962 resultados para Winter Wheat


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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.

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Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

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Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

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Salinity, sodicity, acidity, and phytotoxic levels of chloride (Cl) in subsoils are major constraints to crop production in many soils of north-eastern Australia because they reduce the ability of crop roots to extract water and nutrients from the soil. The complex interactions and correlations among soil properties result in multi-colinearity between soil properties and crop yield that makes it difficult to determine which constraint is the major limitation. We used ridge-regression analysis to overcome colinearity to evaluate the contribution of soil factors and water supply to the variation in the yields of 5 winter crops on soils with various levels and combinations of subsoil constraints in the region. Subsoil constraints measured were soil Cl, electrical conductivity of the saturation extract (ECse), and exchangeable sodium percentage (ESP). The ridge regression procedure selected several of the variables used in a descriptive model, which included in-crop rainfall, plant-available soil water at sowing in the 0.90-1.10 m soil layer, and soil Cl in the 0.90-1.10 m soil layer, and accounted for 77-85% of the variation in the grain yields of the 5 winter crops. Inclusion of ESP of the top soil (0.0-0.10 m soil layer) marginally increased the descriptive capability of the models for bread wheat, barley and durum wheat. Subsoil Cl concentration was found to be an effective substitute for subsoil water extraction. The estimates of the critical levels of subsoil Cl for a 10% reduction in the grain yield were 492 mg cl/kg for chickpea, 662 mg Cl/kg for durum wheat, 854 mg Cl/kg for bread wheat, 980 mg Cl/kg for canola, and 1012 mg Cl/kg for barley, thus suggesting that chickpea and durum wheat were more sensitive to subsoil Cl than bread wheat, barley, and canola.

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The authors overview integrated pest management (IPM) in grain crops in north-eastern Australia, which is defined as the area north of latitude 32°S. Major grain crops in this region include the coarse grains (winter and summer cereals), oilseeds and pulses. IPM in these systems is complicated by the diversity of crops, pests, market requirements and cropping environments. In general, the pulse crops are at greatest risk, followed by oilseeds and then by cereal grains. Insecticides remain a key grain pest management tool in north-eastern Australia. IPM in grain crops has benefited considerably through the increased adoption of new, more selective insecticides and biopesticides for many caterpillar pests, in particular Helicoverpa spp. and loopers, and the identification of pest-crop scenarios where spraying is unnecessary (e.g. for most Creontiades spp. populations in soybeans). This has favoured the conservation of natural enemies in north-eastern Australia grain crops, and has arguably assisted in the management of silverleaf whitefly in soybeans in coastal Queensland. However, control of sucking pests and podborers such as Maruca vitrata remains a major challenge for IPM in summer pulses. Because these crops have very low pest-damage tolerances and thresholds, intervention with disruptive insecticides is frequently required, particularly during podfill. The threat posed by silverleaf whitefly demands ongoing multi-pest IPM research, development and extension as this pest can flare under favourable seasonal conditions, especially where disruptive insecticides are used injudiciously. The strong links between researchers and industry have facilitated the adoption of IPM practices in north-eastern Australia and augers well for future pest challenges and for the development and promotion of new and improved IPM tactics.

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We have tested the efficacy of putative microsatellite single sequence repeat (SSR) markers, previously identified in a 2-49 (Gluyas Early/Gala) × Janz doubled haploid wheat (Triticum aestivum) population, as being linked to partial seedling resistance to crown rot disease caused by Fusarium pseudograminearum. The quantitative trait loci (QTLs) delineated by these markers have been tested for linkage to resistance in an independent Gluyas Early × Janz doubled haploid population. The presence of a major QTL on chromosome 1DL (QCr.usq-1D1) and a minor QTL on chromosome 2BS (QCr.usq-2B1) was confirmed. However, a putative minor QTL on chromosome 2A was not confirmed. The QTL on 1D was inherited from Gluyas Early, a direct parent of 2-49, whereas the 2B QTL was inherited from Janz. Three other putative QTLs identified in 2-49 × Janz (on 1AL, 4BL, and 7BS) were inherited by 2-49 from Gala and were not able to be confirmed in this study. The screening of SSR markers on a small sample of elite wheat genotypes indicated that not all of the most tightly linked SSR markers flanking the major QTLs on 1D and 1A were polymorphic in all backgrounds, indicating the need for additional flanking markers when backcrossing into some elite pedigrees. Comparison of SSR haplotypes with those of other genotypes exhibiting partial crown rot resistance suggests that additional, novel sources of crown rot resistance are available.

