Spectral indexes for identification of nitrogen deficiency in maize

Romualdo, Liliane Maria; Luz, Pedro Henrique de Cerqueira; Baesso, Murilo Mesquita; Devechio, Fernanda de Fátima da Silva; Bet, Jessica Angela

doi:10.5935/1806-6690.20180021

Cited by 7 publications

(7 citation statements)

References 2 publications

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“…These methods were chosen based on the good results obtained in the leaf texture analysis. In Luz et al (2018), Romualdo et al (2018), Silva et al (2014), Romualdo et al (2014), Backes and Bruno (2013), Rossatto et al (2011) and Backes et al (2009), the authors compared state of art texture methods for leaf identification and the best results were achieved by them.…”

Section: Experimental Designmentioning

confidence: 99%

“…Luz et al (2018) studied boron deficiency precisely identified on growth stage V4 of maize plant using texture image analysis, and achieved 88.75% of accuracy in differentiating between leaves using Fractal 3D, in V4 stage. Romualdo et al (2018) used spectral indexes for identification of nitrogen deficiency in maize, and found accuracy rate for N patterns was 80% at V4 stage and 93% at V7 stage. Baesso et al (2020) estudied artificial vision for nutritional diagnosis of corn grown with calcium silicate and magnesium and found a 66% of rights.…”

Section: Introductionmentioning

confidence: 99%

“…Baesso et al (2020),Luz et al (2018),Romualdo et al (2018),Silva et al (2014),Romualdo et al (2014), compared state of art texture methods for leaf identification of nutrition maize plants.…”

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confidence: 99%

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Calcium Deficiency Diagnosis in Maize Leaves Using Imaging Methods Based on Texture Analysis

Devechio¹,

Luz²,

Romualdo³

et al. 2022

JAS

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The artificial vision system (AVS) uses image analysis methods that can interpret images and identify nutritional deficiency symptoms in plant, even in the early stages of development. The objective of this study was to propose methods of image processing using analysis by texture to identify the deficiency of calcium (Ca) in maize (Zea mays L.) plants grown in nutrient solution. Plants were grown in nutrient solution in a greenhouse. Calcium doses were 0.0; 1.7; 3.3 and 5.0 mM of Ca, with four replications. Plant and leaf images were sampled at three main stages of maize development: V4 (plants with four leaves fully developed), V6 (plants with six leaves fully developed) and V8 (plants with eight leaves fully developed). Sampled material was split into (i) index leaf (IL) of the growing stage (V4 = leaf 4, V6 = leaf 6, and V8 = leaf 8), and (ii) new leaf (OL), both to image capture and chemical analysis. Such leaves were scanned, processed by the AVS and chemically analyzed. The texture methods used by the AVS to extract deficiency characteristics in the leaf images were: Volumetric Fractal Dimension (VFD), Gabor Wavelet Energy (GWE) and VFD with canonical analysis (VFDCA). The amount of Ca in the solution resulted in variation in the concentration of Ca in NL and IL, allowing the observation of typical symptoms of Ca deficiency. The AVS method was able to identify all Ca levels in leaves, being the GWE the best indicator using color images, scoring 80% of rights in images of the middle section of new leaves in V4.

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Section: Experimental Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Calcium Deficiency Diagnosis in Maize Leaves Using Imaging Methods Based on Texture Analysis

Devechio¹,

Luz²,

Romualdo³

et al. 2022

JAS

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“…Furthermore, plants may also exhibit similar external symptoms under different stress conditions [184]. Single inspection technology has some limitations, computer vision cannot recognize the chemical properties of plants, spectroscopy cannot detect the spatial information of the plant population [186,187]. Therefore, in future research, multi-technology combination and multi-information fusion will have great potential in crop N status diagnosis.…”

Section: Challenges Of the Choice Of Diagnostic Technology On N Non-d...mentioning

confidence: 99%

Recent Development and Challenges in Spectroscopy and Machine Vision Technologies for Crop Nitrogen Diagnosis: A Review

Zhang

Chen

et al. 2020

Remote Sensing

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Recent development of non-destructive optical techniques, such as spectroscopy and machine vision technologies, have laid a good foundation for real-time monitoring and precise management of crop N status. However, their advantages and disadvantages have not been systematically summarized and evaluated. Here, we reviewed the state-of-the-art of non-destructive optical methods for monitoring the N status of crops, and summarized their advantages and disadvantages. We mainly focused on the contribution of spectral and machine vision technology to the accurate diagnosis of crop N status from three aspects: system selection, data processing, and estimation methods. Finally, we discussed the opportunities and challenges of the application of these technologies, followed by recommendations for future work to address the challenges.

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“…Esta visão também é encontrada no trabalho de Camargo (2012), de que os fertilizantes são os principais responsáveis pelo suprimento de nutrientes do solo fazendo com que as culturas cultivadas consigam se desenvolver melhor. De fato, os fertilizantes são importantes para manter uma boa produtividade nas lavouras, muitos pesquisadores evidenciaram positivamente a adubação em culturas de interesse comercial informando ter melhorado os dados de produção (VÉRAS et al, 2015;PINHEIRO et al, 2017;SOUSA et al, 2017;ROMUALDO et al, 2018).…”

Section: Entrevistadosunclassified

Percepções de estudantes do curso técnico em agropecuária sobre o uso de fertilizantes no semiárido

Silva¹,

Moreira²,

Rodrigues³

et al. 2019

RICA

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Os diferentes conhecimentos expressos sobre o uso de fertilizantes químicos e orgânicos estão intimamente ligados à formação dos agricultores e profissionais que atuam no campo. Este estudo teve como objetivo analisar o conhecimento dos estudantes do curso Técnico Integrado em Agropecuária do Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte, campus de Apodi (RN) sobre a utilização de fertilizantes, químicos e orgânicos, na região do semiárido. Para tanto, foram aplicados questionários estruturados para estudantes do curso mencionado nesse campus. Posteriormente, as respostas foram analisadas e categorizadas em seis grupos: Supridores artificiais das necessidades do solo; Uso de fertilizantes sem critério técnico; Fertilizantes prejudiciais à saúde; Fertilizantes agressores do meio ambiente; Adubação orgânica benéfica ao solo; Ênfase Sustentável. Grande parte dos entrevistados acreditava que os fertilizantes químicos são usados para correção e nutrição do solo, trazendo benefícios para a produção, mas podem causar doenças e problemas ambientais, sobretudo em elevadas quantidades. Além disso, os estudantes também acreditam que a adubação orgânica traz inúmeros benefícios, sobretudo por ser natural. Os discentes entrevistados consideram que, tanto os fertilizantes químicos quanto os orgânicos, são importantes para suprir as necessidades do solo, contudo os orgânicos se destacaram por serem mais rentáveis e mais sustentáveis.

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Spectral indexes for identification of nitrogen deficiency in maize

Cited by 7 publications

References 2 publications

Calcium Deficiency Diagnosis in Maize Leaves Using Imaging Methods Based on Texture Analysis

Calcium Deficiency Diagnosis in Maize Leaves Using Imaging Methods Based on Texture Analysis

Recent Development and Challenges in Spectroscopy and Machine Vision Technologies for Crop Nitrogen Diagnosis: A Review

Percepções de estudantes do curso técnico em agropecuária sobre o uso de fertilizantes no semiárido

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