Evaluation of the productivity of soil amended with different animal wastes in an acid ultisol at Abakaliki, Southeast Nigeria

Nwite, J. N.; Okolo, Chukwuebuka Christopher; Ezeaku, PI

doi:10.5897/sre12.554

Cited by 5 publications

(6 citation statements)

References 13 publications

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“…This corroborates the findings of Nwite (2013) that individual productivity indicators influenced productivity index in predictions. Significantly higher correlation coefficient obtained between the individual productivity indicator and calculated productivity index tends to suggest that there was synergy among the productivity indicators in promoting prediction of grain yields of maize.…”

Section: Discussionsupporting

confidence: 91%

Predicting grain yields of maize in an Ultisol amended with organic wastes using modified productivity index in Abakaliki, Southeastern Nigeria

Nwite¹

2016

Afr. J. Agric. Res.

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Predicting grain yields of maize in soil amended with organic wastes using modified productivity index was studied for three cropping seasons. Soil samples for determination of productivity index and individual productivity indicators for prediction of grain yields of maize were collected from 0 15, 15-30, 30-45, and 45-60 cm depths. Ascribed sufficiency value was assigned to each productivity indicator of bulk density, available water capacity (AWC) pH and depth of rooting zone (DRZ) which were used to calculate productivity index (PI) for each amendment. Highest predictions of grain yields of maize were obtained for sawdust PI=0.39 and grain yield of maize-2.30 t ha -1 in 2013 and burnt rice mill waste PI=0.39 and grain yield of maize=2.30 t ha -1 and PI=0.37 and grain yield of maize=2.25 t ha -1 in 2014 and 2015 cropping seasons, respectively. The prediction of organic wastes for grain yields of maize is as follows BRMW>SD>URMW>C. Calculated productivity index (CPI) predicted highly significant (r=0.92 and r 2 =0.84) grain yields of maize. Bulk density more than AWC and pH predicted highly significant (r=0.95 and r 2 = 0.89) grain yield of maize.

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Section: Discussionsupporting

confidence: 91%

Predicting grain yields of maize in an Ultisol amended with organic wastes using modified productivity index in Abakaliki, Southeastern Nigeria

Nwite¹

2016

Afr. J. Agric. Res.

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“…These data suggest that differences in crop yield can be represented by productivity indices values. This finding agreed with [3] and [39] who found that corn yield increased with the increase of PI and decreased with the decrease of it. The results concluded that as PI, PIm and RI values decreased a general decline in grain yield of rice is recorded.…”

Section: Individual Productivity Index and Grain Yield Of Ricesupporting

confidence: 93%

“…Floodplains have reported to be fragile ecosystems and their conversion to cropland may result in severe ecological and environmental deterioration and degradation if not appropriately done [1]. However, increasing demand for food as a result of rapid population expansion in Nigeria necessitates a substantial extension of croplands into some hitherto uncultivated wetlands/floodplains otherwise considered as marginal lands for rain-fed agriculture [2,3]. Basic soil resource information a pre-requisite for planning sustainable agriculture [4,1] and sustainable agriculture requires both direct and indirect knowledge of the capability and nutrient status of the soils to be utilized [5].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Effectiveness of Some Productivity Models on Floodplain Soils of Wukari Area, Northern Guinea Savanna, Nigeria

Gani

Ammar

Agber

et al. 2020

AJSSPN

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A study on quantifying the productivity of Wukari flood plain soils using Neill’s Productivity Index (PI), Modified Neill’s Productivity Index (PIm) and Riquier Productivity Index (RI) was carried out. The applicability and validity of the productivity index models were determined using rice as a test crop. Result showed significant relationships with coefficients of determination (R2) of 0.7158, 0.7204 and 0.8778 found between grain yield of rice (Y) and PI, PIm and RI values respectively. The highest and the lowest grain yield of rice to a reasonable extent correspond to the higher and the lower productivity index values, respectively. Higher productivity indices explained higher mean grain yield of rice. The productivity indices values decreased with the decrease in grain yield. The grain yield of grain followed productivity index predictions and are hereby recommended as tools of soil productivity assessment in the study area.

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“…Promoting the application of the cattle manure currently being used as fuel for cooking to the fields seems to be a feasible strategy. Application of manure improves physical and chemical properties of soils (Nwite et al 2013;Okenmuo et al 2018). However, a study by Corral-Nunez et al (2014) in the same area reported that applying manure alone is not sufficient to off-set the declining trend, due to limited availability and its various alternative uses.…”

Section: Full Nutrient Balance At Field Levelmentioning

confidence: 99%

Nutrient Balance of Farming Systems in Tigray, Northern Ethiopia

Gebresamuel

Opazo-Salazar

Corral-Núnez

et al. 2020

J Soil Sci Plant Nutr

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The purpose of this study was to explore how soil fertility management and farm nutrient balances varied across socio-economic groups in northern Ethiopia. Field surveys were carried out in 32 farms in Tigray, northern Ethiopia using different socioeconomic groups, viz.: model/non model and female/male farmers. The nutrient input flows and output flows were monitored and analysed using Monitoring for Quality Improvement (MonQI) toolbox. Results of the study showed that average nitrogen (N), phosphorus (P) and potassium (K) balances in the highlands were − 30.8, 4.08 and − 42.75 kg ha −1 , respectively while in the lowland the average nutrient balance were − 19.5, 2.09 and − 15.35 kg ha −1 for N, P and K, respectively. All farms had negative N and K nutrient balances, with lower negative N and K balance recorded in highlands than the lowlands. The reported values account about 0.6% and 2.7% of the total soil N and K pools in the highland and 0.3% and 0.8% in the lowland, respectively. Nutrient depletion rates in the highlands were 0.6% year −1 and 2.7% year −1 for N and K, respectively while for the lowlands the rates were 1.5% year −1 and 3.4% year −1 for N and K, respectively. Depletion rates were higher in the lowlands than highlands due to monocropping, crop residue removal and absence of soil water conservation. Most farms belonging to model farmers of both categories and non-model male farmers show more negative nutrient balance. We conclude that socio-economic status and being model farmers had less role in soil fertility maintenance. However, the more positive balance in female-headed households points to the need for adequate attention and support for the female-headed households. This study underscores the need for sustainable nutrient management. More so, agricultural policy should target female-headed households to help reduce the productivity gap between male-headed households and female-headed households.

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Evaluation of the productivity of soil amended with different animal wastes in an acid ultisol at Abakaliki, Southeast Nigeria

Cited by 5 publications

References 13 publications

Predicting grain yields of maize in an Ultisol amended with organic wastes using modified productivity index in Abakaliki, Southeastern Nigeria

Predicting grain yields of maize in an Ultisol amended with organic wastes using modified productivity index in Abakaliki, Southeastern Nigeria

Evaluating the Effectiveness of Some Productivity Models on Floodplain Soils of Wukari Area, Northern Guinea Savanna, Nigeria

Nutrient Balance of Farming Systems in Tigray, Northern Ethiopia

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