Wheat root distribution,water extraction pattern and grain yield as influenced by time and rate of irrigation

The effect of first irrigation (26, 40 and 54 days after seeding) and the rate of irrigation (5.5, 7.5 and 9.5 cm) applied subsequently at $\text{IW}\text{E}{}_{\mathrm{<mtext>pan</mtext>}}$ ratio of 0.9 on wheat root distribution, water extraction pattern and grain yield was studied on a barrier-free, sandy loam soil. The crop developed a more extensive root system when the first irrigation was applied after 26 days than after 40 and 54 days. With the first irrigation on the 26th day, the crop, receiving subsequent irrigations less frequently but at a heavier rate, developed a deeper root system than the crop receiving frequent, light irrigations. The water extraction pattern corresponded with the root distribution pattern. A relatively small difference in root density in the deeper layers caused a greater difference in soil water content than in the upper layers. Light and frequent irrigations produced maximum grain yields. However, for developing an extensive root system and enhancing water utilization in the subsoil, an early, light irrigation with subsequent irrigations applied less frequently at a relatively heavier rate seems desirable.     

Specific identification of Pasteurella multocida serogroup-A isolates by PCR assay

A polymerase chain reaction (PCR) assay targeting the hyaC-hyaD gene was developed and used to identify strains of Pasteurella multocida belonging to serogroup-A. A set of serogroup-specific-PCR primers amplified a 564 bp product from genomic DNA prepared from bacterial cells or directly from bacterial colonies. This method detected as low as 10 ng of bacterial DNA and had a specificity of 100% for P. multocida serogroup-A. A nested PCR method yielded a single 374 bp product. All fifty isolates were also shown to be identical by restriction fragment length polymorphism (RFLP) analysis of the PCR products after digestion with BglII.     

Soil and nutrients losses under different crop covers in vertisols of Central India

Purpose

Accelerated erosion removes fertile top soil along with nutrients through runoff and sediments, eventually affecting crop productivity and land degradation. However, scanty information is available on soil and nutrient losses under different crop covers in a vertisol of Central India. Thus, a field experiment was conducted for 4 years (2010–2013) to study the effect of different crop cover combinations on soil and nutrient losses through runoff in a vertisol.

Materials and methods

Very limited information is available on runoff, soil, and nutrient losses under different vegetative covers in a rainfed vertisol. Thus, the hypothesis of the study was to evaluate if different crop cover combinations would have greater impact on reducing soil and nutrient losses compared to control plots in a vertisol.

This experiment consisted of seven treatment combinations of crop covers namely soybean (Glycine max) (CC₁), maize (Zea mays) (CC₂), pigeon pea (Cajanus cajan) (CC₃), soybean (Glycine max)?+?maize (Zea mays) ??1:1 (CC₄), soybean (Glycine ma x))?+?pigeon pea (Cajanus cajan) ?2:1 (CC₅), maize (Zea mays)?+?pigeon pea (Cajanus cajan) ??1:1 (CC₆), and cultivated fallow (CC₇). The plot size was 10?×?5 m with 1% slope, and runoff and soil loss were measured using multi-slot devisor. All treatments were arranged in a randomized block design with three replications.

Results and discussion

Results demonstrated that the runoff and soil loss were significantly (p?<?0.05) higher (289 mm and 3.92 Mg ha^?1) under cultivated fallow than those in cropped plots. Among various crop covers, sole pigeon pea (CC₃) recorded significantly higher runoff and soil loss (257 mm and 3.16 Mg ha^?1) followed by that under sole maize (CC₂) (235 mm and 2.85 Mg ha^?1) and the intercrops were in the order of maize?+?pigeon pea (211 mm and 2.47 Mg ha^?1) followed by soybean?+?maize (202 mm and 2.38 Mg ha^?1), and soybean?+?pigeon pea (195 mm and 2.15 Mg ha^?1). The lowest runoff and soil loss were recorded under soybean sole crop (194 mm and 2.27 Mg ha^?1). The data on nutrient losses indicated that the highest losses of soil organic carbon (SOC) (25.83 kg ha^?1), total nitrogen (N), phosphorus (P), and potassium (K) (7.76, 0.96, 32.5 kg ha^?1) were recorded in cultivated fallow (CC₇) as compared to those from sole and intercrop treatments. However, sole soybean and its intercrops recorded the minimum losses of SOC and total N, P, and K, whereas the maximum losses of nutrients were recorded under pigeon pea (CC₃). The system productivity in terms of soybean grain equivalent yield (SGEY) was higher (p?<?0.05) from maize?+?pigeon pea (3358 kg ha^?1) followed by that for soybean?+?pigeon pea (2191 kg ha^?1) as compared to sole soybean. Therefore, maize?+?pigeon pea (1:1) intercropping is the promising option in reducing runoff, soil-nutrient losses, and enhancing crop productivity in the hot sub-humid eco-region.

Conclusions

Study results highlight the need for maintenance of suitable vegetative cover as of great significance to diffusing the erosive energy of heavy rains and also safe guarding the soil resource from degradation by water erosion in vertisols.

