Groundnut (Arachis hypogaea), an important oilseed and food crop of Andhra Pradesh, India is grown largely as a rainfed crop during the rainy season. Drought is the major abiotic stress affecting yield and quality of rainfed groundnut in the state. Yield losses due to drought are highly variable depending on its timing, intensity and duration coupled with other location specific environmental factors such as irradiance and temperature (Nigam et al. 2001). Thus the groundnut productivity in rainy season in the state ranges between 500 kg ha-1 and 1200 kg ha-1 (Reddy et al. 2003).

Summary 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 efficiency of a physiological trait‐based selection approach ( Tr ) vis‐à‐vis an empirical approach ( E ) to ascertain the benefits of the former. The genetic material used in the present study originated from three common crosses and one institute‐specific 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 field 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 efficiency 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 classified 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 significant differences for kernel yield, the two methods of selection did not interact significantly 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 efficiency (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‐deficient 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 efficient water utilisers or partitioners of photosynthates into economic yield. New biotechnological tools are being explored to increase efficiency of physiological trait‐based drought resistance breeding in groundnut.

Aflatoxin contamination in peanut kernels is a serious food safety issue throughout the world. Stringent implementation of the international regulatory limits for aflatoxin contamination has become a major factor affecting the economic viability of dryland peanut growers in regional Queensland. In this study, the effect of time of harvesting (digging) and threshing on kernel yield, seed grades, aflatoxin contamination and gross returns were examined with peanut (cv. Streeton), grown in large-scale on-farm trials in the Burnett District of Queensland, during the 1997-98 and 1999-2000 seasons. Aflatoxin contamination was widespread during the 1997-98 season because of a severe and prolonged end-of-season drought and associated elevated soil temperatures. During the 1999-2000 season, aflatoxin risk was low at 2 sites because of well-distributed rainfall and lower soil temperatures, in contrast to the other 2 sites where the risk was higher. In both seasons, early harvest and threshing under high aflatoxin risk conditions resulted in consistently lower aflatoxin concentrations and higher gross returns (up to 27%) than in delayed harvesting treatments. However, under low aflatoxin risk conditions crops could be left longer to realise higher potential yield and better seed grades. Indeed, early harvest under low aflatoxin risk resulted in lower gross returns because of lower yields and poorer seed grades. The current study highlighted the importance of assessing aflatoxin risk on a site-by-site basis in order to make appropriate decisions on timing of harvest so as to minimise aflatoxin contamination and maximise gross returns from dryland peanuts.

This paper describes the physiological basis and validation of a generic legume model as it applies to 4 species: chickpea (Cicer arietinum L.), mungbean (Vigna radiata (L.) Wilczek), peanut (Arachis hypogaea L.), and lucerne (Medicago sativa L.). For each species, the key physiological parameters were derived from the literature and our own experimentation. The model was tested on an independent set of experiments, predominantly from the tropics and subtropics of Australia, varying in cultivar, sowing date, water regime (irrigated or dryland), row spacing, and plant population density. The model is an attempt to simulate crop growth and development with satisfactory comprehensiveness, without the necessity of defining a large number of parameters. A generic approach was adopted in recognition of the common underlying physiology and simulation approaches for many legume species. Simulation of grain yield explained 77, 81, and 70% of the variance (RMSD = 31, 98, and 46 g/m(2)) for mungbean (n = 40, observed mean = 123 g/m(2)), peanut (n = 30, 421 g/m(2)), and chickpea (n = 31, 196 g/m(2)), respectively. Biomass at maturity was simulated less accurately, explaining 64, 76, and 71% of the variance (RMSD = 134, 236, and 125 g/m(2)) for mungbean, peanut, and chickpea, respectively. RMSD for biomass in lucerne (n = 24) was 85 g/m(2) with an R-2 of 0.55. Simulation accuracy is similar to that achieved by single-crop models and suggests that the generic approach offers promise for simulating diverse legume species without loss of accuracy or physiological rigour.

