scholarly journals EFFECTS OF SPATIAL VARIABILITY OF SOIL CHEMICAL PARAMETERS ON TIFTON 85 GRASS YIELD1

2020 ◽  
Vol 33 (1) ◽  
pp. 236-245
Author(s):  
EUDOCIO RAFAEL OTAVIO DA SILVA ◽  
MURILO MACHADO DE BARROS ◽  
MARCOS GERVASIO PEREIRA ◽  
JOÃO HENRIQUE GAIA GOMES ◽  
STEPHANY DA COSTA SOARES
Keyword(s):  
Decision Making ◽  
Spatial Variability ◽  
Dry Matter ◽  
Irregular Sampling ◽  
Descriptive Statistics ◽  
Dry Matter Yield ◽  
Chemical Parameters ◽  
Tropical Pastures ◽  
Chemical Attributes ◽  
Soil Chemical Parameters

ABSTRACT Studies on spatial variability of soil attributes of tropical pastures gather information that can assist in decision making about managements of these soils. The objective of the present study was to evaluate the spatial variability of soil chemical attributes and their effects on grass yield of Tifton 85. The experiment was carried out in an area of 3.91 ha at the Feno Rio Farm of the Federal Rural University of Rio de Janeiro, Seropédica, RJ, Brazil. Soils of the 0-0.20 and 0.20-0.40 m layers were sampled considering an irregular sampling mesh, making a total of 50 georeferenced points. The parameters evaluated were: the soil chemical attributes pH, Al+3, Ca+2, Mg+2, Na+, K+, P, H+Al, and total organic carbon (TOC); and the Tifton 85 dry matter yield (DMY). The results of these parameters were subjected to descriptive statistics, linear correlation, and geostatistics, and maps were developed for the analyses. Regions with grass yields different from the general mean were found in the area, which presented mean grass yield of 2248 kg ha-1. The soil chemical parameters Na+, Ca+2, TOC, and H+Al were significantly correlated with DMY, confirming that they are important and affect the Tifton 85 grass yield. The mapping of the Tifton 85 cycle is important for understanding the variability of DMY. The investigation of areas with different productive potentials should be followed by development of maps of soil chemical attributes to correlate and understand the ratios that may be involved with these variations.

scholarly journals Spatial variability of soil fertility and its relation with cocoa yield

2017 ◽  
Vol 21 (2) ◽  
pp. 88-93 ◽  
Author(s):  
Railton O. dos Santos ◽  
◽  
Laís B. Franco ◽  
Samuel A. Silva ◽  
George A. Sodré ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Spatial Variability ◽  
Soil Fertility ◽  
Soil Properties ◽  
Crop Yield ◽  
Chemical Properties ◽  
Western Region ◽  
Chemical Attributes ◽  
Cocoa Yield

ABSTRACT The knowledge on the spatial variability of soil properties and crops is important for decision-making on agricultural management. The objective of this study was to evaluate the spatial variability of soil fertility and its relation with cocoa yield. The study was conducted over 14 months in an area cultivated with cocoa. A sampling grid was created to study soil chemical properties and cocoa yield (stratified in season, off-season and annual). The data were analyzed using descriptive and exploratory statistics, and geostatistics. The chemical attributes were classified using fuzzy logic to generate a soil fertility map, which was correlated with maps of crop yield. The soil of the area, except for the western region, showed possibilities ranging from medium to high for cocoa cultivation. Soil fertility showed positive spatial correlation with cocoa yield, and its effect was predominant only for the off-season and annual cocoa.