     

Capturing genetic variability and selection of traits for heat tolerance in a chickpea recombinant inbred line (RIL) population under field conditions

Chickpea is the most important pulse crop globally after dry beans. Climate change and increased cropping intensity are forcing chickpea cultivation to relatively higher temperature environments. To assess the genetic variability and identify heat responsive traits, a set of 296 F_8–9 recombinant inbred lines (RILs) of the cross ICC 4567 (heat sensitive) × ICC 15614 (heat tolerant) was evaluated under field conditions at ICRISAT, Patancheru, India. The experiment was conducted in an alpha lattice design with three replications during the summer seasons of 2013 and 2014 (heat stress environments, average temperature 35 °C and above), and post-rainy season of 2013 (non-stress environment, max. temperature below 30 °C). A two-fold variation for number of filled pods (FPod), total number of seeds (TS), harvest index (HI), percent pod setting (%PodSet) and grain yield (GY) was observed in the RILs under stress environments compared to non-stress environment. A yield penalty ranging from 22.26% (summer 2013) to 33.30% (summer 2014) was recorded in stress environments. Seed mass measured as 100-seed weight (HSW) was the least affected (6 and 7% reduction) trait, while %PodSet was the most affected (45.86 and 44.31% reduction) trait by high temperatures. Mixed model analysis of variance revealed a high genotypic coefficient of variation (GCV) (23.29–30.22%), phenotypic coefficient of variation (PCV) (25.69–32.44%) along with high heritability (80.89–86.89%) for FPod, TS, %PodSet and GY across the heat stress environments. Correlation studies (r = 0.61–0.97) and principal component analysis (PCA) revealed a strong positive association among the traits GY, FPod, VS and %PodSet under stress environments. Path analysis results showed that TS was the major direct and FPod was the major indirect contributors to GY under heat stress environments. Therefore, the traits that are good indicators of high grain yield under heat stress can be used in indirect selection for developing heat tolerant chickpea cultivars. Moreover, the presence of large genetic variation for heat tolerance in the population may provide an opportunity to use the RILs in future-heat tolerance breeding programme in chickpea.     

Foliar fungal disease‐resistant introgression lines of groundnut (Arachis hypogaea L.) record higher pod and haulm yield in multilocation testing

Introgression lines (ILs) of groundnut with enhanced resistance to rust and late leaf spot (LLS) recorded increased pod and haulm yield in multilocation testing. Marker‐assisted backcrossing (MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance (PV) for rust resistance and 67.98% PV for LLS resistance. ILs in the genetic background of TAG 24, ICGV 91114 and JL 24 were evaluated for two seasons to select 20 best ILs based on resistance, productivity parameters and maturity duration. Multilocation evaluation of the selected ILs was conducted in three locations including disease hot spots. Background genotype, environment and genotype × environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV 13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39–79% higher mean pod yield and 25–89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant.     

Linking Microbial Community Dynamics Associated with Rhizosphere Carbon Flow in a Biofuel Crop (Jatropha curcas L.)

Photosynthetically derived rhizodeposits are an important source of carbon (C) for microbes in root vicinity and can influence the microbial community dynamics. Pulse labeling of carbon dioxide (¹³CO₂) coupled with stable isotope probing techniques have potential to track recently fixed photosynthate into rhizosphere microbial taxa. Therefore, the present investigation assessed the microbial community change associated with the rhizosphere and bulk soil in Jatropha curcas L. (a biofuel crop) by combining phospholipid fatty acid (¹³C-PLFA) profiling using a stable isotope ¹³CO₂ labeling approach. The labeling (¹³C) took place after 45 days of germination, PLFAs were extracted from both soils (rhizosphere and bulk) after 1 and 20 days pulse labeling and analyzed by gas chromatography-isotope ratio mass spectrometry. There was no significant temporal effect on the PLFA profiles in the bulk soil, but significantly increased abundance of Gram positive (i15:0) and Gram negative (16:1ω7c and 16:1ω5c) biomarkers was observed in the rhizosphere soil from day 1 to day 20 after labeling. The Gram negative (16:1ω7c) decreased and fungal (18:2ω6,9c) increased significantly in rhizospheric soil compared to bulk soil after day 1 of labeling. Whereas, after 20 days of labeling, the Gram negative biomarker (16:1ω7c and 18:1ω7c) decreased and Gram positive (a15:0) increased significantly in rhizospheric soil compared to bulk soil. One day following labeling, i15:0, a15:0, i16:0, 16:1ω5c, 16:0, i17:0, a17:0, 18:2ω6,9c, 18:1ω9c, and 18:0 PLFAs were significantly more enriched in δ¹³C in the rhizosphere than in the bulk soil. Twenty days after labeling, 16:1ω5c (Gram negative) and 18:2ω6,9c (fungal) were significantly more enriched in δ¹³C in the rhizosphere than in the bulk soil. These results shows the effectives of PLFA coupled using the pulse chase labeling technique to examine the microbial community changes in response to recently fixed photosynthetic C flow in rhizodeposits.