The design of a mobile weigh bin for use in field trials is described. The bin is designed for accurate weighing of peanut yield (pods) from large-scale (1 t) on-farm trials. It can be used with most commercially available peanut threshers and unloads pods quickly into transport trucks, resulting in minimal delay to a farmer's harvesting program.

SummaryGroundnut productivity is low in the semi‐arid tropics mainly because of drought caused by low and erratic rainfall. Genotypes that have ability to use limited available water efficiently are required to enhance productivity of the crop. In groundnut, water use efficiency (WUE) is correlated with specific leaf area (SLA). The latter can be used as a surrogate trait for selecting for WUE. Partitioning of assimilates as measured by the harvest index (HI) has the greatest effect on pod yield. In order to improve SLA and in turn WUE and HI, a good knowledge of genetic systems controlling the expression of these traits is essential for the choice of an efficient breeding procedure. This study was conducted to investigate inheritance of SLA and HI in three crosses involving Chico, TMV 2 NLM, and ICGV 86031 groundnut genotypes. The study included parents, F1, F2, and backcross generations. Generation means analysis indicated that the additive effects were more important than the dominance effects in the expression of SLA and HI. In addition to additive and dominance effects, additive × additive type of epistasis, which can be fixed in groundnut (a self pollinated crop), was also significant for SLA in all the three and for HI, in two crosses. The selection for SLA and HI can be effective in early generations in some crosses and to exploit the additive × additive type of interaction, it can be done in large populations of later generations.

The present study investigates the potential use of a hand‐held portable SPAD chlorophyll meter for rapid assessment of specific leaf area (SLA) and specific leaf nitrogen (SLN), which are surrogate measures of transpiration efficiency (TE) in peanut (Arachis hypogaea L.). The effects of sampling (leaf position, time of sampling and leaf water status) and climatic factors (solar radiation and vapour pressure deficit, VPD) on SLA and SPAD chlorophyll meter reading (SCMR) were studied in a range of peanut genotypes grown under field and greenhouse conditions. The correlation between SLA and SCMR was significant (r=−0.77, P < 0.01) for the second leaf from the apex but the correlation declined for leaves sampled from lower nodal positions. The diurnal fluctuation in SLA ranged from −20 % to +10 %, whereas SCMR was relatively unaffected by these diurnal changes. Solar radiation and VPD during the sampling period had a significant influence on the relationship between SLA and SCMR, largely through their effects on SLA. However, standardization of SLA for these environmental factors significantly improved the relationship between SLA and SCMR from −0.50 to −0.80 (P < 0.01), suggesting that, when protocols for leaf sampling and SLA measurements are followed, SCMR can be a surrogate measure of SLA. There were significant relationships between SLN and SCMR (r=0.84, P < 0.01) and SLN and SLA (r=−0.81, P < 0.01). These significant interrelationships amongst SLA, SLN and SCMR suggested that SCMR could be used as a reliable and rapid measure to identify genotypes with low SLA or high SLN (and hence high TE) in peanut.

Plant breeders spend considerable time, effort and expense in conceptualizing and selecting for improved plant types. Given the climatic variability and diverse management practices in different regionsto which crops are exposed, different plant types may be needed for different agro-ecological zones. By capturing physiological understanding in a predictive framework, crop modelling offers the potential to interpret and predict the performance of individual genotypes in different environments, thus offering a possible decision support role in plant breeding. We propose that, when considering the adaptation of food legumes to the environments in which they are growing, the impact on the whole system should evaluated, including the N economy of the cropping system and impacts on the productivity of associated crops. We present some case studies of the use of static analytical models and simulation to evaluate traits in food legumes, from a cropping systems perspective. In one case study we show that the yield difference between determinate and indeterminate soybean types in this semi-arid environment will depend upon interactions between seasonal conditions, flowering date and starting soil water, which models can assist in analysing. Conducting analyses over the climatic record also allows any yield advantage to be assessed against the impact on the riskiness of production. In another study, we highlight the interaction between agronomic management (such as row spacing) and the performance of cowpea genotypes differing in height and leaf posture when grown as intercrops with maize. In a third case study we address the question of the impact of chickpea genotypes differing in potential N fixation on system performance of a chickpea-wheat rotation under dryland conditions. The results show the trade-off between the gains or losses in chickpea and wheat yields by introducing chickpea with different traits into the rotation. In summary, the case studies are intended to demonstrate that breeding objectives often need to incorporate the impact of altered plant traits beyond the yield of the targeted crop and the interaction of management and climate on the differential performance of genotypes. This is particularly the case for food legume crops which are typically grown as important components of crop rotations.