THE INFLUENCE OF Zn AND P FERTILIZER ON THE DRY MATTER YIELD AND NUTRIENT CONTENT OF FLAX (Linum usitatissimum L.) ON SOILS VARYING IN Ca AND Mg LEVEL

1989 ◽  
Vol 69 (3) ◽  
pp. 461-472 ◽  
Author(s):  
C. A. GRANT ◽  
L. D. BAILEY
Keyword(s):  
Linum Usitatissimum ◽  
Dry Matter ◽  
Nutrient Content ◽  
Yield Response ◽  
Dry Matter Yield ◽  
Chemical Parameters ◽  
Linum Usitatissimum L ◽  
Zinc Fertilization ◽  
P Fertilizer ◽  
P Application

Flax (Linum usitatissimum L.) was grown in two growth chamber experiments on a total of 16 Black Chernozemic soils varying in content of Mg, Ca, P, and Zn. On three of the soils, dry matter yield of flax increased in response to application of P. Phosphorus availability was greater with broadcast than with banded fertilizer applications. Increased yield in response to Zn application was observed on one-half of the soils. Applications of P that increased P level in the tissue above 0.46% led to consistent but nonsignificant decreases in yield and reduced the level of Zn in the tissue. Zinc fertilization increased Zn and decreased P level in the tissue. Yield response to P application was not strongly related to soil chemical parameters measured, but increased as tissue P level decreased and tissue Zn level increased. High levels of soil Mg and soil pH and high tissue levels of Mg and P were the factors most closely associated with a yield response to Zn applied with P. Key words: Flax, Linum usitatissimum, Ca, Zn, P, Mg, fertilizer placement

scholarly journals Replacement of liming and NPK fertilization with turkey litter in degraded areas grown with Urochloa decumbens

2018 ◽  
Vol 39 (2) ◽  
pp. 467
Author(s):  
Andrisley Joaquim da Silva ◽  
Fernando França da Cunha ◽  
Cassiano Garcia Roque ◽  
Monice Donatila Tavares da Silva ◽  
Diego Oliveira Ribeiro ◽  
...  
Keyword(s):  
Organic Matter ◽  
Dry Matter ◽  
Block Design ◽  
Control Sample ◽  
Base Saturation ◽  
Dry Matter Yield ◽  
Soil Fertilization ◽  
Urochloa Decumbens ◽  
Calcium Magnesium ◽  
Chemical Attributes

Soil fertility and acidity correction in recovering areas require high doses of correctives and fertilizers. Therefore, the use of low-cost products may be an alternative in infertile areas. The objective of this study was to evaluate the effect of soil fertilization and correction methods on the yield of degraded areas cultivated with Urochloa decumbens and soil chemical attributes. The study was conducted in Orthic Quartzarenic Neosol in Mineiros, Goiás, Brazil, from October 2011 to September 2013. The experiment included soil samples treated with 2 Mg ha-1 of dolomitic limestone, a standard fertilizer (45, 54, and 75 kg ha-1 of N, P, and K, respectively), or 3 Mg ha-1 of turkey litter, and a control sample without correction/fertilization. Each treatment included four replicates in a completely randomized block design. The experimental plots consisted of areas of 4.0 m2 (2.0 ?? 2.0 m). The dry matter yield of forage grass and the following soil chemical attributes were evaluated: organic matter, hydrogen potential (pH in CaCl2), phosphorus (resin), potassium, calcium, magnesium, cation exchange capacity (CEC), and base saturation. The data were subjected to analysis of variance, and the means were compared using Tukey’s test at a level of significance of 0.05. Fertilization did not affect the pH, potassium, and CEC of the soil. Fertilization with turkey litter increased the levels of organic matter, phosphorus, calcium, magnesium, and base saturation compared with soils subjected to standard fertilization or liming. Furthermore, soils fertilized with turkey litter presented higher dry matter yield of Urochloa decumbens compared with unfertilized soils or soils subjected to acidity correction by liming but were not significantly different from soils treated with standard fertilizers. Therefore, fertilization with 3 Mg ha-1 of turkey litter is recommended for improving degraded pastures.

