scholarly journals Prospects for Measurement of Dry Matter Yield in Forage Breeding Programs Using Sensor Technologies

Agronomy ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 65 ◽  
Author(s):  
Alem Gebremedhin ◽  
Pieter E. Badenhorst ◽  
Junping Wang ◽  
German C. Spangenberg ◽  
Kevin F. Smith
Keyword(s):  
Dry Matter ◽  
Low Cost ◽  
Large Data ◽  
Breeding Systems ◽  
Full Potential ◽  
Dry Matter Yield ◽  
Forage Crops ◽  
Phenotypic Data ◽  
Breeding Programs ◽  
High Dry Matter

Increasing the yield of perennial forage crops remains a crucial factor underpinning the profitability of grazing industries, and therefore is a priority for breeding programs. Breeding for high dry matter yield (DMY) in forage crops is likely to be enhanced with the development of genomic selection (GS) strategies. However, realising the full potential of GS will require an increase in the amount of phenotypic data and the rate at which it is collected. Therefore, phenotyping remains a critical bottleneck in the implementation of GS in forage species. Assessments of DMY in forage crop breeding include visual scores, sample clipping and mowing of plots, which are often costly and time-consuming. New ground- and aerial-based platforms equipped with advanced sensors offer opportunities for fast, nondestructive and low-cost, high-throughput phenotyping (HTP) of plant growth, development and yield in a field environment. The workflow of image acquisition, processing and analysis are reviewed. The “big data” challenges, proposed storage and management techniques, development of advanced statistical tools and methods for incorporating the HTP into forage breeding systems are also reviewed. Initial results where these techniques have been applied to forages have been promising but further research and development is required to adapt them to forage breeding situations, particularly with respect to the management of large data sets and the integration of information from spaced plants to sward plots. However, realizing the potential of sensor technologies combined with GS leads to greater rates of genetic gain in forages.

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 Effect of seedbed methods and time of harvest on the yield and nutritive value of some forage crops grown on Vertisol at Debre Zeit, Ethiopia

1992 ◽  
Vol 1 (5) ◽  
pp. 491-497
Author(s):  
Abate Tedla ◽  
Helena Airaksinen ◽  
M. A. Mohamed-Saleem
Keyword(s):  
Avena Sativa ◽  
Crude Protein ◽  
Dry Matter ◽  
Nutritive Value ◽  
Dry Matter Yield ◽  
Lablab Purpureus ◽  
Forage Crops ◽  
Dry Matter Digestibility ◽  
Time Of Harvest

The influence of the improved drainage broadbed and furrow (BBF), as opposed to the traditional flat seedbed over the growing season on the dry matter yield and nutritive value of Avena sativa, Vigna unguiculata, Lablab purpureus, Vida dasycarpa, Trifolium steudneri and Sesbania sesban were studied on Vertisol. Up to 7 t/ha dry matter yield was recorded for Avena sativa and Lablab purpureus when planted on Vertisols with improved drainage. Dry matter yield of forage crops also increased with advance in stage of maturity or subsequent harvests. On both improved and traditional flat seedbed methods, the chemical analysis of forage crops showed similar declines in crude protein content and in vitro dry matter digestibility (IVDMD) levels as the maturity of forage crops progressed.

Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences

2018 ◽  
Vol 259 ◽  
pp. 1-10 ◽  
Author(s):  
Jonathan Jesus Ojeda ◽  
Octavio Pedro Caviglia ◽  
Jorge Gonzalo Nicolás Irisarri ◽  
Mónica Graciela Agnusdei
Keyword(s):  
Dry Matter ◽  
Annual Variation ◽  
Dry Matter Yield ◽  
Forage Crops ◽  
Use Efficiency ◽  
Precipitation Use Efficiency

scholarly journals Estimating Elephant-Grass Adaptability and Stability for Energy-Biomass Production by Regression Models

2021 ◽  
Vol 13 (3) ◽  
pp. 68
Author(s):  
Alexandre Gomes de Souza ◽  
Yure Pequeno de Souza ◽  
Rogério Figueiredo Daher ◽  
Verônica Brito da Silva ◽  
Geraldo de Amaral Gravina ◽  
...  
Keyword(s):  
Biomass Production ◽  
Alternative Energy ◽  
Dry Matter ◽  
Northern Region ◽  
Dry Matter Yield ◽  
Elephant Grass ◽  
High Dry Matter ◽  
Matter Production ◽  
Genotype Evaluation ◽  
Janeiro State

