ABSTRACT The planting of unconventional vegetables has increased in Brazil. This is mainly due to the demand of nutritionally rich foods grown in sustainable crops. In this scenario, ora-pro-nobis stands out, as, although being part of the meal of large part of the Brazilian population, it has been cultivated despite the lack of scientific knowledge. Thus, this study aimed to adjust a leaf area estimation model for ora-pro-nobis, using the measurements of the leaves. For the model adjustment and validation, 4000 leaves were collected in four different genotypes, being 1000 in each of them. The regression models were adjusted using 2000 independent and random observations, using 500 leaves per genotype. Thus, the observed leaf area was studied as a linear function of the dimensions of the leaf blade: length (L), width (W) and product (LW). The remaining 2000 observations, also 500 per separate genotype, were used only in the statistical validation study. The adjusted allometric model based on the product (LW) proved to be precise and accurate for estimating the leaf area of ora-pro-nobis, being applicable to any of the four genotypes analyzed regardless of the leaf size: L A ^ L W = 0.9294 + 0.6815 x L W.

RESUMO O plantio de hortaliças não convencionais tem ganhado espaço no cenário nacional, o que se relaciona, principalmente, com a procura por alimentos nutricionalmente ricos advindos de cultivos sustentáveis. Neste cenário, destaca-se o ora-pro-nobis, que embora presente na mesa de muitos brasileiros, tem sido cultivado frente a escassez de conhecimento científico sobre a espécie. Assim, objetivou-se ajustar um modelo de estimação de área foliar (AF) em ora-pro-nobis, usando medidas de suas folhas. Para o ajuste dos modelos e validação do selecionado coletou-se 4000 folhas em quatro genótipos distintos, sendo 1000 em cada um deles. Os modelos de regressão foram ajustados a partir de 2000 observações independes e aleatórias, utilizando-se 500 folhas por genótipo. Deste modo, a área foliar observada foi estudada como função linear das dimensões do limbo foliar: comprimento (C), largura (L) e do produto (CL). As demais 2000 observações, também 500 por genótipo em separado, foram utilizadas apenas no estudo de validação estatística. O modelo alométrico ajustado baseado no produto (CL) mostrou-se preciso e acurado para a estimação da área foliar em ora-pro-nobis, sendo aplicável a qualquer um dos quatro genótipos analisados independentemente do tamanho de suas folhas: A F ^ C L = 0,9294 + 0,6815 x C L.

ABSTRACT Yacon (Smallanthus sonchifolius [Poepp.] H. Rob., Asteraceae) is an Andean plant being explored as a functional food, due to high concentrations of fructooligosaccharides (FOS), a natural sweetener capable of reducing blood lipids and glucose levels, supporting prevention of chronic diseases, such as diabetes. Yacon commercial production is still being established, thus cropping practices and their impact on profitability are yet poorly explained. Improved planting recommendations are demanded, as it affects crop yield. In this background, a field trial was conducted to determine row spacing and plant populations for yacon production in tropical highland areas. The experimental design was a randomized complete block, in a split-plot scheme, where blocks were three row spacings (0.8, 1.0 and 1.2 m) and subplots covered three spacings between plants (0.4, 0.5 and 0.6 m), with four replicates. At harvest time, evaluations on accumulation of dry mass in the plant and tuber root production data (number, weight, total productivity, and per class) were made. Profitability indicators were estimated (gross income, operational profit, and benefit-cost ratio). Data suggest productive and economic variations among tested planting configurations, as an example higher productivity (31.5 t ha-1) and positive benefit-cost ratio (2.51) when using 1.0 m between rows and 0.4 m between plants for the conditions tested. These results point out the prospect to select better crop management practices for yacon, cutting costs, and increasing yield. Another key find was yacon’s capacity to overcome intense drought and temperature stress, not previously documented for this crop. Therefore, yacon is a new crop with potential to boost farming income through crop diversification.