Minimal cost multifactor experiments for agricultural research involving hard-to-change factors

Multifactor experiments are very common in agricultural research. Randomizing run orders in multifactor experiments often witness in large number of factorwise level changes which will increase the cost and time of the experiments. Minimal cost multifactor experiments are such experiments where the cost of the experiment is minimum which can be achieved by choosing a factorial run order where the total number of factor level change is minimum as cost of the experiment is directly proportional to the number of level changes of factors. Here, a method of constructing minimal cost 2-level multifactor experiments with minimum number of factorwise level changes has been proposed. As for a same factorial combination, there may exist more than one minimally changed factorial run order, an exhaustive search was also performed to obtain all possible minimally changed run order for two level multifactorial experiments with three factors. Due to restricted randomization, adaption of these run orders may witness the effect of systematic time trend. Hence, the usual method of analysis may not be a feasible solution due to lack of randomization. Here, the analytical procedure of experiments using minimal cost multifactorial run order has also been highlighted based on a real experimental data. The work has been carried out at ICAR-Indian Agricultural Statistics Research Institute, New Delhi during 2019-20. The data from the real experiment used for explaining the analysis procedure has been collected from Climate Change Facility of ICAR-Indian Agricultural Research Institute farm, New Delhi, India based on experiments conducted during 2014-15

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Not AvailableAn experiment was executed at field condition to evaluate ecological impact of Bt cotton (Mech 162 + Bt) on soil microbes and Bt protein behavior in soil. Root exudates of Bt cotton plant containing Bt protein enter into soil which persisted in soil for atleast 235 days after sowing (DAS). During vegetative and flowering stage, Bt protein was not detectable in both qualitative and quantitative assay but, during onset of boll formation at 150 DAS, a level of 0.0013 μg/g of Cry 1Ac protein was quantified in rhizospheric soil which further increased exponentially up to 0.0033 μg/g at 195 DAS and then maintained at the same level till 235 DAS with Cry1Ac expression level of 0.0029 μg/g soil. Rhizospheric soil of Bt cotton had significantly higher (p < 0.05) abundance of Fatty Acid Methyl Esters (FAME) of gram positive bacteria. Abundance of polyunsaturated FAMEs that are indicators of fungi, were slightly higher in Bt as compared to non-Bt cotton soils. The metabolic profiling, also called community level physiological profiling (CLPP) showed more microbial functional diversity (Shannon–Wiener Diversity) in soil samples of different growth stages of Bt cotton than its corresponding non-Bt variety. Our results showed that Cry 1AC Bt protein persists in clay loamy soil even after harvesting and significantly altered microbial community composition and functional diversity in rhizospheric soil of Bt cotton than non-Bt. Any possible and unintentional changes in composition of root exudes of Bt cotton could regulate the selection of different microbial communities and thus can alter functional responses.Not Availabl

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Not AvailableThis study was conducted to evaluate 16 early Indian cauliflower genotypes for agro-morphological traits, bioactive compounds and antioxidant activity. Analysis of variance, cluster analyses, and principal components analysis (PCA) elucidated patterns of variation among the genotypes. The genotype CC 12 exhibited highest marketable curd weight (450 g). Curd sinigrin varied from 3.29 to 16.37 µmol 100g−1 FW with maximum in DC 41–5. Total antioxidant capacity (CUPRAC and FRAP) ranged from 8.87 to 24.24 mg GAE 100g−1 and 11.71 to 34.00 mg GAE 100g−1 FW, respectively. The Phenotypic coefficient of variation (PCV) was higher than the Genotypic coefficient of variation (GCV) for all the characters with highest GCV, PCV and high heritability value for sinigrin content in curd. D2 statistics classified the genotypes into three clusters where genotypes in cluster I had high sinigrin both in curd and leaf. The PCA revealed that first principal component (PC1) contributed 47.86% of total variation whereas, second principal component (PC2) contributed 35.14%. The genotypes Pusa Deepali, Selection 71, and CC 13 could be used in breeding programme for higher yield and bioactive compounds.Not Availabl