Data from studies of growth and development, and response to plant density in common groundnut (Arachis hypogaea) cultivars were examined from published studies. Data were available from the humid tropics of Indonesia, the semi-arid tropics of north-west Australia and the humid coastal and inland elevated areas of north-east Australia. Temperature and irradiance played a major role in determining crop duration, individual plant size and partitioning of dry matter to pods across environments, and these plant characteristics provided the major determinants of pod yield and response to plant density. Crop duration was shortest in humid tropical and subtropical environments, with both high and low temperatures apparently delaying crop maturity. A relatively small individual plant size in humid tropical environments was due to a combination of low incident irradiance and short duration, with very high plant densities needed to maximize dry matter production. The progressive decline in harvest indices in more tropical environments was due to a decline in pod numbers per plant. Although increased plant density resulted in greater numbers of pod initials in the humid tropics, a high proportion of these pods did not contain developed seeds and pod yield at high densities remained relatively low at ≤2.5 t ha−1.

Current phenotrp models utilized by plant breeders partition traits, such as reproductive yield 0,in to the 'statistical' components of genetic (G), environ. mental (E), and genotype by environment (GxE) interaction. Raits such as yield commonly have large GxE interaction tern. Breeders often have little information concerning the physiological basis of this GxE interaction, thw laving them without a clear idea of how to lunher exploit the material. Better lrnowlrdge of the physiological basis for the differential rrsponra of genotypes to spfiflc environments should improve the efficiency with which the breeder w charaeterlze material for its G, and GxE interaction, and hence increase thespeed at which superior gnotypes can be identified

Because of its relationship with water‐use efficiency (W), carbon isotope discrimination in leaves (Δ) was proposed to be useful for identifying genotypes with greater water‐use efficiency. In this study we examined the relationship between W and Δ in four peanut (Arachis hypogaea L.) genotypes. The genotypes were grown in and around mini‐lysimeters embedded in soil and were subjected to two drought regimes, intermittent and prolonged water deficit conditions, by varying the irrigation timing and amount. Automated rain‐out shelters prevented any rain from reaching the experimental plots during the treatment period. The mini‐lysimeters allowed accurate measurement of water use and total dry matter (including roots) in a canopy environment. Water‐use efficiency, which ranged from 1.81 to 3.15 g kg−1, was negatively correlated with Δ, which ranged from 19.1 to 21.8%. Tifton‐8 had the highest W (3.15 g kg−1) and Chico the lowest (1.81 g kg−1, representing a variation in W of 74% among genotypes. Variation in W arose mainly from genotypic differences in total dry matter production rather than from differences in water use. It is concluded that δ is a useful trait for selecting genotypes of peanut with improved W under drought conditions in the field. A strong negative relationship existed between W and specific leaf area (SLA, cm3 g−1) and between Δ and SLA, indicating that genotypes with thicker leaves had greater W. SLA could therefore be used as a rapid and inexpensive selection index for high W in peanut where mass spectrometry facilities are not available.

