https://repositorio.ifgoiano.edu.br/handle/prefix/148 Wed, 02 Sep 2026 12:35:07 GMT 2026-09-02T12:35:07Z http://repositorio.ifgoiano.edu.br:80/retrieve/216/22.jpg https://repositorio.ifgoiano.edu.br/handle/prefix/148 https://repositorio.ifgoiano.edu.br/handle/prefix/6944 Título: ESTUDO FISIOLÓGICO, MORFOLÓGICO E QUÍMICO DA Stachys byzantina (K. KOCH) SOB DIFERENTES ESPECTROS DE LUZ Autor(es): Gonçalves, Rute Costa de Campos Primeiro Orientador: Megguer, Clarice Aparecida Primeiro Membro da Banca: Ribeiro, Antônio Carlos Chaves Segundo Membro da Banca: Moreira, Marialva Alvarenga Abstract: Lamb's ear (Stachys byzantina K. Koch) is a Non-Conventional Edible Plants that has attracted increasing interest due to its nutritional, functional, and medicinal potential, associated with the presence of essential nutrients and bioactive compounds with high antioxidant activity. Among the environmental factors that influence plant quality, light plays a fundamental role in regulating growth, photosynthesis, and the biosynthesis of secondary metabolites, potentially promoting an increase in the production of phenolic compounds, flavonoids, and other antioxidant substances of interest for food and human health. In this context, this study aimed to evaluate the development of Stachys byzantina cultivated under controlled environment and exposed to different light spectra, as well as to investigate the effects of these spectra on physiological, morphological, and chemical characteristics of the species. The results showed that light spectral quality significantly influences photosynthetic performance and plant metabolism, promoting distinct responses among treatments and showing potential to modulate the synthesis of bioactive compounds. In general, the use of artificial lighting in indoor cultivation systems proved to be a promising strategy to optimize the production and quality of Stachys byzantina, favoring not only its growth but also the obtaining of products with higher functional and antioxidant value. Thus, the study contributes to the valorization of Non-Conventional Edible Plants and expands the prospects of its use as a functional food and a source of bioactive compounds for different applications. Editor: Instituto Federal Goiano Tipo: Dissertação Mon, 29 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6944 2026-06-29T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6879 Título: MANEJO DO COMPLEXO DE ENFEZAMENTOS DO MILHO DOCE (Zea mays L.) ATRAVÉS DE NUTRIÇÃO FOLIAR Autor(es): Fátima, Isabela Gonçalves de Primeiro Orientador: Trogello, Emerson Abstract: Corn is the world’s leading cereal crop in terms of cultivation and includes several specialty varieties, among which sweet corn stands out due to its high market potential. The corn stunt disease complex is one of the major challenges affecting this crop and can be classified into red stunt and pale yellow stunt, both of which cause significant yield losses. These are systemic diseases caused by mollicutes that invade and colonize the vascular tissues, reducing the growth and reproductive capacity of affected plants. Therefore, the adoption of integrated disease management practices is essential to improve crop quality. The present study aimed to evaluate the influence of micronutrient management on the corn stunt disease complex in sweet corn (Zea mays L.), seeking to reduce disease-related losses. The experiment was conducted in Morrinhos, Goiás, Brazil, from March to June 2025 under center-pivot irrigation. The sweet corn hybrid used was GSS0227, and the nutrients were supplied through the commercial products Dueto (77.7 g L⁻¹ Mn and 77.7 g L⁻¹ Zn), Boro Pro (130 g L⁻¹ B), and Buddy (47.25 g L⁻¹ Cu). Eight treatments were evaluated, consisting of the products applied individually, in combination, and an untreated control. Two applications were carried out for each treatment in association with the grower’s conventional management practices. The evaluated variables were Total Weight, Ear Weight, Grain Weight, Soluble Solids (°Brix), and Total Chlorophyll. The results showed no statistically significant differences among treatments for any of the evaluated variables. Therefore, the application of micronutrients was not directly associated with reducing the damage caused by the corn stunt disease complex in sweet corn plants. Editor: Instituto Federal Goiano Tipo: Dissertação Fri, 12 