尼日利亚南部翁多州沥青土中秋葵产量模型研究

Imoukhuede Oladunni Bimpe, Fasinmirin Johnson Toyin, Olayanju Gbenga Moses
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摘要

本研究连续两个生长季节(2020年和2021年)在Ondo州南部irelle选择群落(Loda、Lofo和Legbogbo)的沥青土中调查了秋葵(Abelmoschus esculentus L. Moench)的生长和产量响应。Legbogbo的沥青含量非常低,作为对照。质地类为砂质壤土,土壤呈酸性。在深度0 ~ 100 cm处挖3个土壤剖面坑,每隔10 cm采集部分土壤样品,移至土壤实验室进行宏量元素和微量元素的化学浓度分析。重金属含量最高的地区是罗达。更重要的是,在Legbogbo站点(对照)和Lofo站点的某些情况下,沥青浓度最低。研究结果表明,两者存在显著差异(P <各深度位置间重金属值差异0.05)。不同地点的结果也表明,土壤深度和位置具有显著性(P <0.05)对土壤重金属的主要影响。土壤重金属浓度低于允许的极限值,表明研究区重金属浓度可能没有对秋葵的生长和产量产生负面影响。试验两季各地点的所有农艺参数均为Legbogbo>Lofo>Loda。秋葵体重0公斤。Loda站点在2020和2021生长季的豆荚产量均为ha-1,而Legbogbo站点在两个生长季的果实产量均最高。利用逐步回归模型建立秋葵产量预测模型,发现在P <下,秋葵产量与钾含量呈显著相关(r2 = 0.95);0.05和磷(r2 = 0.99) (P <0.01)。
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Yield Modeling of Okra (Abelmoschus esculentus L. moench) in Bituminous Soils of Southern Ondo State, Nigeria
This study investigated the growth and yield response of okra (Abelmoschus esculentus L. Moench) in bituminous soils of selected communities (Loda, Lofo and Legbogbo) in Irele, southern Ondo State for two consecutive growing seasons (2020 and 2021). The Legbogbo site, which of very low bitumen, serves as the control. The textural class is sandy loam and the soil is acidic. Some samples of soil were collected from three dug soil profile pit at depths 0-100 cm at an interval of 10 cm and moved to the soil laboratory for the analysis of the chemical concentrations of macro and trace elements. The highest value of the heavy metal was recorded at Loda. More so, the least amount of the bitumen concentration was recorded at Legbogbo site (control) and in some cases at Lofo site. Result from the study showed that there is significant difference (P < 0.05) in the values of the heavy metals among the location at all depths. The results from various locations also showed that the soil depth and location were significant (P < 0.05) in their main effects on the soil heavy metals. It was observed that the heavy metal concentration of soil was lower than the permissible limit, an indication that the concentration of heavy metals of the study areas may not have negatively influenced the growth and yield of okra. All agronomic parameters in all locations during the two seasons of experiment were in the way of Legbogbo>Lofo>Loda. Okra had 0 kg.ha-1 pod yield at the Loda site at both 2020 and 2021 growing seasons, while Legbogbo had the greatest fruit yield for both seasons. Okra yield prediction model was developed using the stepwise regression model and it was observed that Okra yield significantly correlated to potassium (r2 = 0.95) at P < 0.05 and phosphorus (r2 = 0.99) (P < 0.01).
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