Improving the efficiency of phytoremediation using electrically charged plant and chelating agents
In: Environmental science and pollution research: ESPR, Band 23, Heft 3, S. 2479-2486
ISSN: 1614-7499
6 Ergebnisse
Sortierung:
In: Environmental science and pollution research: ESPR, Band 23, Heft 3, S. 2479-2486
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 28, Heft 4, S. 4845-4856
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 24, Heft 34, S. 26485-26496
ISSN: 1614-7499
In: Environmental science and pollution research: ESPR, Band 30, Heft 53, S. 114166-114182
ISSN: 1614-7499
AbstractManaging the nutritional status of strawberry plants is critical for optimizing yield. This study evaluated the potential of hyperspectral imaging (400–1,000 nm) to estimate nitrogen (N), phosphorus (P), potassium (K), and calcium (Ca) concentrations in strawberry leaves, flowers, unripe fruit, and ripe fruit and to predict plant yield. Partial least squares regression (PLSR) models were developed to estimate nutrient concentrations. The determination coefficient of prediction (R2P) and ratio of performance to deviation (RPD) were used to evaluate prediction accuracy, which often proved to be greater for leaves, flowers, and unripe fruit than for ripe fruit. The prediction accuracies for N concentration were R2P = 0.64, 0.60, 0.81, and 0.30, and RPD = 1.64, 1.59, 2.64, and 1.31, for leaves, flowers, unripe fruit, and ripe fruit, respectively. Prediction accuracies for Ca concentrations were R2P = 0.70, 0.62, 0.61, and 0.03, and RPD = 1.77, 1.63, 1.60, and 1.15, for the same respective plant parts. Yield and fruit mass only had significant linear relationships with the Difference Vegetation Index (R2 = 0.256 and 0.266, respectively) among the eleven vegetation indices tested. Hyperspectral imaging showed potential for estimating nutrient status in strawberry crops. This technology will assist growers to make rapid nutrient-management decisions, allowing for optimal yield and quality.
In: Computers and electronics in agriculture: COMPAG online ; an international journal, Band 224, S. 109209
ISSN: 1872-7107
In: Computers and Electronics in Agriculture, Band 151, S. 492-500