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Not AvailableHigh temperature has detrimental effects on growth and yield of any crops. A total of 62 two eggplant genotypes were evaluated for growth and yield traits at two growing season during summer season (March-July) and kharif season (July-November). Average of three replications was used for each trait in statistical analysis involving one way analysis of variance (ANOVA), Principal Component Analysis (PCA) and Agglomerative Hierarchial Clustering (AHC) using SAS ver. 9.3 and R package. Analysis of variance indicated high variability for all the traits among the eggplant genotypes. Highest yield per plant was recorded in Guhala Chatua Local (1.8 kg) in summer season whereas in kharif season, yield per plant was maximum in Swarnamani Black (5.97 Kg). The mean yield per plant (1.83 kg) was more in kharif season as compared to summer season (0.09 kg). The percentage yield reduction in summer season was more than 90% in almost all the genotypes and the lowest yield reduction (22.11%) was found in Guhala Chatua Local followed by DBL-21 and DBL-08. In summer season, the first principal component (PC1) and second principal component (PC2) could explain 48% and 14% of total variance, respectively where yield per plant contributed positively to PC1. In kharif season, first principal component (PC1) and second principal component (PC2) could explain 33% and 20% of the variance, respectively where total number of fruit weight per plant, fruit diameter and yield per plant traits contributed positively to PC1. The Hierarchical cluster analysis revealed five clusters based on the similarities among the genotypes in both summer and kharif season but the clustering pattern was different among season. Based on the study, promising heat-tolerant genotypes (Guhala Chatua Local, DBL-21 and DBL-08) have been identified which could be novel source for heat tolerance gene (s) for utilizing in breeding programme.Not Availabl

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Not AvailableIn this study, a total of 20 simple sequence repeat (SSR) markers were used to study the genetic diversity and population structure among 60 accessions of eggplant. Out of 20 SSR markers, 15 were found to be polymorphic which were subjected to statistical analysis by Power Marker and NTSYSPc software. The polymorphic SSR markers generated 46 alleles with an average of 3.06 alleles per locus. The PIC value varied from 0.12 to 0.47. The marker emf21N03 was most informative with PIC value of 0.57. The UPGMA-based dendrogram classified all the accessions into two major clusters comprising cultivated accessions and wild progenitor in cluster I and other wild accessions in cluster II. The PCA plot separated the accessions into four quadrangles where unexploited wild accessions presented in second quadrant. Population structure analysis showed 6 sub- populations with 16 accessions in population I, 12 accessions in population II, 11 accessions in population III, 5 accessions in population IV, 12 accessions in population V and 4 in population VI. The subpopulation IV had all pure individuals. These findings will provide new insights in genetic resources conservation and exploitation of genetic diversity of eggplant germplasm in breeding programme.Not Availabl

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Not AvailableMultifactor experiments are very common in agricultural research. Randomizing run orders in multifactor experiments often witness in large number of factorwise level changes which will increase the cost and time of the experiments. Minimal cost multifactor experiments are such experiments where the cost of the experiment is minimum which can be achieved by choosing a factorial run order where the total number of factor level change is minimum as cost of the experiment is directly proportional to the number of level changes of factors. Here, a method of constructing minimal cost 2-level multifactor experiments with minimum number of factorwise level changes has been proposed. As for a same factorial combination, there may exist more than one minimally changed factorial run order, an exhaustive search was also performed to obtain all possible minimally changed run order for two level multifactorial experiments with three factors. Due to restricted randomization, adaption of these run orders may witness the effect of systematic time trend. Hence, the usual method of analysis may not be a feasible solution due to lack of randomization. Here, the analytical procedure of experiments using minimal cost multifactorial run order has also been highlighted based on a real experimental data. The work has been carried out at ICAR-Indian Agricultural Statistics Research Institute, New Delhi during 2019–20. The data from the real experiment used for explaining the analysis procedure has been collected from Climate Change Facility of ICAR-Indian Agricultural Research Institute farm, New Delhi, India based on experiments conducted during 2014–15.Not Availabl

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Not AvailableA study was conducted to quantify the effect of elevated carbon dioxide (CO2) and temperature on soil organic nitrogen (N) fractions and enzyme activities in rice rhizosphere. Rice crop was grown inside the open top chambers in the ICAR-Indian Agricultural Research Institute. The N was applied in four different doses. Grain yield and aboveground N uptake by rice significantly reduced under elevated temperature. However, elevated CO2 along with elevated temperature was able to compensate this loss. Principal component analysis clearly indicated that microbial biomass carbon, microbial biomass N, amino acid N, total hydrolysable N, ammonia N and serine–threonine N contributed significantly to rice grain yield. Combined effect of elevated CO2 and elevated temperature decreased the total hydrolysable N, especially for lower N doses. The N-acetyl-glucosaminidase and leucine aminopeptidase enzyme activities were negatively correlated with the organic N pools. Higher activities of these enzymes under limited N supply may accelerate the decomposition of organic N in soil. When N was applied in super-optimal dose, plant N demand was met thereby causing lesser depletion of total hydrolysable N. Better nitrogen management will alleviate faster depletion of native soil N under future scenario of climate change and thus might cause N sequestration in soil.Not Availabl