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Root system characteristics are of fundamental importance to soil exploration and below-ground resource acquisition. Root architectural traits determine the in situ space-filling properties of a root system or root architecture. The growth angle of root axes is a principal component of root system architecture that has been strongly associated with acquisition efficiency in many crop species. The aims of this study were to examine the extent of genotypic variability for the growth angle and number of seminal roots in 27 current Australian and 3 CIMMYT wheat (Triticum aestivum L.) genotypes, and to quantify using fractal analysis the root system architecture of a subset of wheat genotypes contrasting in drought tolerance and seminal root characteristics. The growth angle and number of seminal roots showed significant genotypic variation among the wheat genotypes with values ranging from 36 to 56 (degrees) and 3 to 5 (plant-1), respectively. Cluster analysis of wheat genotypes based on similarity in their seminal root characteristics resulted in four groups. The group composition reflected to some extent the genetic background and environmental adaptation of genotypes. Wheat cultivars grown widely in the Mediterranean environments of southern and western Australia generally had wider growth angle and lower number of seminal axes. In contrast, cultivars with superior performance on deep clay soils in the northern cropping region, such as SeriM82, Baxter, Babax, and Dharwar Dry exhibited a narrower angle of seminal axes. The wheat genotypes also showed significant variation in fractal dimension (D). The D values calculated for the individual segments of each root system suggested that, compared to the standard cultivar Hartog, the drought-tolerant genotypes adapted to the northern region tended to distribute relatively more roots in the soil volume directly underneath the plant. These findings suggest that wheat root system architecture is closely linked to the angle of seminal root axes at the seedling stage. The implications of genotypic variation in the seminal root characteristics and fractal dimension for specific adaptation to drought environment types are discussed with emphasis on the possible exploitation of root architectural traits in breeding for improved wheat cultivars for water-limited environments.

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Flour yield quantitative trait loci (QTLs) were identified in 3 Australian doubled haploid populations, Sunco × Tasman, CD87 × Katepwa, and Cranbrook × Halberd. Trial data from 3 to 4 sites or years were available for each population. QTLs were identified on chromosomes 2BS, 4B, 5AL, and 6BL in the Sunco × Tasman population, on chromosomes 4B, 5AS, and 6DL in the CD87 × Katepwa population, and on chromosomes 4DS, 5DS, and 7AS in the Cranbrook × Halberd population. In the Sunco × Tasman cross the highest genetic variance was detected with the QTL on chromosome 2B (31.3%), in the CD87 × Katepwa cross with the QTL on chromosome 4B (23.8%), and in the Cranbrook × Halberd cross with the QTL on chromosome 5D (18%). Only one QTL occurred in a similar location in more than one population, indicating the complexity of the flour yield character across different backgrounds.

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Better understanding of root system structure and function is critical to crop improvement in water-limited environments. The aims of this study were to examine root system characteristics of two wheat genotypes contrasting in tolerance to water limitation and to assess the functional implications on adaptation to water-limited environments of any differences found. The drought tolerant barley variety, Mackay, was also included to allow inter-species comparison. Single plants were grown in large, soil-filled root-observation chambers. Root growth was monitored by digital imaging and water extraction was measured. Root architecture differed markedly among the genotypes. The drought-tolerant wheat (cv. SeriM82) had a compact root system, while roots of barley cv. Mackay occupied the largest soil volume. Relative to the standard wheat variety (Hartog), SeriM82 had a more uniform rooting pattern and greater root length at depth. Despite the more compact root architecture of SeriM82, total water extracted did not differ between wheat genotypes. To quantify the value of these adaptive traits, a simulation analysis was conducted with the cropping system model APSIM, for a wide range of environments in southern Queensland, Australia. The analysis indicated a mean relative yield benefit of 14.5% in water-deficit seasons. Each additional millimetre of water extracted during grain filling generated an extra 55 kg ha-1 of grain yield. The functional implications of root traits on temporal patterns and total amount of water capture, and their importance in crop adaptation to specific water-limited environments, are discussed.