Optimum harvest date of maize for biogas and silage purposes

2009 ◽  
Vol 57 (2) ◽  
pp. 119-125
Author(s):  
G. Hadi
Keyword(s):  
Dry Matter ◽  
Biogas Production ◽  
Weather Conditions ◽  
Vegetation Period ◽  
Dry Mass ◽  
Matter Content ◽  
Harvest Date ◽  
Dry Matter Content ◽  
Dry Matter Yield ◽  
Vegetative Organs

The dry matter and moisture contents of the aboveground vegetative organs and kernels of four maize hybrids were studied in Martonvásár at five harvest dates, with four replications per hybrid. The dry matter yield per hectare of the kernels and other plant organs were investigated in order to obtain data on the optimum date of harvest for the purposes of biogas and silage production.It was found that the dry mass of the aboveground vegetative organs, both individually and in total, did not increase after silking. During the last third of the ripening period, however, a significant reduction in the dry matter content was sometimes observed as a function of the length of the vegetation period. The data suggest that, with the exception of extreme weather conditions or an extremely long vegetation period, the maximum dry matter yield could be expected to range from 22–42%, depending on the vegetation period of the variety. The harvest date should be chosen to give a kernel moisture content of above 35% for biogas production and below 35% for silage production. In this phenophase most varieties mature when the stalks are still green, so it is unlikely that transport costs can be reduced by waiting for the vegetative mass to dry.

Nitrogen Fertilization of Basil

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 481a-481 ◽  
Author(s):  
M. Rangappa ◽  
H.L. Bhardwaj
Keyword(s):  
Moisture Content ◽  
Dry Matter ◽  
Calcium Nitrate ◽  
Control Treatment ◽  
Dry Matter Yield ◽  
Sweet Basil ◽  
Broad Leaf ◽  
Yield Difference ◽  
Optimum N Rate ◽  
N Rates

Sweet basil (Ocimum basilicum) is an important culinary herb in Virginia and other areas. The objective of this study, conducted during 1997, was to determine optimal N rate for fresh and dry matter yield. Seed of Broad Leaf sweet basil were direct-seeded on 18 June in rows 0.75 m apart in a RCBD design with 8 replications. Four N rates (0, 25, 50, and 75 kg N/ha) were used. Calcium nitrate (15.5% N) was used as the fertilizer source. All plants from 1-m row length from middle row of each plot were harvested by hand on 23 Sept. and fresh weights were recorded. The plant material was dried at 70°C for 48 h to record dry weights. The moisture content at harvest was calculated from fresh and dry weights. The fresh yields following 0, 25, 50, and 75 kg N/ha were 3.7, 5.4, 6.4, and 6.8 kg/m2, respectively. The yield difference between two highest N rates was not significant, however, both these rates had significantly higher yield than the two lowest rates. Similar results were also obtained for dry matter yields. The highest N rate of 75 kg N/ha resulted in significantly higher dry matter yield (1.3 kg/m2) as compared to the other three rates. The lowest dry matter yield was obtained after the control treatment (0.6 kg/m2). An opposite relationship between N rate and moisture content was observed when the highest moisture content resulted from control and 50 kg N/ha treatments. These results indicate that optimum N rate for sweet basil in Virginia is 50 to 75 kg/ha.

Effects of Seeding Rate on the Dry Matter Yield and Nutritive Value of Fall‐Grown Oat

cftm ◽  
2016 ◽  
Vol 2 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Wayne K. Coblentz ◽  
Jason S. Cavadini
Keyword(s):  
Dry Matter ◽  
Nutritive Value ◽  
Dry Matter Yield ◽  
Seeding Rate

Water‐phosphorus coupling enhances fine root turnover and dry matter yield of alfalfa under drip irrigation

2021 ◽  
Author(s):  
Xuanshuai Liu ◽  
Junwei Zhao ◽  
Junying Liu ◽  
Weihua Lu ◽  
Chunhui Ma ◽  
...  
Keyword(s):  
Drip Irrigation ◽  
Dry Matter ◽  
Fine Root ◽  
Root Turnover ◽  
Dry Matter Yield ◽  
Fine Root Turnover

scholarly journals Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3971
Author(s):  
Gabriel Silva de Oliveira ◽  
José Marcato Junior ◽  
Caio Polidoro ◽  
Lucas Prado Osco ◽  
Henrique Siqueira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Dry Matter ◽  
Pearson Correlation ◽  
Genetic Correlations ◽  
Remote Sensing Data ◽  
Breeding Program ◽  
Yield Traits ◽  
Dry Matter Yield ◽  
Breeding Programs ◽  
Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

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