Prediction of the Nutritive Value of Pasture Silage by Near Infrared Spectroscopy (NIRS)

Restaino, E.; Fernandez, E.; Manna, Alejandro La; Cozzolino, Daniel

doi:10.4067/s0718-58392009000400011

Cited by 10 publications

(20 citation statements)

References 18 publications

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“…The total number of lab-analyzed plants was 190 for the four destructive harvests. The plant tissue was weighed, then oven dried at 60 • C for 48 hours, and ground in a Foss cyclone grinder with a 1 mm grating [29,41]. The sample were analyzed for eight NV parameters using a Foss NIRS TM XDS rapid content analyzer (HillerØd, Denmark).…”

Section: Laboratory Analysismentioning

confidence: 99%

“…Atmospheric turbidity has a profound influence on solar radiance and must be considered if sunlight is used as the energy source for spectroscopy [28]. Lack of sample preparation also introduces noise, as the drying and grinding of samples for lab-based NIRS are important for improving accuracy and robustness of the technique [29]. When spectral collection is in situ, the variation in leaf size, shape and illumination create optical phenomena which are a large source of noise [30].…”

Section: Introductionmentioning

confidence: 99%

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Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants

et al. 2019

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The nutritive value (NV) of perennial ryegrass is an important driver of productivity for grazing stock; therefore, improving NV parameters would be beneficial to meat and dairy producers. NV is not actively targeted by most breeding programs due to NV measurement being prohibitively slow and expensive. Nondestructive spectroscopy has the potential to reduce the time and cost required to screen for NV parameters to make targeted breeding of NV practical. The application of a field spectrometer was trialed to gather canopy spectra of individual ryegrass plants to develop predictive models for eight NV parameters for breeding programs. The targeted NV parameters included acid detergent fibre, ash, crude protein, dry matter, in vivo dry matter digestibility, in vivo organic matter digestibility, neutral detergent fibre, and water-soluble carbohydrates. The models were developed with partial least square regression. Model predicted ranking of plants had R2 between (0.87 and 0.39) and lab rankings of highest preforming plants. The highest ranked plants, which are generally the selection target for breeding programs, were accurately identified with the canopy-based model at a speed, cost and accuracy that is promising for NV breeding programs.

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Section: Laboratory Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants

et al. 2019

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“…para DIVMS e menor para FDN (FREITAS et al, 2016). Restaino et al (2009) trabalharam com silagens de forragens (gramíneas, leguminosas e mistura das duas -Lotus, Festuca, Lolium, Leucaena), e conseguiram R 2 de calibrações para FDN igual a 0,75, para FDA igual a 0,80 e para DIVMS igual a 0,60.…”

Section: Calibrações E Validações Internasunclassified

“…Em um trabalho com silagem de forragens (gramíneas, leguminosas e mistura das duas -Lotus, Festuca, Lolium, Leucena), Restaino et al (2009) conseguiram SEP da validação para FDN, FDA e DIVMS iguais a 8,1, 4,8 e 4,5, respectivamente. Talvez piores do que os presentes resultados por terem utilizado vários gêneros de plantas, e conservadas (LUTZ et al, 1984).…”

Section: Validações Externasunclassified

“…192 -0,502 0,049 0,043 -0,124 -0,077 -0,008 -0,159 -0,126 0,138 -0,084 -0,1077 -0,133 0,422 -0,287 -0coeficiente angular da equação linear de regressão entre os vieses de digestibilidade in vitro da matéria seca e digestibilidade in vitro da fibra em detergente neutro e a variável independente estudada; 2 Coeficiente de determinação do modelo de regressão linear entre vieses de digestibilidade in vitro da matéria seca e digestibilidade in vitro da fibra em detergente neutro e a variável independente estudada; 3 Probabilidade de aceitação da hipótese nula: coeficiente angular = Regressão linear entre vieses das estimativas da digestibilidade in vitro da matéria seca (método de espectroscopia em infravermelho próximo -métodos convencionais: DIFDIVMS) É claro que mais estudos sobre acurácia, precisão e robustez das análises em NIRS utilizando Brachiaria devem ser conduzidos, principalmente com número maior de amostras, e de anos diferentes(RESTAINO et al, 2009), a fim de que se tenha cada vez mais confiabilidade nos resultados e se compreenda quais análises necessitam de mais atenção e cuidado, tanto via úmida para abastecer o aparelho NIRS com resultados corretos, quanto no próprio NIRS, estabelecendo decisões corretas relativas a prétratamentos, escolha de PCs, retirada de outliers.…”

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>b<Quantificação de lignina em >i<Brachiaria spp.>/i< medida por LDA, LBA e NIRS>/b<