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6879 2026-06-12T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6779 Título: INTERAÇÃO DE FLUOPIRAM E Trichoderma harzianum NO CONTROLE DE PATÓGENOS DE SOLO NAS CULTURAS DO TOMATEIRO E MELOEIRO Autor(es): Silva, Juliana Nascimento Primeiro Orientador: Pontes, Nadson de Carvalho Abstract: Soilborne pathogens such as Rhizoctonia solani and Meloidogyne spp. are major phytosanitary constraints in vegetable crops, impairing root system development, plant establishment, and crop productivity. In this context, this dissertation aimed to evaluate the potential of integrated soilborne pathogen management through the association of the nematicide fluopyram with the biological control agent Trichoderma harzianum ESALQ-1306 in tomato and melon crops. Field experiments were carried out in a randomized complete block design, with treatments involving single and combined inoculations of R. solani and Meloidogyne javanica in tomato, and of R. solani and Meloidogyne incognita in melon, in the presence or absence of fluopyram and T. harzianum. In tomato, the evaluated variables were root colonization frequency by T. harzianum, R. solani incidence, gall index, egg and second-stage juvenile populations, fresh root mass, and yield. In melon, in addition to root colonization and R. solani incidence, nematological indices, fresh root mass, and yield were assessed. In both crops, T. harzianum showed high root colonization frequency throughout the crop cycle, even in the presence of fluopyram, demonstrating compatibility between the chemical and biological strategies. Treatments containing fluopyram and/or T. harzianum reduced R. solani incidence and nematological indices compared with the infested controls, with more consistent responses observed for Meloidogyne spp. In tomato, the association between fluopyram and T. harzianum was effective in reducing gall index and final egg and juvenile populations, while maintaining yield, especially under coinoculation conditions. In melon, the treatments also promoted suppression of R. solani and Meloidogyne spp., with emphasis on the association between fluopyram and T. harzianum under coinoculation, which resulted in the highest yield. Overall, the results demonstrate that the combined use of fluopyram and T. harzianum ESALQ-1306 is a promising strategy to integrate the management of soilborne pathogens in vegetable crops, contributing to the reduction of fungal and nematode damage and supporting more sustainable and efficient production systems. Editor: Instituto Federal Goiano Tipo: Dissertação Wed, 18 Mar 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6779 2026-03-18T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6635 Título: VISÃO COMPUTACIONAL E INTELIGÊNCIA ARTIFICIAL PARA MEDIÇÃO DO MESOCARPO DE TOMATES Autor(es): Souza, João Carlos Soares Primeiro Orientador: Silva, Alexandre Carvalho Abstract: Advances in computer vision and artificial intelligence have driven innovation in agriculture, particularly in automated product inspection. In the context of Agro 4.0, standardized systems are crucial for optimizing processes and ensuring objective analyses compared to conventional methods. This study investigates the application of Computer Vision and Artificial Intelligence in measuring the mesocarp thickness of tomatoes (Solanum lycopersicum L.), an essential parameter for industrial and commercial standardization. To this end, a low-cost integrated hardware and software system was developed, based on digital image capture and processing. Statistical validation compared automated methods with physical reference measurements. The results demonstrated that the Artificial Intelligence (AI) model outperformed the conventional Computer Vision (CV) technique, achieving an accuracy of 90.76% (compared to 86.88% for CV) and a Mean Absolute Error (MAE) of 0.608 mm. The system achieved an optimized inference time of approximately 6 seconds per sample. It is concluded that the automation tool demonstrates technical feasibility and high reliability, offering promising prospects for realtime classification, selection of new varieties, and the improvement of phenotypic evaluation of fruits in vegetable farming and industry. Editor: Instituto Federal Goiano Tipo: Dissertação Wed, 01 Apr 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6635 2026-04-01T00:00:00Z