Spatial relationships between soil attributes and corn yield in no-tillage system

Rodrigues, Marcos Sales; Corá, José Eduardo; Fernandes, Carolina

doi:10.1590/s0100-06832012000200029

Cited by 24 publications

(26 citation statements)

References 22 publications

(34 reference statements)

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“…This was in agreement with the study carried out by Rodrigues et al 2012 who found out that a positive correlation between maize yield and K contents in soils. Moreover, Montezano et al 2006 observed that soil property such as sand content was negatively correlated to maize yield.…”

Section: Discussionsupporting

confidence: 93%

Immobilization of leachate's heavy metals using soil-zeolite column

Mirzaei¹,

Heidarpour²,

Tabatabaei³

et al. 2013

International Journal Of Recycling of Organic Waste in Agricult

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Purpose This study was conducted to determine the effect of compost supplemented with jatropha cake on maize (Zea mays L) yield in a degraded soil and their residual effects on soil fertility in Ilorin, Nigeria. Methods Field trials were conducted at Kwara State University Teaching and Research Farm, Malete, in 2016/2017 cropping season. The treatments consisted of control, un-amended compost Grade B supplemented with Jatropha cake AJ (30% Grade B + 70% JC) at 1.5 t/ha, BJ (30% Grade B + 70% JC) at 2.0 t/ha, CJ (50% Grade B + 50% JC) at 2.5 t/ha including NPK at 60 kg N/ha. The treatments were arranged in a randomized complete block design (RCBD) and replicated three times. Results Maize grain yield (3.1 t/ha) was obtained from CJ at 2.5 t/ha this was significantly (p < 0.05) greater than that of NPK treatment (2.2 t/ha) after the first cropping. At second trials, maize grain yield values gotten from CJ at 2.5 t/ha were also significantly (p < 0.05) greater than that of NPK values. Treatments CJ at 2.5 t/ha significantly (p < 0.05) improved soil pH, available P and exchangeable K. Conclusion Fertilizer 50% Grade B + 50% Jatropha cake at 2.5 t/ha had a significant and positive effect on soil fertility after harvesting of maize when compared with NPK in both cropping.

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Section: Discussionsupporting

confidence: 93%

Immobilization of leachate's heavy metals using soil-zeolite column

Mirzaei¹,

Heidarpour²,

Tabatabaei³

et al. 2013

International Journal Of Recycling of Organic Waste in Agricult

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“…The choice of attributes for the analyzed soil and plants, which are discussed below, was based on factors related to plant productivity (RODRIGUES; CORÁ; FERNANDES, 2012;ALVES et al, 2013;COSTA et al, 2014;BAZZI et al, 2015). Disturbed and undisturbed soil samples were collected, along with samples of plants during the phenological cycle of the crop.…”

Section: Sample Collectionmentioning

confidence: 99%

“…Defining management zones requires various steps, from data collection to map evaluation, based on which the cultivation area is divided into subareas that have homogeneity with respect to the evaluated attributes (RODRIGUES; CORÁ; FERNANDES, 2012;ALVES et al, 2013;FARID et al, 2013;DALCHIAVON et al, 2013;BAZZI et al, 2015;SANTOS et al, 2015;SARAIVA, 2015). This allows the application of inputs at appropriate rates for improving the productivity of a crop (BREDEMEIER et al, 2013;BAGHERI et al, 2013;COSTA et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Defining Management Zones Based on Soil Attributes and Soybean Productivity

et al. 2017

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-Demarcating soil management zones can be useful, for instance, delimiting homogeneous areas and selecting attributes that are generally correlated with plant productivity, but doing so involves several different steps. The objective of this study was to identify the chemical and physical attributes of soil and soybean plants that explain crop productivity, in addition to suggesting and testing a methodological procedure for defining soil management zones. The procedure consisted of six steps: sample collection, data filtering, variable selection, interpolation, grouping, and evaluation of management zones. The samples were collected in an experimental area of 12.5 ha cultivated with soybean during the 2013/14 crop in Dystrophic Red Latosol, in Mato Grosso, Brazil. A total of 117 pairs of plant and soil samples were collected. Student's t-test was used (α = 0.02) to verify that the number of samples was adequate for correlation analysis. Results showed that only the P and Mn content in the grains explained (based on R 2 values) the variation in soybean grain productivity the area. Based on the interpolation of these contents by ordinary kriging, the fuzzy C-means algorithm was used to separate them into groups by similarity. Division into two groups was the best option, which could be differentiated by Mann-Whitney test (P < 0.05), resulting in a map with 10 management zones.Keywords: Glycine max L.. Direct seeding. Precision agriculture. DEFINIÇÃO DE ZONAS DE MANEJOS A PARTIR DE ATRIBUTOS DO SOLO E PRODUTIVIDADE DE SOJARESUMO -Zonas de manejo do solo são usadas, por exemplo, para delimitar áreas homogêneas, selecionando atributos que no geral correlacionam com a produtividade das plantas, mas, defini-las requer diferentes etapas. Objetivou-se neste trabalho identificar atributos químicos e físicos do solo e de plantas de soja que explicaram a produtividade de grãos da cultura e, também, sugerir e testar um procedimento metodológico para definir zonas de manejo do solo. O procedimento consistiu de seis etapas: coleta de amostras, filtragem dos dados, seleção das variáveis, interpolação, agrupamento e avaliação das zonas de manejo. As amostras foram coletadas em uma área experimental de 12,5 ha, cultivada com soja na safra 2013/14, em um Latossolo Vermelho Distrófico, em Mato Grosso, onde foram coletados 117 pares de amostras de plantas e de solo. Utilizando-se o teste de Student (α = 0,02), verificou-se que o número de amostras foi adequado para a análise de correlação. Entretanto, apenas os teores de P e Mn dos grãos explicaram (R 2 ) a variação da produtividade de grãos de soja na área. Com base na interpolação destes teores por krigagem ordinária utilizou-se o algoritmo fuzzy C-means para separá-los em grupos por similaridade, em que a divisão em 2 grupos foi a melhor opção, que diferiram pelo teste de Mann-Whitney (P < 0,05), resultando em um mapa com 10 zonas de manejo. Palavras-chave:Glycine max L.. Plantio direto. Agricultura de precisão.

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“…The number of samples is another important issue should be analyzed. Evidently, the more samples taken, the more quality of soil maps [3] demonstrated that when soil properties are sampled at a similar rate to crop yield, it is possible to understand the cause and effect relationships related to the spatial distribution of crop yield and soil properties. High correlations between soil properties and crop yield can be observed when variables are sampled at a similar intensity.…”

mentioning

confidence: 99%