RESUMO
Cooking time is a crucial determinant of culinary quality of cassava roots and incorporating it into the early stages of breeding selection is vital for breeders. This study aimed to assess the potential of near-infrared spectroscopy (NIRS) in classifying cassava genotypes based on their cooking times. Five cooking times (15, 20, 25, 30, and 40 minutes) were assessed and 888 genotypes evaluated over three crop seasons (2019/2020, 2020/2021, and 2021/2022). Fifteen roots from five plants per plot, featuring diameters ranging from 4 to 7 cm, were randomly chosen for cooking analysis and spectral data collection. Two root samples (15 slices each) per genotype were collected, with the first set aside for spectral data collection, processed, and placed in two petri dishes, while the second set was utilized for cooking assessment. Cooking data were classified into binary and multiclass variables (CT4C and CT6C). Two NIRs devices, the portable QualitySpec® Trek (QST) and the benchtop NIRFlex N-500 were used to collect spectral data. Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. The spectral data were split into a training set (80%) and an external validation set (20%). For binary variables, the classification accuracy for cassava cooking time was notably high ( R C a l 2 ranging from 0.72 to 0.99). Regarding multiclass variables, accuracy remained consistent across classes, models, and NIR instruments (~0.63). However, the KNN model demonstrated slightly superior accuracy in classifying all cooking time classes, except for the CT4C variable (QST) in the NoCook and 25 min classes. Despite the increased complexity associated with binary classification, it remained more efficient, offering higher classification accuracy for samples and facilitating the selection of the most relevant time or variables, such as cooking time ≤ 30 minutes. The accuracy of the optimal scenario for classifying samples with a cooking time of 30 minutes reached R C a l 2 = 0.86 and R V a l 2 = 0.84, with a Kappa value of 0.53. Overall, the models exhibited a robust fit for all cooking times, showcasing the significant potential of NIRs as a high-throughput phenotyping tool for classifying cassava genotypes based on cooking time.
RESUMO
Sweet potato (Ipomoea batatas) is a rustic horticultural crop with high production potential. However, the crop is susceptible to many pests and diseases. The objective of this study was to evaluate 10 genotypes of sweet potato regarding their yield and resistance to soil insects, under Brazilian cerrado soil conditions. Genotypes were selected from the Sweet Potato Germplasm Bank of Embrapa Hortaliças. The experiment was conducted at Água Limpa Farm, belonging to University of Brasilia (UnB), and consisted of a randomized block design, with 10 treatments (genotypes), 10 plants per plot, and four replications. The following traits were analyzed: number of perforations per root, incidence of roots injured by insects, plant resistance degree, root shape, total and marketable root yields, root peel color, root pulp color, pulp total soluble solids, pulp titratable acidity, pulp TSS/TA ratio, pulp moisture, and pulp starch yield. Genotype CNPH 53 (26.78 t ha-1) presented total root yield greater than the commercial variety Brazlândia Rosada (17.54 t ha-1). Genotype Santa Sofia (11.77 t ha-1) and Brazlândia (13.5 t ha-1) had similar marketable root yields. CNPH 53 showed the best agronomic performance, exhibiting moderate susceptibility to soil insects and root shape meeting the market standards. It also had low pulp TA (2.53%); high pulp TSS (12.25 °Brix) and pulp TSS/AT ratio (4.24); pulp moisture content close to 70%; and the highest pulp starch content (11.98%). The traits number of perforations per root, root shape, and pulp TA presented heritability values close to 70%. Marketable root yield, pulp moisture, and pulp starch content demonstrated heritability values greater than 90% and CVG/CVE greater than 1
A batata-doce (Ipomoea batatas) é uma hortícola rústica e de elevado potencial produtivo. No entanto, ainda é suscetível a grande número de pragas e doenças. O objetivo deste trabalho foi avaliar dez genótipos de batata-doce quanto à produtividade e resistência a insetos de solo nas condições de solo do cerrado Brasileiro. Os genótipos avaliados foram selecionados do Banco de Germoplasma da Embrapa Hortaliças. O experimento foi conduzido na Fazenda Água Limpa da Universidade de Brasília (UnB) utilizando delineamento experimental de blocos casualizados, com 10 tratamentos, 4 repetições e 10 plantas de batata-doce por parcela. As características avaliadas foram: número de furos por raiz, incidência de danos causados por insetos, grau de resistência da planta, formato de raiz, cor da casca da raiz, cor da polpa da raiz, produtividade total e comercial de raiz, e teor de sólidos solúveis totais (SST), acidez total titulável (AT), STT/AT, rendimento de amido e umidade da polpa. O genótipo CNPH 53 apresentou produtividade total (26,78 t ha-1) superior à variedade comercial Brazlândia Rosada (17,54 t ha-1). O genótipo Santa Sofia obteve produtividade comercial (11,77 t ha-1) próxima à variedade Brazlândia Rosada (13,75 t ha-1). O genótipo CNPH 53 apresentou o melhor desempenho agronômico, exibindo suscetibilidade moderada aos insetos de solo e formato de raiz dentro dos padrões comerciais. Apresentou também baixa acidez (2,53%); alto teor de sólidos solúveis (12,25 °Brix) e de ratio (4,24); teor de umidade da polpa próximo a 70% e maior teor de amido na polpa (11,98%). As características número de furos, formato e acidez apresentaram valores de herdabilidade próximos de 70%. A produtividade comercial, umidade e amido da polpa demonstraram valores de herdabilidade acima de 90% e CVg/CVe maior que 1