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The effects of fertilisers on 8 tropical turfgrasses growing in 100-L bags of sand were studied over winter in Murrumba Downs, just north of Brisbane in southern Queensland (latitude 27.4°S, longitude 153.1°E). The species used were: Axonopus compressus (broad-leaf carpetgrass), Cynodon dactylon (bermudagrass 'Winter Green') and C. dactylon x C. transvaalensis hybrid ('Tifgreen'), Digitaria didactyla (Queensland blue couch), Paspalum notatum (bahiagrass '38824'), Stenotaphrum secundatum (buffalograss 'Palmetto'), Eremochloa ophiuroides (centipedegrass 'Centec') and Zoysia japonica (zoysiagrass 'ZT-11'). Control plots were fertilised with complete fertilisers every month from May to September (72 kg N/ha, 31 kg P/ha, 84 kg K/ha, 48 kg S/ha, 30 kg Ca/ha and 7.2 kg Mg/ha), and unfertilised plots received no fertiliser. Carpetgrass and standard bermudagrass were the most sensitive species to nutrient supply, with lower shoot dry weights in the unfertilised plots (shoots mowed to thatch level) compared with the fertilised plots in June. There were lower shoot dry weights in the unfertilised plots in July for all species, except for buffalograss, centipedegrass and zoysiagrass, and lower shoot dry weights in the unfertilised plots in August for all species, except for centipedegrass. At the end of the experiment in September, unfertilised plots were 11% of the shoot dry weights of fertilised plots, with all species affected. Mean shoot nitrogen concentrations fell from 3.2 to 1.7% in the unfertilised plots from May to August, below the sufficiency range for turfgrasses (2.8-3.5%). There were also declines in P (0.45-0.36%), K (2.4-1.5%), S (0.35-0.25%), Mg (0.24-0.18%) and B (9-6 mg/kg), which were all in the sufficiency range. The shoots in the control plots took up the following levels (kg/ha.month) of nutrients: N, 10.0-27.0; P, 1.6-4.0; K, 8.2-19.8; S, 1.0-4.2; Ca, 1.1-3.3; and Mg, 0.8-2.2, compared with applications (kg/ha.month) of: N, 72; P, 31; K, 84; S, 48; Ca, 30; and Mg, 7.2, indicating a recovery of 14-38% for N, 5-13% for P, 10-24% for K, 2-9% for S, 4-11% for Ca and 11-30% for Mg. These results suggest that buffalograss, centipedegrass and zoysiagrass are less sensitive to low nutrient supply than carpetgrass, bermudagrass, blue couch and bahiagrass. Data on nutrient uptake showed that the less sensitive species required only half or less of the nitrogen required to maintain the growth of the other grasses, indicating potential savings for turf managers in fertiliser costs and the environment in terms of nutrients entering waterways.

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We tested the capacity of several published multispectral indices to estimate the nitrogen nutrition of wheat canopies grown under different levels of water supply and plant density and derived a simple canopy reflectance index that is greatly independent of those factors. Planar domain geometry was used to account for mixed signals from the canopy and soil when the ground cover was low. A nitrogen stress index was developed, which adjusts shoot %N for plant biomass and area, thereby accounting for environmental conditions that affect growth, such as crop water status. The canopy chlorophyll content index (CCCi) and the modified spectral ratio planar index (mSRPi) could explain 68 and 69% of the observed variability in the nitrogen nutrition of the crop as early as Zadoks 33, irrespective of water status or ground cover. The CCCi was derived from the combination of 3 wavebands 670, 720 and 790 nm, and the mSRPi from 445, 705 and 750 nm, together with broader bands in the NIR and RED. The potential for their spatial application over large fields/paddocks is discussed.

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The APSIM-Wheat module was used to investigate our present capacity to simulate wheat yields in a semi-arid region of eastern Australia (the Victorian Mallee), where hostile subsoils associated with salinity, sodicity, and boron toxicity are known to limit grain yield. In this study we tested whether the effects of subsoil constraints on wheat growth and production could be modelled with APSIM-Wheat by assuming that either: (a) root exploration within a particular soil layer was reduced by the presence of toxic concentrations of salts, or (b) soil water uptake from a particular soil layer was reduced by high concentration of salts through osmotic effects. After evaluating the improved predictive capacity of the model we applied it to study the interactions between subsoil constraints and seasonal conditions, and to estimate the economic effect that subsoil constraints have on wheat farming in the Victorian Mallee under different climatic scenarios. Although the soils had high levels of salinity, sodicity, and boron, the observed variability in root abundance at different soil layers was mainly related to soil salinity. We concluded that: (i) whether the effect of subsoil limitations on growth and yield of wheat in the Victorian Mallee is driven by toxic, osmotic, or both effects acting simultaneously still requires further research, (ii) at present, the performance of APSIM-Wheat in the region can be improved either by assuming increased values of lower limit for soil water extraction, or by modifying the pattern of root exploration in the soil pro. le, both as a function of soil salinity. The effect of subsoil constraints on wheat yield and gross margin can be expected to be higher during drier than wetter seasons. In this region the interaction between climate and soil properties makes rainfall information alone, of little use for risk management and farm planning when not integrated with cropping systems models.

