Effect of Copper Supplied in the Form of Different Cu-Saturated Sludge samples and Copper Salts on the Cu-Concentration and Dry Matter yield of Corn Grown in Sand

1981 ◽  
pp. 287-304
Author(s):  
S. Gupta ◽  
H. Haeni
Keyword(s):  
Dry Matter ◽  
Dry Matter Yield ◽  
Copper Salts ◽  
Effect Of Copper

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.

Diurnal Variation in Alfalfa ( Medicago sativa L.) Dry Matter Yield and Overnight Losses in Harvested Alfalfa Forage 1

1973 ◽  
Vol 65 (3) ◽  
pp. 413-417 ◽  
Author(s):  
W. R. Knapp ◽  
D. A. Holt ◽  
V. L. Lechtenberg ◽  
L. R. Vough
Keyword(s):  
Diurnal Variation ◽  
Medicago Sativa ◽  
Dry Matter ◽  
Dry Matter Yield ◽  
Medicago Sativa L

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.

scholarly journals GENETIC CONTROL OF VARIATION IN A SELECTED POPULATION OF RUSSIAN WILD RYEGRASS (ELYMUS JUNCEUS)

1976 ◽  
Vol 56 (2) ◽  
pp. 275-280
Author(s):  
T. LAWRENCE
Keyword(s):  
Genetic Control ◽  
Seed Yield ◽  
Seed Weight ◽  
Dry Matter ◽  
Recurrent Selection ◽  
Direct Selection ◽  
Adult Plant ◽  
Dry Matter Yield ◽  
Seedling Characters ◽  
Additive Control

Progenies from a five-genotype diallel cross in Russian wild ryegrass, Elymus junceus Fisch., were studied to assess the pattern of genetic control for F1 seed weight and a number of seedling and adult plant characters. Variation in F1 seed weight was largely determined by the maternal parent, but some control by the pollen parent was apparent. Of the seedling characters, days to emerge, rate of leaf appearance, rate of tiller appearance, and seedling dry matter yield, only days to emerge showed additive variance which is amenable to direct selection. The other three characters could be most easily exploited by a recurrent selection program. The adult plant characters, date of inflorescence appearance, P content of the forage, and organic matter digestibility indicated strong additive control which is amenable to direct selection. Dry matter yield and seed yield also showed strong additive control which was accompanied by specific combining ability and weak maternal effects suggesting good progress should be possible by direct selection methods but crossing the selections in a diallel fashion prior to formation of synthetics might be desirable. The seedling characters, rate of leaf and tiller appearance and seedling dry matter yield were interrelated and associated with adult plant yield, thus offering the possibility of screening seedlings for these characters in a recurrent selection program for improved forage or seed yield.

EVALUATION OF ALFALFA CULTIVARS FOR REACTION TO CROWN AND ROOT ROT

1985 ◽  
Vol 65 (1) ◽  
pp. 95-98 ◽  
Author(s):  
R. MICHAUD ◽  
C. RICHARD
Keyword(s):  
Disease Severity ◽  
Root Rot ◽  
Dry Matter ◽  
Forage Yield ◽  
Dry Matter Yield ◽  
Crown And Root Rot ◽  
Disease Free

Fourteen alfalfa cultivars were grown for 2 yr at three locations and evaluated for forage dry matter yield and crown and root rot. Significant differences were found among cultivars for dry matter yield. All cultivars were affected by crown and root rot, most cultivars showing between 20 and 30% of infected tissues. Differences were observed among as well as within the cultivars for disease severity. The frequency of disease-free plants was less than 1.3% of the plants evaluated. Correlation between root rot index and forage yield was −0.87 [Formula: see text] when data were pooled over years and locations.Key words: Lucerne, root rot, cultivar, yield

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