Impact of Foliar Application of Zinc and Magnesium Aminochelate on Bean Physiology and Productivity in Ghana
Bibliographic record
Abstract
Foliar application of fertilizers can guarantee nutrient availability to beans, leading to higher yield and seed quality. Different approaches including glycine have been used to improve mineral nutrient status of plants toward safer products and improved human health. However, limited research has been undertaken to understand the response of beans to amino Zn and Mg foliar fertilizer application in Ghana. This study was conducted to investigate the effect of zinc, magnesium, and combined zinc and magnesium foliar fertilizer application on two improved common bean (Phaseolus vulgaris L.) varieties locally referred to as Adoye and Nsroma in the forest (Fumesua) and forest-savannah transition (Akumadan) agro-ecological zones of Ghana during the 2018 and 2019 cropping seasons. The treatments were arranged in split-plot design with the two improved common bean varieties as the main plot, and foliar fertilizer options (zinc, 200 g/ha; magnesium, 224 g/ha; combined zinc and magnesium, 100 g/ha Zn and 112 g/ha Mg) and water spray (control) as the subplot treatments. The zinc and combined zinc and magnesium treatments had similar and significantly ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>P</a:mi> <a:mo>≤</a:mo> <a:mn>0.05</a:mn> </a:math> ) higher plant height of 37.1 cm and 38.7 cm compared to the control and magnesium treatments. The results also showed that chlorophyll content was approximately 15.6% higher in plants treated with zinc plus magnesium compared to the other treatments. Similarly, stomatal conductance was significantly ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>P</c:mi> <c:mo>≤</c:mo> <c:mn>0.05</c:mn> </c:math> ) increased by 35.6% with zinc plus magnesium treatment relative to the other treatments. The improved chlorophyll content and stomatal conductance in those treatments resulted in ∼55.3–80.6% increase in crop biomass and seed yield. Crop performance parameters such as plant height, canopy spread, and chlorophyll content were significantly higher ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>P</e:mi> <e:mo>≤</e:mo> <e:mn>0.05</e:mn> </e:math> ) at Akumadan, resulting in a greater seed yield of 1486.2 kg/ha compared to 1365.3 kg/ha at Fumesua. Combined application of zinc and magnesium appears to be a potential soil improvement strategy for common bean production in tropical soil environment of Ghana.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".