The allocation pattern of leaf nitrogen throughout a crop canopy can theoretically affect crop photosynthetic performance and radiation use efficiency (RUE). No information is available on the existence of leaf nitrogen gradients in peanut (Arachis hypogaea L.) canopies, nor on how these gradients might impact on RUE. Peanut crops (cv. Tifton-8) were grown in warm and cool environments, and the canopy profiles of leaf area index, light interception, specific leaf weight (SLW), leaf nitrogen concentration (LNC) and specific leaf nitrogen (SLN) were examined at 73 and 112 days after planting. Crop RUE was also measured during this period.There was a marked decline in SLN from the top to the base of the canopy in both environments. The gradient in SLN occurred due to changes in SLW and LNC in the warm environment, but only due to changes in SLW in the cool environment. The gradient appeared to be largely controlled by the light environment within the canopy, as evidenced by the commonality (across environments) of the relationship between SLN and cumulative light interception throughout the canopy.Radiation use efficiency was 33% higher in the crop grown in the warm compared to the cool environment, suggesting that cool temperatures can limit RUE in peanut. For the crop at the warm site, RUE was 32% higher than the theoretical RUE assuming a uniform SLN distribution in the canopy. It is suggested that the existence of non-uniform SLN distribution in the canopy may allow enhanced RUE compared to canopies with uniform SLN distribution.

The contribution of symbiotic N2 fixation to the total N budget of irrigated crops of peanut (Arachis hypogaea L.) during vegetative and reproductive growth was investigated using four peanut cultivars with differing patterns of dry matter (DM) partitioning to developing pods. Estimates of NZ fixation were obtained with the 15N natural abundance procedure by using a non-nodulating peanut genotype as a non-N2-fixing reference plant. Partitioning was assessed on the basis of vegetative DM equivalents, with adjustments to pod DM based on relative synthesis costs of vegetative and pod DM. Cultivars differed in crop duration, DM production and yield of pods and kernels. Despite large differences in derived DM partitioning coefficients among cultivars (0.68 to 1.03), both total crop N and fixed N increased as a constant proportion of accumulated, energy-adjusted DM. Crop duration was the primary factor determining both total crop N and fixed N. In addition to fixation, all cultivars continued to accumulate soil mineral N throughout the season. However, in all cultivars except TMV-2, crop N uptake during reproductive growth was insufficient to meet the demands of developing pods and N was renlobilized from vegetative plant parts. Remobilized N was almost exclusively N derived originally from N2 fixation. Despite relatively high levels of N2 fixation (from 140 to 210 kg N ha-1, depending on crop duration), all cultivars except Virginia Bunch showed a negative apparent N balance when the amounts of N2 fixed were compared to N removed in pods at final harvest. This was primarily due to high N harvest indices (0.62 to 0.73), and is likely to be a feature of many recently released, high yielding cultivars.

Radiation use efficiency (RUE) of well-watered crops, measured as grams of biomass accumulated for each megajoule of intercepted total solar radiation, is affected by the level of leaf nitrogen in the canopy and has been related to the canopy specific leaf nitrogen (SLN; g N m-2 leaf area). A number of field experiments on peanut have measured RUE values greater than current theories predict on the basis of their canopy SLN levels. It is possible that these discrepancies between measured and theoretical values may be caused by non-uniform distribution of SLN in the canopy, incident radiation level, and/or the influence of diffuse radiation. In this study, we developed a theoretical framework to predict the consequences of these factors on RUE in peanut and used it to explain the causes of discrepancies between theory and practice. The framework is structured to determine photosynthesis of a layered crop canopy by distributing incident radiation among sunlit and shaded leaves in each layer. It allows for variation in incident direct and diffuse radiation associated with location (latitude), time of year, time of day, and atmospheric condition, which is expressed as the degree of transmission of extra-terrestrial radiation. It also allows for variation in photosynthetic capacity associated with average SLN of the canopy and its distribution in the canopy. Daily canopy photosynthesis, intercepted radiation, and RUE are obtained by numerical integration of instantaneous values calculated at specific times of the day. The framework predicted experimentally determined RUE values accurately and quantified the contribution of each major factor to variation in RUE. On clear days, with high canopy SLN, RUE was predicted to be 1.l g MJ-1. The major cause of previous underestimation of RUE was found to be variation in RUE associated with the level of incident radiation flux density as affected by the degree of atmospheric transmission. RUE increased by up to 0.4 g MJ-1 as atmospheric transmission decreased from 0.75 (clear sky) to 0.35 (heavy cloud). However, varying incident radiation by changing time of year or latitude did not affect RUE. Partitioning incident radiation into direct and diffuse components and consideration of canopy gradients in SLN both had significant effects on RUE, but of a lesser magnitude than effects of degree of atmospheric transmission. The former caused increases in RUE of up to 0.15 g MJ-l, while the latter caused increases of up to 0.13 g MJ-1 at low canopy SLN. Hence, by quantifying the understanding of plant physiological processes and integrating appropriately to the canopy scale, this theoretical framework has explained the causes of discrepancies between measured RUE and previous theoretical estimates.

