, ascorbic acid, and carotenoid contents but it did not affect tomato fruit acidity; therefore, tomato fruits from the treated plants were tastier than those from control.

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Applying a digital method for measuring leaf area index of tomato plants

Cited by 5 publications

References 7 publications

UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations

UAV Multispectral Imaging Potential to Monitor and Predict Agronomic Characteristics of Different Forage Associations

Penerapan Metode Digital Untuk Mengukur Indeks Luas Daun Tanaman Sawi Caisim (Brassica Juncae L.)

The Influence of Biostimulants on Tomato Plants Cultivated under Hydroponic Systems

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