Diagnóstico nutricional da rúcula para nitrogênio com processamento digital de imagens
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Data
2021-10-25
Autores
Silva, Paulo Henrique Soares [UNESP]
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Universidade Estadual Paulista (Unesp)
Resumo
A rúcula é a segunda hortaliça folhosa mais cultivada em hidroponia. Porém, há raros estudos sobre a adequação da concentração do nitrogênio (N) na solução nutritiva. Este nutriente é o segundo mais acumulado pela rúcula e afeta sobremaneira o crescimento, produtividade e qualidade desta hortaliça. Técnicas computacionais têm sido utilizadas na tentativa de avaliar o estado nutricional de plantas e predizer, precocemente, a deficiência nutricional. O objetivo do trabalho foi avaliar concentrações de N (79,2; 118,8; 158,4 e 237,6 mg L- 1), presentes na solução nutritiva, no teor de N foliar, crescimento, produtividade, qualidade e a viabilidade do uso de imagens digitais na identificação precoce da deficiência de N em rúcula 'Folha Larga'. O experimento foi realizado em hidroponia, em delineamento experimental de blocos casualizados, com cinco repetições. No estudo da técnica computacional, aplicou-se o processamento digital de imagem (PDI) nas folhas novas, intermediárias e velhas, aos 11, 14, 17 e 20 dias após o início da Fase III de crescimento. O maior teor de nitrogênio foliar foi de 28,2 g kg-1, alcançado com 186 mg L-1 de N na solução nutritiva. O crescimento (número de folhas, área foliar, massa seca) e produtividade da rúcula foram máximos quando se usou a maior concentração de N na solução nutritiva. O teor de nitrato (qualidade da rúcula) foi máximo com 210,2 mg L-1 de N (3527,70 mg kg-1), mas na faixa aceitável para hortaliças. Assim, com base no crescimento, produtividade e qualidade da rúcula, recomenda-se o seu cultivo com 237,6 mg L-1 de N na solução nutritiva. O PDI não foi capaz de identificar a deficiência de N precocemente. Os melhores resultados do PDI foram verificados nas folhas velhas, aos 20 dias na Fase III.
The arugula is the second most widely cultivated leafy vegetable in hydroponics. However, there are few studies on the adequacy of nitrogen (N) concentration in the nutrient solution. This nutrient is the second most accumulated by arugula, and greatly affects the growth, productivity, and quality of this vegetable. Computational techniques have been used in an attempt to assess the nutritional status of plants and to predict, early, nutritional deficiency. The objective of the study was to evaluate N (79.2; 118.8; 158.4 e 237.6 mg L-1of N) in nutrient solution on leaf N content, growth, yield, quality and the feasibility of using digital images for early identification of N deficiency in arugula 'Folha larga'.The experiment was conducted in hydroponics, in a randomized block design, with five repetitions.In the computational technique study, digital image processing (DIP) was applied to the young, intermediate, and old leaves at 11, 14, 17, and 20 days after the onset of Phase III growth. The highest leaf nitrogen content was 28.2 g kg-1, reached with 186 mg L-1 in the nutrient solution. The growth (number of leaves, leaf area, dry mass) and productivity of arugula were maximum when the highest concentration of N in the nutrient solution was used. The nitrate content (arugula quality) was maximum at 210.2 mg L-1 (3527,70 mg kg-1), but in the acceptable range for vegetables. Thus, based on the growth, productivity, and quality of arugula, it is recommended to grow it with 237.6 mg L-1 in the nutrient solution. The PDI was not able to identify N deficiency early. The best PDI results were seen in the old leaves at 20 days in Phase III.
The arugula is the second most widely cultivated leafy vegetable in hydroponics. However, there are few studies on the adequacy of nitrogen (N) concentration in the nutrient solution. This nutrient is the second most accumulated by arugula, and greatly affects the growth, productivity, and quality of this vegetable. Computational techniques have been used in an attempt to assess the nutritional status of plants and to predict, early, nutritional deficiency. The objective of the study was to evaluate N (79.2; 118.8; 158.4 e 237.6 mg L-1of N) in nutrient solution on leaf N content, growth, yield, quality and the feasibility of using digital images for early identification of N deficiency in arugula 'Folha larga'.The experiment was conducted in hydroponics, in a randomized block design, with five repetitions.In the computational technique study, digital image processing (DIP) was applied to the young, intermediate, and old leaves at 11, 14, 17, and 20 days after the onset of Phase III growth. The highest leaf nitrogen content was 28.2 g kg-1, reached with 186 mg L-1 in the nutrient solution. The growth (number of leaves, leaf area, dry mass) and productivity of arugula were maximum when the highest concentration of N in the nutrient solution was used. The nitrate content (arugula quality) was maximum at 210.2 mg L-1 (3527,70 mg kg-1), but in the acceptable range for vegetables. Thus, based on the growth, productivity, and quality of arugula, it is recommended to grow it with 237.6 mg L-1 in the nutrient solution. The PDI was not able to identify N deficiency early. The best PDI results were seen in the old leaves at 20 days in Phase III.
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Palavras-chave
Plantas nutrição, Horticultura, Plantas efeitos do nitrogênio, Inteligência artificial, Visão artificial, Horticultural products