In Brazil, there is already a recommendation for the production of cassava seed-cuttings for the production of seedlings originated from micropropagation, which may be extended for the production of seedlings obtained from cuttings from healthy plant stems, in order to avoid the spread of diseases. Therefore, it is essential to establish adequate cultivation substrates of easy acquisition which may stimulate the growth of seedlings, both to reduce the nursery period, as well as the seedling’s production costs. The objective of this work was to evaluate the effect of organic fertilizers made from bovine and goat manures, and tree pruning residues, to produce seedlings of three cassava varieties. The plots were set in a completely randomized design, with six replicates. The treatments consisted of three cassava genotypes (BRS Formosa, BRS Tapioqueira and BRS Kiriris) and five proportions of organic fertilizer: soil (0: 100, 20:80, 40:60, 60:40 and 80:20). The evaluations were performed 30 and 45 days after planting (DAP). There were isolated effects for shoot dry mass, total dry mass, leaf area and number of leaves. Interactions were verified for root length, chlorophyll a and total chlorophyll index, root dry mass and shoot dry mas/root dry mass ratio 45 DAP. The organic fertilizer stimulated the initial growth of cassava seedlings in the three varieties studied in the proportion of 50% of organic fertilizer and 50% of Latosol. Varieties BRS Formosa and BRS Kiriris showed the highest Dickson Quality Scores. Genotypes reacted efficiently to organic fertilization and can be propagated on these easily acquisition cultivation substrates.

Cassava (Manihot esculenta Crantz) starch consists of amylopectin and amylose, with its properties determined by the proportion of these two polymers. Waxy starches contain at least 95% amylopectin. In the food industry, waxy starches are advantageous, with pastes that are more stable towards retrogradation, while high-amylose starches are used as resistant starches. This study aimed to associate near-infrared spectrophotometry (NIRS) spectra with the waxy phenotype in cassava seeds and develop an accurate classification model for indirect selection of plants. A total of 1127 F2 seeds were obtained from controlled crosses performed between 77 F1 genotypes (wild-type, Wx_). Seeds were individually identified, and spectral data were obtained via NIRS using a benchtop NIRFlex N-500 and a portable SCiO device spectrometer. Four classification models were assessed for waxy cassava genotype identification: k-nearest neighbor algorithm (KNN), C5.0 decision tree (CDT), parallel random forest (parRF), and eXtreme Gradient Boosting (XGB). Spectral data were divided between a training set (80%) and a testing set (20%). The accuracy, based on NIRFlex N-500 spectral data, ranged from 0.86 (parRF) to 0.92 (XGB). The Kappa index displayed a similar trend as the accuracy, considering the lowest value for the parRF method (0.39) and the highest value for XGB (0.71). For the SCiO device, the accuracy (0.88−0.89) was similar among the four models evaluated. However, the Kappa index was lower than that of the NIRFlex N-500, and this index ranged from 0 (parRF) to 0.16 (KNN and CDT). Therefore, despite the high accuracy these last models are incapable of correctly classifying waxy and non-waxy clones based on the SCiO device spectra. A confusion matrix was performed to demonstrate the classification model results in the testing set. For both NIRS, the models were efficient in classifying non-waxy clones, with values ranging from 96−100%. However, the NIRS differed in the potential to predict waxy genotype class. For the NIRFlex N-500, the percentage ranged from 30% (parRF) to 70% (XGB). In general, the models tended to classify waxy genotypes as non-waxy, mainly SCiO. Therefore, the use of NIRS can perform early selection of cassava seeds with a waxy phenotype.