Biochar has significant potential to improve crop performance. This study examined the effect of biochar application on the photosynthesis and yield of peanut crop grown on two soil types. The commercial peanut cultivar Middleton was grown on red ferrosol and redoxi-hydrosol (Queensland, Australia) amended with a peanut shell biochar gradient (0, 0.375, 0.750, 1.50, 3.00 and 6.00%, w/w, equivalent up to 85 t ha(-1)) in a glasshouse pot experiment. Biomass and pod yield, photosynthesis-[CO2] response parameters, leaf characteristics and soil properties (carbon, nitrogen (N) and nutrients) were quantified. Biochar significantly improved peanut biomass and pod yield up to 2- and 3-folds respectively in red ferrosol and redoxi-hydrosol. A modest (but significant) biochar-induced improvement of the maximum electron transport rate and saturating photosynthetic rate was observed for red ferrosol. This response was correlated to increased leaf N and accompanied with improved soil available N and biological N fixation. Biochar application also improved the availability of other soil nutrients, which appeared critical in improving peanut performance, especially on infertile redoxi-hydrosol. Our study suggests that application of peanut shell derived biochar has strong potential to improve peanut yield on red ferrosol and redoxi-hydrosol. Biochar soil amendment can affect leaf N status and photosynthesis, but the effect varied with soil type.

Two pot experiments were conducted in two different seasons at the University of Agricultural Science, Bangalore, India, to study (a) the relationship between chlorophyll concentration (by measuring the leaf light-transmittance characteristics using a SPAD metre) and transpiration efficiency (TE) and (b) the effect of leaf N on chlorophyll and TE relationship in peanut. In Experiment (Expt) I, six peanut genotypes with wide genetic variation for the specific leaf area (SLA) were used. In Expt II, three non-nodulating isogenic lines were used to study the effect of N levels on leaf chlorophyll concentration-TE relationship without potential confounding effects in biological nitrogen fixation. Leaf N was manipulated by applying N fertiliser in Expt II. Chlorophyll concentration, TE (g dry matter kg 21 of H 2 O transpired, measured using gravimetric method), specific leaf nitrogen (g N m 22 , SLN), SLA (cm 2 g 21 ), carbon isotope composition (Á 13 C) were determined in the leaves sampled during the treatment period (35-55 days after sowing) in the two experiments. Results showed that the leaf chlorophyll concentration expressed as soil plant analytical development (SPAD) chlorophyll metre reading (SCMR) varied significantly among genotypes in Expt I and as a result of N application in Expt II. Changes in leaf N levels were strongly associated with changes in SCMR, TE and Á 13 C. In both the experiments, a significant positive relationship between SCMR and TE with similar slopes but differing intercepts was noticed. However, correction of TE for seasonal differences in vapour pressure deficit (VPD) between the two experiments resulted in a single and stronger relationship between SCMR and TE. There was a significant inverse relationship between SCMR and Á 13 C, suggesting a close linkage between chlorophyll concentration and Á 13 C in peanut. This study provides the first evidence for a significant positive relationship between TE and leaf chlorophyll concentration in peanut. The study also describes the effect of growing environment on the relationships among SLA, SLN and SCMR.

Drought is the major abiotic constraint affecting groundnut productivity and quality worldwide. Most breeding programmes in groundnut follow an empirical approach to drought resistance breeding, largely based on kernel yield and traits of local adaptation, resulting in slow progress. Recent advances in the use of easily measurable surrogates for complex physiological traits associated with drought tolerance encouraged breeders to integrate these in their selection schemes. However, there has been no direct comparison of the relative effi ciency of a physiological trait-based selection approach (Tr) vis-à-vis an empirical approach (E) to ascertain the benefi ts of the former. The genetic material used in the present study originated from three common crosses and one institute-specifi c cross from four collaborating institutes in India (total seven crosses). Each institute contributed six genotypes and each followed both the Tr and E selection approaches in each cross. The fi eld trial of all selections, consisting of 192 genotypes (96 each Tr and E selections), was grown in 2000/2001 in a 4 × 48 alpha design in 12 season × location environments in India. The selection effi ciency of Tr relative to E, RE Tr , was estimated using the genetic concept of response to selection. Based on all the 12 environments, the two selection methods performed more or less similarly (RE Tr = 1.045). When the 12 environments were grouped into rainy season and post-rainy season, the relative response to selection in Tr method was higher in the rainy than in the post-rainy season (RE Tr = 1.220 vs 0.657) due to a higher genetic variance, lower G × E, and high h 2 . When the 12 environments were classifi ed into four clusters based on plant extractable soil-water availability, the selection method Tr was superior to E in three of the four clusters (RE Tr = 1.495, 0.612, 1.308, and 1.144) due to an increase in genetic variance and h 2 under Tr in clustered environments. Although the crosses exhibited signifi cant differences for kernel yield, the two methods of selection did not interact signifi cantly with crosses. Both methods contributed more or less equally to the 10 highest-yielding selections (six for E and four for Tr). The six E selections had a higher kernel yield, higher transpiration (T), and nearly equal transpiration effi ciency (TE) and harvest index (HI) relative to four Tr selections. The yield advantage in E selections came largely from greater T, which would likely not be an advantage in water-defi cient environments. From the results of these multi-environment studies, it is evident that Tr method did not show a consistent superiority over E method of drought resistance breeding in producing a higher kernel yield in groundnut. Nonetheless, the integration of physiological traits (or their surrogates) in the selection scheme would be advantageous in selecting genotypes which are more effi cient water utilisers or partitioners of photosynthates into economic yield. New biotechnological tools are being explored to increas...

No abstract

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM’s maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.