Context. To increase cereal production, primary producers want to know the amount of fertiliser that needs to be applied to achieve high yield. To calculate the critical soil test value (CSTV) especially in Colwell-P, several models were found in the literature. The arcsine-log calibration curve has been commonly used in Australia to estimate the CSTV. However, this method has some mathematical weaknesses, which tend to give underestimated values for CSTV.

Aim. In this paper, we describe the mathematical issues and propose a model to overcome these issues. The simplified model proposed allows us to estimate the CSTV and its standard error.

Method. We have applied the regression and the delta method to the data used in the arcsine-log calibration curve (ALCC) method.

Key results. Based on the given data, a soil test value of 31.5 mg P kg⁻¹ soil is required to achieve 90% relative yield of wheat, which is the middle ground of previously published critical values between the underestimate (21.4 mg kg⁻¹) generated by the ALCC algorithm and the overestimate (40 mg kg⁻¹) generated by the conventional Mitscherlich method.

Conclusions. Advantages of this method are: (1) simple to apply to any data sets; and (2) easy to incorporate other covariates into the models. This method should be applied for computing estimates of CSTV and its standard error because it overcomes the contentious issue of the division of the y-axis by the correlation coefficient.

Implication. The proposed method should replace the ALCC algorithm and the current P values used in farming may need to be updated.

Chickpea (Cicer arietinum) is the third most significant grain legume grown in dry and semi-arid regions. Ensuring global food security necessitates sustainable practices, such as improving agricultural productivity with cultivars that provide increased yields and adaptability. The major limits on chickpea production are poor genetic diversity, low and variable yield, and vulnerability to biotic and abiotic stresses. Despite the abundance of germplasm accessions, their impact on improving chickpea genetics has been limited. Combining contemporary genomic resources with conventional breeding techniques holds the potential to develop climate-resilient chickpea varieties. To close the genome-to-phenome gap, contemporary genomic technology must be integrated with molecular breeding initiatives. Furthermore, major genetic resources, such as molecular markers and transcript sequences, have been identified. Recent advances in genomic methods and technologies have eased large-scale sequencing and genotyping in chickpea as well as in other crops. These tools are intended to help identify trait-specific germplasm, map phenotypes, and mine alleles for biotic and abiotic stress tolerance, as well as agronomic qualities. This review focuses on recent improvements that have opened new opportunities for establishing and screening breeding populations and tactics for improving selection efficiency and speeding genetic gain in chickpea.

Context. Green gram (Vigna radiata) is an important source of plant-based dietary protein. ‘Physical dormancy’ or ‘hardseededness’ is prevalent in many released varieties of green gram in India. Green gram seeds exhibit a variable proportion of hard seeds that do not imbibe water. Presence of hard seeds results in uneven germination, lower field emergence and leads to poor yield. Hardseededness is primarily attributed to thick impermeable seed coat, lignin content, and structural carbohydrates, which is controlled genetically as well as by prevailing environmental interactions.

Aim. To identify the major biochemical and growing conditions regulating the hardseededness in green gram.

Methods. Ninehard seeded (HS) and nine non-hard seeded (NHS) genotypes of green gram were evaluated for variation in hardseededness and physico-chemical parameters during two consecutive monsoon and summer season.

Key results. Hardseededness varied significantly between HS and NHS genotypes as well as between the growing seasons. Physico-chemical parameters like lignin content, cellulose, hemicelluloses, total phenol, and calcium content varied significantly among HS and NHS genotypes and also between monsoon and summer produced seeds.

Conclusions. Green gram genotypes produced in summer season exhibited lower proportion of hard seeds compared to those grown in the monsoon season. This may be due to higher atmospheric temperature at the time of seed maturity as well as relatively lower lignin, calcium, phenol, and structural carbohydrate content in varieties.

Implications. Our findings indicated that the summer season may be preferred over monsoon for production of quality seeds of identified hard seeded green gram varieties.

Context. Comparing the life cycles of wild and cultivated carrots is vital for identifying any overlapping flowering periods, as wild carrots have the potential to compromise the genetic purity of commercial carrot seeds via pollen flow. However, little information is known about how juvenility, vernalization, and their interactions impact the flowering pattern of wild and cultivated carrots in New Zealand.

Aims. We evaluated the influence of different juvenile phases, and vernalization phases on floral characteristics and flowering behaviour of cultivated and wild carrots.

Methods. The study was a factorial randomized complete block design with four blocks of five plants per block, incorporating treatments of different carrot genotypes (G₁, cultivated; G₂, wild carrots), juvenile phases (J₁, 12 weeks; J₂, 8 weeks; J₃, 4 weeks), and vernalization phases (V₁, 12 weeks; V₂, 4 weeks; V₃, no vernalization). Flowering percentage, flowering time, percentage of overwinter survival, and floral traits, including number of umbels and branches, and height of floral stem were recorded and analyzed by ANOVA.

Key results. Cultivated carrots flowered only when exposed to 12 weeks vernalization, while wild carrots have shown 100% flowering across all treatment combinations. Wild carrots exhibited a higher overwintering survival rate (94.9–100%) than cultivated carrots (66.1–98.3%). Prolonged exposure to vernalization significantly affected the floral traits of wild carrots.

Conclusions. There is a high likelihood of overlapping flowering periods between wild and cultivated carrots, as wild carrots can survive as both winter and summer annuals.

Implications. To avoid undesirable pollen flow during overlapping flowering periods of wild and cultivated carrots, we recommend timely weed management strategies to control wild carrots.