Guimarães¹

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AGRADECIMENTOS ♥ A Jesus, Maria e todos os santos, por me regerem, me guardarem, me governarem e me iluminarem. ♥ A meus familiares, pela sabedoria, força, incentivo, carinho, educação e muita, mas muita paciência. Em especial a meus pais Martius e Maria Aparecida que sempre lutaram por mim incondicionalmente. ♥ À Universidade de São Paulo (USP) e ao Prof. Dr. Romualdo Shigueo Fukushima por ter me acolhido como orientada, pela infraestrutura e pela confiança em mim depositada. ♥ À Embrapa Pecuária Sudeste (CPPSE) pelas doações e condições de realizar este projeto. Em especial ao Gilberto de Souza, Cristina Picchi, Mariana Dias (empresa Büchi) e Andrea Barreto. ♥ Ao meu namorado Thiago Henrique da Silva, por ter me apoiado desde o começo até o fim deste projeto, sem medir esforços para me ajudar, com amor e compreensão. ♥ A todos os docentes do Departamento de Nutrição e Produção Animal (VNP), em especial ao professor Paulo Mazza Rodrigues, e também os da FZEA Valdo Herling, Lilian Pereira e Saulo da Luz e Silva por todos os ensinamentos. ♥ Aos professores Lilian Barreto Elston, Ed Hoffmann Madureira e Josefino Mendes Neto (Juju), por me ensinarem que os valores são a base da educação. ♥ Aos funcionários do VNP-FMVZ e da FZEA, em especial ao Pedro Pacheco, à Simi, à Renata, à Ana, à Alessandra, dona Lúcia, Dione, João Paulo, a todos os funcionários das bibliotecas, todas as faxineiras, os vigilantes e seguranças, por estarem sempre disponíveis, inúmeras vezes, para me ajudar. ♥ Aos professores da banca examinadora, pela disponibilidade e contribuição. ♥ E a todos aqueles que contribuíram direta ou indiretamente para realização deste trabalho, MEUS SINCEROS AGRADECIMENTOS. Eu não teria chegado até aqui sem cada um de vocês. ♥ O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES)-Código de Financiamento 001. Tem que ter veneno!

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Abstracts from the Proceedings of the 33rd Biennial Conference of the Australian Association of Animal Sciences

2021

Anim. Prod. Sci.

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During the career of Professor Eric Underwood, the feeding of livestock was closely linked to the availability of local resources. He solved problems by making the connections between the nutrient content of soil and livestock health, but while his research had global impact, I am sure he didn't foresee either the scale of the global feed trade or the environmental impact that livestock systems would have on the world 50 years on from his retirement in 1970.The livestock industry in 2020 is very different from what it was in 1970: global meat production is ~336 million tonnes per year (FAOSTAT averaged over 2016, 17 and 18) compared to the 92 million tonnes produced globally 50 years before. In Australia, the proportional contribution (by weight) of sheep and goat meat to total meat production has decreased from 35 to 16% over that time period and the annual import (mainly from Argentina) of soybean cake in 2016-18 averaged 743,000 tonnes out of a total of 895,000 tonnes of imported feed. Thus, even with Australia's land mass, feeding its livestock sector has a long-range footprint.As we know, livestock production also has global impact through the emission of greenhouse gases (GHGs) into the atmosphere -the relationship also influenced by diet. Gerber et al. (2013) published an extensive assessment of the global contribution of emissions of GHGs from the livestock sector in 2013: beef and cattle milk production accounted for 41 and 20% of the emissions, while pig meat and poultry meat and eggs contributed 9 and 8% respectively. The expansion of pasture and feed crops into forests accounted for 9%.Awareness of the negative environmental impacts of livestock production systems started to become an important topic for research in the 1990s, as policies to limit the environmental impact of agriculture were introduced (e.g. Nitrate Vulnerable Zones in the European Union). The publication of Livestock's Long Shadow in 2006 raised global awareness of the long-range environmental impacts of livestock production systems and since then millions of dollars have been invested in quantifying those impacts. Looking at agricultural production simply through an environmental lens is not sufficient though, since global agreement to the 2030 Agenda for Sustainable Development with 17 Sustainable Development Goals (SDGs). These goals are to be delivered as a package and include 'zero hunger' and 'economic growth', both goals to which livestock production makes a significant contribution (Mehrabi et al. 2020).Research questions thus need to address the potential consequences on all goals, of pathways for making progress towards individual goals. Eric Underwood solved animal health problems through his research, providing solutions based on nutritional knowledge. In the last 50 years animal science has added greatly to that knowledge and supported the development and implementation of technologies which have facilitated the 3.5-fold increase in global meat production. Agriculture and trade policies have also played a significant ro...

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Prediction of the Nutritive Value of Pasture Silage by Near Infrared Spectroscopy (NIRS)

Cited by 10 publications

References 18 publications

Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants

Field Spectroscopy to Determine Nutritive Value Parameters of Individual Ryegrass Plants

>b<Quantificação de lignina em >i<Brachiaria spp.>/i< medida por LDA, LBA e NIRS>/b<

Abstracts from the Proceedings of the 33rd Biennial Conference of the Australian Association of Animal Sciences

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