Agro-morphological and biochemical responses of quinoa (Chenopodium quinoa Willd. var: ICBA-Q5) to organic amendments under various salinity conditions

Abstract

In the Sahara Desert, due to drought and salinity and poor soil fertility, very limited crop choice is available for the farmers to grow crops. Quinoa (Chenopodium quinoa Willd.) has shown promising under such conditions in the South of Morocco, a true representative site of Sahara Desert. Soil organic amendments have the potential to minimize negative effects of soil salinity and improve crop production. Thus, this study aimed to elucidate the impact of nine organic amendments on quinoa (var. ICBA-Q5) growth, productivity, and biochemical parameters under saline irrigation water application (4, 12, and 20 dS·m-1). Results of the experiment indicate a significant effect of organic amendments on major agro-morphological and productivity parameters. Biomass and seed yield tends to decrease with the rise of salinity level, and organic amendments have improved productivity compared to the non-treated control. However, salinity stress alleviation was assessed by determining pigments concentration, proline content, phenolic compounds, and antioxidant activity. Therefore, the action of organic amendments varies from one level of salinity to another. Furthermore, a remarkably significant decrease in total saponin content was reached due to the application of amendments even at high saline conditions (20 dS·m-1). The results demonstrate the possibility of enhancing the productivity of quinoa as an alternative food crop under salinity conditions by using organic amendments and improving the quality of grains (saponin reduction) during the pre-industrialization process.

Quinoa–Olive Agroforestry System Assessment in Semi-Arid Environments: Performance of an Innovative System

“…However, such relationships were analyzed in other pedoclimatic conditions. A positive correlation between grain yield, dry matter, and crop water productivity has been reported [62,78]. This analysis revealed more significant positive correlations (55%) in AFS than in SCS (45%) between the monitored parameters.…”