In Brazil, elephant grass has been researched for energy generation, as it represents an alternative energy source by virtue of its biomass production. The present study was developed to examine the adaptability and energy-biomass production stability of 73 elephant-grass genotypes under a biannual-harvest regime, using the methodologies proposed by Eberhart and Russell and Cruz. The experiment was carried out at the northern region of Rio de Janeiro State, Brazil. Nine harvests and subsequent evaluations were performed at six-month intervals. Each harvest was considered an environment of genotype evaluation. After the plants were harvested, their dry matter yield (DMY) was estimated in t ha-1 harvest. Combined analysis of variance revealed highly significant effects of genotypes, harvests, and genotype × harvest interaction, by the F test. In five of the nine evaluated harvests, the genotypes had an average dry matter yield greater than the overall mean. The method of Eberhart and Russel was effective in identifying highly adaptable elephant-grass genotypes with high dry matter production stability throughout the nine harvests. When the method of Cruz was used, no genotypes were found comprising high yielding ability, adaptability to unfavorable environments, responsiveness to environmental improvement, and high stability altogether.

scholarly journals Fulfilling the responsibilites of the manager of the laboratory for the selection of forage crops

2019 ◽  
Vol 2019 (1) ◽  
pp. 118-124
Author(s):  
L.H. Marinich
Keyword(s):  
Protein Content ◽  
Control Systems ◽  
Dry Matter ◽  
Dry Matter Yield ◽  
Panicle Length ◽  
Seed Productivity ◽  
Forage Crops ◽  
Relative Contribution ◽  
High Level ◽  
Selection Of

The effects of GCA samples according to the results of dialysis analysis are given. Genetic control systems of traits of each variety are reflected, in particular the relative contribution of dominant and recessive alleles. According to the analysis of the effects of general combinatorial ability, samples with high indicators were selected for most of the studied features: the number of vegetatively elongated shoots - Poltava 52; foliage - Anto; dry matter yield - Poltava 52; protein content in dry matter - Poltava 52; the number of generative shoots - Anto and Poltava 52; panicle length - Anto and Radio-mutant k-7; seed productivity - Anto. A high level of the coefficients of heredity of the studied signs in a broad sense (H2 = 0,93 – 0,99) have been established. The coefficients of heredity in the narrow sense (h2) in terms of genetic variability due to additive effects of genes were different. The highest rate was in seed productivity (0,91), the number of vegetatively elongated shoots (0,78), dry matter yield (0,70); the lowest - in the length of the panicle (0,35) and the height of the plant - (0,43). The protein content was average (0,58). Key words: unbearded hundred-spike, diallel crosses, general combination ability, heredity.

scholarly journals Effect of mulching practices on growth and yield of forage crops under rainfed ecosystem

2018 ◽  
Vol 10 (1) ◽  
pp. 266-271
Author(s):  
Himangshu Das ◽  
Champak Kumar Kundu ◽  
Prasanta Kumar Bandyopadhyay ◽  
Sahuji Bandyopadhyay ◽  
Pintoo Bandopadhyay
Keyword(s):  
Dry Matter ◽  
Panicum Maximum ◽  
Dry Matter Yield ◽  
Soil Dust ◽  
Forage Crops ◽  
Area Index ◽  
Forage Crop ◽  
Green Fodder ◽  
Fodder Yield ◽  
Growth Attributes

There had been very less systemic study of forage crops in this part of the world. The information is scanty and not well documented. With these backgrounds, a field experiment was conducted during winter and summer season of 2012-13 and 2013-14 with three forage crops [Brachiaria brizantha, Panicum maximum and Setaria anceps] and three mulching managements [no mulching, soil dust mulching and live mulching]. Experiment was laid out in split plot design with three replications. Forage crop was assigned to the main plots and mulching to the subplots. The results revealed that superior growth attributes as well as highest green fodder yield (91.14 q ha-1 in winter and 307.20 q ha-1 in summer) and dry matter yield (26.27 q ha-1 in winter and 66.99 q ha-1 in summer) were obtained with forage crop Setaria anceps. Mulching influenced all growth parameters (plant height, leaf area index and crop growth rate) significantly and recorded highest with live mulching followed by soil dust and no mulching. Adoption of live mulching resulted in highest green fodder yield (94.17 q ha-1 in winter and 309.58 q ha-1 in summer) as well as highest dry matter yield (26.28 q ha-1 in winter and 71.93 q ha-1 in summer). The present experimental findings signify the importance of live mulching in improving growth attributes and yield of forage crops.

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