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Reduced supplies of nitrogen (N) in many soils of southern Queensland that were cropped exhaustively with cereals over many decades have been the focus of much research to avoid declines in profitability and sustainability of farming systems. A 45-month period of mixed grass (purple pigeon grass, Setaria incrassata Stapf; Rhodes grass, Chloris gayana Kunth.) and legume (lucerne, Medicago sativa L.; annual medics, M. scutellata L. Mill. and M. truncatula Gaertn.) pasture was one of several options that were compared at a fertility-depleted Vertosol at Warra, southern Queensland, to improve grain yields or increase grain protein concentration of subsequent wheat crops. Objectives of the study were to measure the productivity of a mixed grass and legume pasture grown over 45 months (cut and removed over 36 months) and its effects on yield and protein concentrations of the following wheat crops. Pasture production (DM t/ha) and aboveground plant N yield (kg/ha) for grass, legume (including a small amount of weeds) and total components of pasture responded linearly to total rainfall over the duration of each of 3 pastures sown in 1986, 1987 and 1988. Averaged over the 3 pastures, each 100 mm of rainfall resulted in 0.52 t/ha of grass, 0.44 t/ha of legume and 0.97 t/ha of total pasture DM, there being little variation between the 3 pastures. Aboveground plant N yield of the 3 pastures ranged from 17.2 to 20.5 kg/ha per 100 mm rainfall. Aboveground legume N in response to total rainfall was similar (10.6 - 13.2 kg/ha. 100 mm rainfall) across the 3 pastures in spite of very different populations of legumes and grasses at establishment. Aboveground grass N yield was 5.2 - 7.0 kg/ha per 100mm rainfall. In most wheat crops following pasture, wheat yields were similar to that of unfertilised wheat except in 1990 and 1994, when grain yields were significantly higher but similar to that for continuous wheat fertilised with 75 kg N/ha. In contrast, grain protein concentrations of most wheat crops following pasture responded positively, being substantially higher than unfertilised wheat but similar to that of wheat fertilised with 75 kg N/ha. Grain protein averaged over all years of assay was increased by 25 - 40% compared with that of unfertilised wheat. Stored water supplies after pasture were < 134mm (< 55% of plant available water capacity); for most assay crops water storages were 67 - 110 mm, an equivalent wet soil depth of only 0.3 - 0.45 m. Thus, the crop assays of pasture benefits were limited by low water supply to wheat crops. Moreover, the severity of common root rot in wheat crop was not reduced by pasture - wheat rotation.

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Root-lesion nematode (Pratylenchus thornei) is a serious pathogen of wheat in many countries. The International Triticeae Mapping Initiative (ITMI) population of recombinant inbred lines (RILs) was assessed for resistance to P. thornei to determine the chromosome locations of the resistance genes. The ITMI population is derived from a cross between the resistant synthetic hexaploid wheat W-7984 and a susceptible bread wheat cultivar Opata 85. Two years of phenotypic data for resistance to P. thornei were obtained in replicated glasshouse trials. Quantitative trait locus (QTL) analysis was performed using available segregation and map data for 114 RILs. A QTL on chromosome 6DS showed consistent effects for reduced nematode numbers (partial resistance) across years and accounted for 11% and 23% of the phenotypic variation. A second QTL for P. thornei resistance on chromosome 2BS accounted for an additional 19% and 5%. Restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) markers associated with the QTLs are physically located in regions rich in major genes at the distal ends of the short chromosome arms of 6D and 2B. SSR markers with potential for marker-assisted selection of P. thornei resistance effective in different genetic backgrounds have been identified.

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A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.