Population Dynamics of Trifolium balansae and T. resupinatum in Self- Regenerating Pasture. I. Seed and Plant Densities and Dry Matter Yield

1996 ◽  
Vol 33 (6) ◽  
pp. 1241 ◽  
Author(s):  
P. I. Jansen ◽  
R. L. Ison
Keyword(s):  
Population Dynamics ◽  
Dry Matter ◽  
Dry Matter Yield ◽  
Plant Densities

Comparison of some Stylosanthes species at three sites in central Queensland

1976 ◽  
Vol 16 (82) ◽  
pp. 715 ◽  
Author(s):  
LA Edye ◽  
JB Field ◽  
HG Bishop ◽  
RL Hall ◽  
JH Prinsen ◽  
...  
Keyword(s):  
Dry Matter ◽  
Native Grasses ◽  
Dry Matter Yield ◽  
The Third ◽  
Plant Densities

Nineteen accessions of eight Stylosanthes species were grown in association with volunteer species (mainly native grasses) for three years in small mown swards at three different sites in central Queensland. The outstanding accessions for dry matter yield were S. scabra 40292 and 40205: they significantly out-yielded S. hamata cv. Verano at all three sites and their plant densities in the third year at the wettest site were significantly higher than all other accessions except S. scabra 49833. At all sites, 'Verano' gave significantly higher mean annual dry matter yields than S. guyanensis cv. Oxley and S. humilis cv. Paterson. Other accessions that showed promise were S. scabra 49833 and 40289 and S. viscosa 34904: the latter accession performed relatively better at the wettest site.

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.

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.

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