Newest publications
Comparative analysis of minerals, carotenoids, and tocochromanols in ripe seeds, immature seeds and tepals of bitter and non-bitter quinoa genotypes
(2026) Lauer, Luise Amelie; Kollmar, Marius; Schmöckel, Sandra M.; Frank, Jan
Quinoa (Chenopodium quinoa Willd.) contains high amounts of minerals, carotenoids and vitamin E (tocochromanols), but also antinutrients, such as saponins. Based on their saponin content, quinoa can be classified into “bitter” and “non-bitter” genotypes. Carotenoids (lutein, zeaxanthin, β-carotene, β-cryptoxanthin), vitamin E and saponins share a precursor in their respective biosynthesis pathways. Thus, we investigated whether the downregulation of saponin biosynthesis in non-bitter quinoa affects the contents of minerals and lipid-soluble compounds compared to bitter quinoa. The analytes were quantified in ripe seeds of fifty (23 bitter and 27 non-bitter) quinoa genotypes. A subset of twelve genotypes (6 bitter and 6 non-bitter) was analyzed for carotenoids and tocochromanols in immature seeds and their tepals. Total mineral (8206 mg/kg vs. 8646 mg/kg) and carotenoid contents (314 µg/100 g vs. 242 µg/100 g) did not differ between bitter and non-bitter ripe seeds. However, non-bitter quinoa seeds contained higher lutein and total tocochromanol (driven by tocotrienols) contents than bitter genotypes. Carotenoid and tocochromanol contents in immature seeds and tepals did not differ between phenotypes; tepals had up to 74-fold higher contents than the seeds. In conclusion, the downregulation of saponin biosynthesis in non-bitter quinoa genotypes does not affect the biosynthesis of carotenoids and tocochromanols.
Household decision dynamics and food insecurity: evidence from the one-cow-per-poor-family programme in Rwanda
(2025) Kareem, Olayinka Idowu; Akeremale, Mayokun; Wieck, Christine; Dusingizimana, Theogene; Kamana, Olivier; Chagunda, Mizeck G. G.
Rwanda, like many African countries, endeavours to overcome the food insecurity challenge with different initiatives. One such initiative is the ‘ one-cow-per-poor-family’ programme known as the ‘Girinka Programme’. With the introduction of every cow into the household, there is a resultant change in household bio-economics. Subsequently, some decisions must be made regarding either the consumption or the selling of milk, calves or manure. This study investigates the effect of household decision dynamics within the framework of this programme on food insecurity in Rwanda. The micro-econometrics analytical approach is adopted in the empirical strategy using the household data from the ‘Girinka Programme’ in an ordered probit model. A total of 3000 households were surveyed, and data were collected across 20 districts in Rwanda in 2016 and 2017 and used in the empirical estimations. Our findings affirm the a priori expectation that households’ food insecurity is reduced with additional income sources. Besides, the results indicate that the households acquired and/or used more land by participating in the programme through access to cow’s manure and income earned either by selling the heifer or milk, than before the programme. Also, we find that households with a higher number of calves are more food-secure. The estimations indicate that there is heterogeneity in the level of food insecurity across the districts owing to the decision dynamics of the households across the districts, which lead to different outcomes. The study concludes that participation in the Girinka Programme's intervention significantly reduced food insecurity. To this end, there is a need to establish, as a strategic policy option, the institutionalisation and strengthening of the Girinka Programme for sustainability, which should be affirmed and safeguarded as a social protection policy that directly impacts food insecurity and supports the attainment of sustainable development.
Generic optimization approach of soil hydraulic parameters for site-specific model applications
(2024) Trenz, Jonas; Memic, Emir; Batchelor, William D.; Graeff-Hönninger, Simone
Site-specific crop management is based on the postulate of varying soil and crop requirements in a field. Therefore, a field is separated into homogenous management zones, using available data to adapt management practices environment to maximize productivity and profitability while reducing environmental impacts. Due to advancing sensor technologies, crop growth and yield data on more minor scales are common, but soil data often needs to be more appropriate. Crop growth models have shown promise as a decision support tool for site-specific farming. The Decision Support System for Agrotechnology Transfer (DSSAT) is a widely used point-based model. To overcome the problem of inappropriate soil input data problem, this study introduces an external plug-in program called Soil Profile Optimizer (SPO), which uses the current DSSAT v4.8 to calibrate soil profile parameters on a site-specific level. Developed as an inverse modelling approach, the SPO can calibrate selected soil profile parameters by targeting available in-season plant data. Root Mean Square Error (RMSE) and normalized RMSE as error minimization criteria are used. The SPO was tested and evaluated by comparing different simulation scenarios in a case study of a 3-yr field trial with maize. The scenario with optimized soil profiles, conducted with the SPO, resulted in an R 2 of 0.76 between simulated and observed yield and led to significant improvements compared to the scenario conducted with field scale soil profile information (R 2 0.03). The SPO showed promise in using spatial plant measurements to estimate management zone scale soil parameters required for the DSSAT model.
Editorial: Agroecological practices to enhance resilience of farming systems
(2025) Scordia, Danilo; von Cossel, Moritz; Gresta, Fabio
Abundance and symbiotic efficiency of indigenous rhizobia nodulating faba bean and common bean in southern Ethiopia
(2025) Geremu, Tadele; Abera, Girma; Lemma, Bekele; Rasche, Frank
The symbiotic association between legumes and indigenous rhizobia is crucial for enhancing legume productivity. However, inconsistent results and suboptimal performance of rhizobia inoculation in promoting legume production have been observed. In this regard, we assessed the abundance and symbiotic efficiency of indigenous rhizobia nodulating faba bean and common bean, as well as the soil factors affecting rhizobia abundance in southern Ethiopia. The study also compared the performance of indigenous rhizobia with commercial strains and mineral nitrogen treatment plants. A total of 132 soil samples were collected from barley, wheat, maize, potato, common bean, faba bean, intercropped common bean and maize, enset, and grazing land. Indigenous rhizobia were isolated and enumerated from these samples. Faba bean (FB) and common bean (CB) rhizobia population ranged from 0.0 to 1.7 x 10 4 and 1.7 x 10 1 to 1.7 x 10 7 cells g -1 soil, respectively. Rhizobia populations were significantly influenced by soil pH, EC, OC, TN, CEC, exchangeable acidity, aluminium, and the host crop occurrence. The isolated indigenous rhizobia demonstrated significant potential in enhancing nodulation, shoot dry weight, and TN accumulation in plants. Symbiotic efficiency indices revealed that over 95% of the indigenous rhizobia were effective in nodulation and shoot dry matter accumulation, indicating that naturally occurring rhizobia are efficient and may reduce the need for commercial inoculants in areas with abundant indigenous populations. However, in areas where rhizobia populations are low, strains isolated from faba bean (33FB, 84FB) and common bean (44CB, 102CB), which outperformed commercial strains should be further evaluated. The results suggest that soil rhizobia population levels should be assessed prior to inoculation to optimize nodulation and crop performance. To this end, it is emphasized to evaluate soil rhizobia strains to assess their stability and competitiveness relative to commercial inoculants across different agroecological conditions.