Two peanut cultivars of different botanical type (Virginia and Spanish) were grown at 3 plant population densities (40000, 120000 and 240000 plants/ha) and relied solely on stored soil water in a deep kraznozem soil for water requirements. Protracted crop water deficits occurred from flowering to maturity. Plant population influenced both the temporal and spatial patterns of water use, with high density crops extracting water from lower depths sooner than low density crops. Higher water use prior to early podfilling in high density crops was associated with more rapid leaf area development.Reproductive development was strongly influenced by plant population density, with more pods per M2 in low than in high density crops. Lower leaf water potential and individual leaf photosynthetic rates in the middle of the day during the pegging and early podding phase suggested that high crop water deficits had lowered assimilate availability and reduced reproductive potential in high, compared with low, density crops.The results indicate that there is scope for increasing pod yield when peanut is growing solely on stored water, by reducing plant population. The timing of water use, as distinct from the amount of water used, was the major determinant of pod yield.

PEANUTS are grown under a variety of cropping systems throughout Indonesia and Australia where both protracted and/or intermittent drought stress limit growth and pod yield. The detrimental effects of drought can be modified to some extent through such management options as supplementary irrigation, manipulations in either maturity type or planting date, and intercropping differing maturity cultivars. Increases in pod yield under water-limited conditions are possible also through the identification and selection of cultivars better able to resist and/or adapt to such drought effects. Unfortunately, selection for drought resistance/tolerance has proved difficult in breeding programs because of the need to test large numbers of genotypes in multiple seasons and locations. Large costs in space, time and resources mean that selection for characters other than pod yield at maturity is not feasible. More detailed understanding of the developmental and physiological adaptations enabling superior performance of genotypes under drought stress is therefore needed to identify reliable indices of drought resistance/tolerance. Selection for these traits should complement conventional breeding programs and lead to more efficient use of time and resources.

The effects of plant population density on total dry matter (TDM) production, and on pod and kernel yields, of 2 peanut (Arachis hypogaea L.) cultivars (Virginia and Spanish) were investigated under a range of contrasting soil water availability regimes. Protracted crop water deficits were applied to each plant population density treatment in 3 experiments: (i) from planting until the early pod-filling phase (DSWF, dry start, wet finish); (ii) during the pod-filling to maturity phase (WSDF, wet start, dry finish); (iii) from flowering to maturity (TS, terminal stress). Crop water deficits of varying timing and severity were shown to modify substantially the effect of plant population on yield response compared with that observed under well-watered conditions. In most cases, TDM was maximised at the lowest density (40000 Plants/ha). In the WSDF and DSWF experiments, significant cultivar x plant population interactions for pod yield were found. The Spanish cultivar, McCubbin, showed strong pod yield response to S30000 plants/ha, while the Virginia cultivar, Early Bunch, did not respond to increases in plant population above 40000 plants/ha. These differing responses were probably associated with cultivar differences in branching pattern. Under extreme water stress situations where crops were forced to rely solely on soil water reserves (TS), pod yields were highest at the lowest plant population density and declined rapidly as plant population increased. The Gardner and Gardner (1983) model provided a useful framework to characterise the plant population-pod yield response under reduced water availability. The assumptions that both partitioning of dry matter to pods and the hypothetical minimum plant size capable of producing pods were crop constants, irrespective of crop water deficits experienced, were shown to be invalid. These constants may, however, be linearly related to water availability. Relationships relating these parameters to an index of crop or soil water status may improve the predictive capability of the model under water-limited conditions.