Compositional quality

Maize (Zea mays L.) grain yield and compositional quality are interrelated and are highly influenced by environmental factors such as temperature, total precipitation, and soil water storage. Our aim was to develop a regression model to account for this relationship among grain yield and compositional quality traits across a large geographical region. Three key growth periods were used to develop algorithms based on the week of emergence, the week of 50% silking, and the week of maturity that enabled collection and modeling of the effect of weather and climatic variables across the major maize growing region of the United States. Principal component analysis (PCA), stepwise linear regression models, and hierarchical clustering analyses were used to evaluate the multivariate relationship between weather, grain quality, and yield. Two PCAs were found that could identify superior grain compositional quality as a result of ideal environmental factors as opposed to low-yielding conditions. Above-average grain protein and oil levels were favored by less nitrogen leaching during early vegetative growth and higher temperatures at flowering, while greater oil than protein concentrations resulted from lower temperatures during flowering and grain fill. Water availability during flowering and grain fill was highly explanatory of grain yield and compositional quality.

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The Diagnosis of the Causes of the Production of Herd Milk With Low Fat, Protein and Lactose Contents

BSAP Occasional Publication ◽

10.1017/s0263967x00003578 ◽

1984 ◽

Vol 9 ◽

pp. 110-111

Author(s):

H. R. Ferns ◽

D. J. Roberts

Keyword(s):

Milk Fat ◽

Low Cost ◽

Accurate Information ◽

Milk Analysis ◽

Dual Approach ◽

Large Numbers ◽

Flow Diagrams ◽

Compositional Quality ◽

Herd Milk ◽

Simple Flow

A dual approach is required to diagnose the cause or causes of the production of herd milk of inferior compositional quality. By studying the results of the analysis of a milk sample in conjunction with accurate information obtained at the farm, it is frequently possible to trace the origin of the problem and, hence, give reliable advice to overcome it. Simple flow diagrams are available as an aid to the Adviser and the diagrams for milk fat, protein and lactose are illustrated.Case histories are available to illustrate the approach used and indicate the effects of advice on milk production and compositional quality. When diagnosis is difficult, a more detailed investigation is necessary. This might involve the sampling and analysis of foods and the analysis of samples of milk from individual cows. The use of automated infra red spectrophotometric instruments for milk analysis and the processing of results using computers, enable large numbers of samples to be dealt with expeditiously and at low cost.

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Influence of wilting time on silage compositional quality and microbiology

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200004701 ◽

2001 ◽

Vol 2001 ◽

pp. 88-88 ◽

Cited By ~ 1

Author(s):

I.A. Bouriako ◽

H. Shihab ◽

V. Kuri ◽

J. K. Margerison

Keyword(s):

Dry Matter ◽

Microbial Growth ◽

Matter Content ◽

Dry Matter Content ◽

Forage Crops ◽

Fermentation Quality ◽

Feeding Value ◽

Silage Quality ◽

Compositional Quality

Wilting grass before ensiling has become a firmly established practice, since it provides economic advantages due to the increment of the dry matter content of the forage before ensiling. Most forage crops contain less than 20 per cent of dry matter when they are cut thus reduction of the weight of crop to be transported provides advantages (Gordon et al., 1999). Also, research has shown that such practices yield improved and reduced effluent loss from the silo and higher feeding value of the silage. Wilting of grass prior to ensiling has been widely adopted as a means of reducing effluents produced and improving the fermentation quality of silage. The aim of this research was to assess the effect of differing wilting periods and silage moisture levels of silage quality and microbial growth levels.

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A comparison of the flavor and compositional quality of peanuts from several origins

Food Chemistry ◽

10.1016/0308-8146(94)90042-6 ◽

1994 ◽

Vol 51 (1) ◽

pp. 21-27 ◽

Cited By ~ 13

Author(s):

K BETT ◽

J VERCELLOTTI ◽

N LOVEGREN ◽

T SANDERS ◽

R HINSCH ◽

...

Keyword(s):

Compositional Quality

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Routine testing of producers' milk supplies for compositional quality using randomly selected samples

International Journal of Dairy Technology ◽

10.1111/j.1471-0307.1989.tb02152.x ◽

1989 ◽

Vol 42 (2) ◽

pp. 42-47

Author(s):

J. CONNOLLY ◽

M G. FLEMING ◽

P. REID

Keyword(s):

Routine Testing ◽

Compositional Quality

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Egyptian mango by-product 1. Compositional quality of mango seed kernel

Food Chemistry ◽

10.1016/j.foodchem.2006.10.017 ◽

2007 ◽

Vol 103 (4) ◽

pp. 1134-1140 ◽

Cited By ~ 115

Author(s):

Ahmed E.M. Abdalla ◽

Saeid M. Darwish ◽

Eman H.E. Ayad ◽

Reham M. El-Hamahmy

Keyword(s):

Seed Kernel ◽

Mango Seed Kernel ◽

Compositional Quality ◽

Mango Seed

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Productive performance of Holstein and the crossbreding Kiwi Cross x Holstein cattle

Agronomía Mesoamericana ◽

10.15517/am.v31i2.38541 ◽

2020 ◽

pp. 329-339

Author(s):

Henry David Mogollón García ◽

David Felipe Nieto Sierra ◽

Edwin Castro-Rincón

Keyword(s):

Milk Production ◽

Production Costs ◽

Holstein Cattle ◽

Dairy Production ◽

Productive Performance ◽

Total Solids ◽

Holstein Breed ◽

Compositional Quality ◽

Improved Performance

Introduction. During decades, milk production in the Nariño state has depended on the Holstein breed. For this reason, it is necessary to evaluate a model of milk production that allows to decrease production costs and in turn improves the compositional quality of the milk. Objective. This study aimed to compare milk production and compositional quality of Holstein (HO) and the crossbreed between Kiwi Cross (KC) x HO. Materials and methods: Monthly milk production in HO cows (n=30) and the ones from the F1 of the KC x HO cross (n=40), was measured by adjusting the day in milk (DIM) and milk production by third of lactation, fat, protein and total solids. For the period between October 2016 and May 2017, 9,809 dairy production records were analyzed. Results: Maximum production was 25.8 ± 0.53 vs. 23.2 ± 0.53 l day-1 for HO vs. KC cows (p<0.05), respectively. The DIM was not different; however, in days 60, 90, 150, 180, 210 and 240 the HO group produced more milk than the KC group, with a persistence in the lactation peak until day 60, and from that point onwards milk production showed decreasing rates in both groups. Furthermore, the production per third of lactation was higher (p<0.05) in the first third compared to the second and third periods for HO (13.6±0.56 vs. 11.3±0.5723 and 9.9±0.47 l day-1, respectively) and KC (12.8±0.4505 vs. 10.6±0.66 and 9.5 ± 1.69 l day-1, respectively). Fat content was higher (p<0.05) in KC compared to HO in week one, three and five (4±0.07, 4±0.07, 4±0.07 vs. 3.6±0.12, 3.6±0.11, 3.7±0.09 %, respectively); likewise, protein in week one and four was higher in the KC group compared to HO (3.3±0.04 vs. 3.1±0.05 %; p<0.05). Total solids were 13.3±0.17 vs. 12.5±0.23% (p<0.05) for KC and HO cows, respectively in weeks two and five. Conclusion: Milk production in KC and HO was similar; however, KC improved performance in compositional milk quality, increasing the percentages of fat, protein and consequently, total solids.

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