Plant Agronomic Features Can Predict Quality and Field Performance: A Bibliometric Analysis

Plant quality and survival prediction tools are useful when applied in the field in different agricultural sectors. The objectives of this study were to conduct a review and bibliometric analysis of the Dickson Quality Index (DQI) as a key plant quality indicator and with respect to its scientific applications. A third objective was to identify the main morphological and physiological parameters used in plant production research. The methodology and findings of 289 scientific articles were analysed based on the morphological, physiological, and mathematical parameters used as plant quality indicators in research on forest, medicinal, horticultural, aromatic, and ornamental species. During the last 10 years, the number of publications that have used the DQI as a plant quality parameter has increased by 150%, and Brazilian researchers stand out as the most frequent users. Forestry is the discipline where quality parameters and their biometric relationships are most often used to facilitate intensive plant production. Use of the DQI increases the certainty of prediction, selection, and productivity in the plant production chain. The DQI is a robust tool with scientific application and great potential for use in the preselection of plants with high quality standards among a wide range of plant species.

Preliminary Study on the Effect of Nitrogen Fertilisation on Phytochemical Content Quality of Gynura procumbens

The study was carried out to examine the effects of nitrogen (N) fertilisation on phytochemical content quality, to determine types of phytochemicals compositions, and to establish phytochemicals marker compounds in Gynura procumbens. In this two factors study, three stages of harvesting (H) time and three rates of N were laid out according to Randomised Complete Block Design (RCBD). Physiological and biochemical attributes were recorded to exhibit the trend for plant quality. The results showed that, N has affected phytochemical content significantly (p < 0.05) with stronger effect on physiological and biochemical attributes (p < 0.01). The results suggested that 0 and 90 kg/ha N, respectively are highly and least effecting the Photo, Cond, TChlC, TCC, TPrc, TLiC, TPC and TFC.