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Not AvailableAnthropogenic activities in few decades past have increased the concentration of the atmospheric greenhouse gases (GHGs) which leads to climate change. This changing climate will certainly have impact on agricultural production. A study was carried out during the kharif season of year 2017 inside the open top chamber (OTCs) in IARI farm, New Delhi to quantify the interactive effect of elevated CO2 and temperature on growth of rice crop. Rice crop was grown in crates under two different CO2 levels: ambient (400 ppm) and elevated (550 ± 25 ppm) and with two temperature levels: ambient and elevated ( + 2°C). Growth of rice increased in elevated CO2 treatment while it decreased under high temperature condition. This was observed in terms of changes in tiller number, straw weight and root weight of the crop. Straw weight of rice reduced from 44.7 g hill - 1 to 52.1 g hill - 1in high temperature treatment. But increase in CO2 concentration significantly increased straw weight of the crop. The study showed that increased CO2 concentration was able to compensate the loss due to enhance growth of rice crop under high CO2 condition.Not Availabl

Conventional and Zero Tillage with Residue Management in Rice&ndash;Wheat System in the Indo-Gangetic Plains: Impact on Thermal Sensitivity of Soil Organic Carbon Respiration and Enzyme Activity

The impact of global warming on soil carbon (C) mineralization from bulk and aggregated soil in conservation agriculture (CA) is noteworthy to predict the future of C cycle. Therefore, sensitivity of soil C mineralization to temperature was studied from 18 years of a CA experiment under rice&ndash;wheat cropping system in the Indo-Gangetic Plains (IGP). The experiment comprised of three tillage systems: zero tillage (ZT), conventional tillage (CT), and strip tillage (ST), each with three levels of residue management: residue removal (NR), residue burning (RB), and residue retention (R). Cumulative carbon mineralization (Ct) in the 0&ndash;5 cm soil depth was significantly higher in CT with added residues (CT-R) and ZT with added residues (ZT-R) compared with the CT without residues (CT-NR). It resulted in higher CO2 evolution in CT-R and ZT-R. The plots, having crop residue in both CT and ZT system, had higher (p &lt; 0.05) Van&rsquo;t-Hoff factor (Q10) and activation energy (Ea) than the residue burning. Notably, micro-aggregates had significantly higher Ea than bulk soil (~14%) and macro-aggregates (~40%). Aggregate-associated C content was higher in ZT compared with CT (p &lt; 0.05). Conventional tillage with residue burning had a reduced glomalin content and &beta;-D-glucosidase activity than that of ZT-R. The ZT-R improved the aggregate-associated C that could sustain the soil biological diversity in the long-run possibly due to higher physical, chemical, and matrix-mediated protection of SOC. Thus, it is advisable to maintain the crop residues on the soil surface in ZT condition (~CA) to cut back on valuable C from soils under IGP and similar agro-ecologies

Nitrogen-enriched biochar co-compost for the amelioration of degraded tropical soil

Tropical soils are often deeply weathered and vulnerable to degradation having low pH and unfavorable Al/Fe levels, which can constrain crop production. This study aims to examine nitrogen-enriched novel biochar co-composts prepared from rice straw, maize stover, and gram residue in various mixing ratios of the biochar and their feedstock materials for the amelioration of acidic tropical soil. Three pristine biochar and six co-composts were prepared, characterized, and evaluated for improving the chemical and biological quality of the soil against a conventional lime treatment. The pH, cation exchange capacity (CEC), calcium carbonate equivalence (CCE) and nitrogen content of co-composts varied between 7.78–8.86, 25.3–30.5 cmol (p+) kg−1, 25.5–30.5%, and 0.81–1.05%, respectively. The co-compost prepared from gram residue biochar mixed with maize stover at a 1:7 dry-weight ratio showed the highest rise in soil pH and CEC, giving an identical performance with the lime treatment and significantly better effect (p < .05) than the unamended control. Agglomerates of calcite and dolomite in biochar co-composts, and surface functional groups contributed to pH neutralization and increased CEC of the amended soil. The co-composts also significantly (p < .05) increased the dehydrogenase (1.87 µg TPF g−1 soil h−1), β-glucosidase (90 µg PNP g−1 soil h−1), and leucine amino peptidase (3.22 µmol MUC g−1 soil h−1) enzyme activities in the soil, thereby improving the soil’s biological quality. The results of this study are encouraging for small-scale farmers in tropical developing countries to sustainably reutilize crop residues via biochar-based co-composting technology