Core Ideas
Cereal‐legume binary mixtures increased forage productivity per unit area compared to cereal‐cereal and legume‐legume binary mixtures.
In binary mixtures, pearl millet was marginally more resistant to yield reduction in comparison to sorghum.
Soybean suffered the highest yield losses in binary mixtures compared to cowpea and cluster bean.
The assessment of competitive performance of mixture components is important for maximizing benefits of intercropping systems. This field study tested binary mixtures of two cereals {sorghum [Sorghum bicolor (L.) Moench] and pearl millet [Cenchrus americanus (L.) Morrone]} and three forage legumes {cowpea [Vigna unguiculata (L.) Walp.], cluster bean [Cyamopsis tetragonoloba (L.) Taub.], and soybean[Glycine max (L.) Merr.]}, along with their sole crops on competitive indices. Sorghum–cowpea binary mixture resulted in a lower green forage yield of sorghum and cowpea by 9 and 36%, respectively, but overall biomass production was increased by 30 and 117% compared to their sole crop equivalents. Partial land equivalent ratios (LER) of all component crops were higher than 0.50, indicating better land use efficiency, except of soybean in binary mixtures with cowpea and cluster bean. However, the highest LER was of sorghum–cowpea (1.55), followed by sorghum–soybean (1.48) and pearl millet–soybean (1.48) binary mixtures. Pearl millet dominated sorghum and all legumes, while cowpea remained a superior competitor among legumes as per aggressivity value (AV) index. The highest crowding ratio (CR) was exhibited by pearl millet in binary mixture with cluster bean indicating its higher competitive ability in comparison to other mixture components. Observed yield loss data indicated that pearl millet was the most resistant crop to yield loss in all binary mixtures, while soybean had the highest yield reduction. In a short term, the highest area time equivalent ratio (ATER) for sorghum–cowpea binary mixture indicated the maximum advantage for this binary mixture compared to other binary mixtures.
Activated carbon
is a widely used sorbent for the removal of mercury
from coal combustion flue gas. Many studies have been conducted to
understand the physical properties of activated carbon and the flue
gas conditions that are important for increasing its mercury adsorption
capability. The Brunauer–Emmett–Teller (BET) surface
area and pore volume of activated carbon and the injection of acidic
gases have been reported to influence the performance of activated
carbon in mercury adsorption. However, the mercury adsorption mechanism
of activated carbon is not understood in terms of the physical properties
of activated carbon and the composition of the flue gas. Therefore,
two representative raw materials of activated carbon, wood and coal,
were used in this study. Activated carbon samples with varying physical
properties were prepared by applying different carbonization and activation
conditions. The prepared activated carbons were tested for mercury
adsorption in three different simulated gas compositions: (1) a baseline
gas condition and (2) two simulated flue gas conditions. The mercury
adsorption efficiency was shown to linearly increase with the BET
surface area of activated carbon in the baseline gas condition. The
coal activated carbon showed a higher mercury adsorption efficiency
than the pinewood activated carbon. In the simulated flue gas conditions,
the mercury adsorption efficiency rapidly increased and then very
slightly increased with each physical property of activated carbon.
The term autosomal recessive congenital ichthyosis (ARCI) is the subgroup of ichthyosis, which describes a highly heterogeneous group of genetic disorders of the skin characterized by cornification and defective keratinocytes differentiation associated with mutations in at least 14 genes including <i>PNPLA1</i>. To study the molecular basis of the Pakistani kindreds (A and B) affected by ARCI, whole-exome sequencing (WES) in the DNA samples of affected members was performed followed by Sanger sequencing of the candidate gene to hunt down the disease-causing sequence variant/s. WES data analysis led to the identification of a novel nonsense sequence variant (c.892C>T; p.Arg298*, family A) and a recurrent missense variant (c.102C>A; p.Asp34Glu, family B) in <i>PNPLA1</i> mapped to the ARCI locus in chromosome 6p21.31. Validation and cosegregation analysis of the variants in the remaining family members of the respective families were confirmed by Sanger sequencing. The current investigation expands the spectrum of <i>PNPLA1</i> mutations and helps establish the proper clinico-genetic diagnosis and correct genotype-phenotype correlation.
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