Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.

Lentil (Lens culinaris Medik.) is a popular legume crop in the Mediterranean region, widely grown for its nutritious seeds and improving soil fertility. Lentil yield is a critical and challenging trait for crop genetic improvement because it is influenced by various factors that have detrimental effects on seed yields and seed quality traits. This research was carried out in Italy between 2017 and 2019 to identify high-performing stable genotypes presenting multiple desirable traits and to assess the seed quality of 13 lentil accessions in the field. According to the results of the multi-trait stability index (MTSI), (1) only three accessions (Altamura, Easton, and Caltagirone) fared better in various environmental conditions, and (2) the selected accessions had strength toward seed yield (SY), above-ground biomass (AGB), and 1000-seed weight (THS). The genotype × environment interaction (GEI) effects were highly significant for all traits. During the third growing season, most lentil accessions were sensitive to frost. There was no correlation between lentil seed yield and protein concentration. The MTSI is a useful tool for breeders interested in selecting accessions based on their mean performance and stability, as well as desirable traits and minimum multicollinearity issues.

Quinoa (Chenopodium quinoa Willd.) is one of the most popular emerging food crops in the Andean region. It is tolerant to environmental stresses and characterized by interesting nutritional traits. Thus, it has the potential to contribute to food and nutrition security in marginal environments. In this study, we conducted a systematic review integrated with a bibliometric analysis of cropping practices of quinoa under field conditions. The analysis is based on published data from the literature relating to the period 2000–2020. A total of 33 publications were identified, revealing that scientific research on the agronomic practices and performances of quinoa under field conditions is still limited. Africa, Asia, and Europe were the leading research production sites in this field and together provided over 81% of the total scientific production. There were no papers from the Australian continent. The number of papers screened dealing with tillage and weed control management was very limited. The keyword co-occurrence network analyses revealed that the main topics addressed in the scientific literature related to the effect of “variety” and “deficit irrigation”, followed by “water quality”, “fertilization”, and “sowing date” on seed yield. Results from this study will permit us to identify knowledge gaps and limited collaboration among authors and institutions from different countries. Salinity, sowing density, and sowing date were the agronomic interventions affecting productive response the most.