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In this paper, we present a procedure for implementing field-based high-throughput plant phenotyping (HTPP) that can be used in resource-constrained research programs. The procedure relies on opensource tools with the only expensive item being one-off purchase of a drone. It includes acquiring images of the field of interest, stitching the images to get the entire field in one image, calculating and extracting the vegetation indices of the individual plots, and analyzing the extracted indices according to the experimental design. Two populations of groundnut genotypes with different maturities were evaluated for their reaction to early and late leaf spot (ELS, LLS) diseases under field conditions in 2020 and 2021. Each population was made up of 12 genotypes in 2020 and 18 genotypes in 2021. Evaluation of the genotypes was done in four locations in each year. We observed a strong correlation between the vegetation indices and the area under the disease progress curve (AUDPC) for ELS and LLS. However, the strength and direction of the correlation depended upon the time of disease onset, level of tolerance among the genotypes and the physiological traits the vegetation indices were associated with. In 2020, when the disease was observed to have set in late in medium duration population, at the beginning of the seed stage (R5), normalized green-red difference index (NGRDI) and variable atmospheric resistance index (VARI) derived at the beginning pod stage (R3) had a positive relationship with the AUDPC for ELS, and LLS. On the other hand, NGRDI and VARI derived from images taken at R5, and physiological maturity (R7) had negative relationships with AUDPC for ELS, and LLS. In 2021, when the disease was observed to have set in early (at R3) also in medium duration population, a negative relationship was observed between NGRDI and VARI and AUDPC for ELS and LLS, respectively. We found consistently negative relationships of NGRDI and VARI with AUDPC for ELS and LLS, respect

Early Leaf Spot (ELS) caused by the fungus Passalora arachidicola and Late Leaf Spot (LLS) also caused by the fungus Nothopassalora personata, are the two major groundnut (Arachis hypogaea L.) destructive diseases in Ghana. Accurate phenotyping and genotyping to develop groundnut genotypes resistant to Leaf Spot Diseases (LSD) and to increase groundnut production is critically important in Western Africa. Two experiments were conducted at the Council for Scientific and Industrial Research-Savanna Agricultural Research Institute located in Nyankpala, Ghana to explore the effectiveness of using RGB-image method as a high-throughput phenotyping tool to assess groundnut LSD and to estimate yield components. Replicated plots arranged in a rectangular alpha lattice design were conducted during the 2020 growing season using a set of 60 genotypes as the training population and 192 genotypes for validation. Indirect selection models were developed using Red-Green-Blue (RGB) color space indices. Data was collected on conventional LSD ratings, RGB imaging, pod weight per plant and number of pods per plant. Data was analyzed using a mixed linear model with R statistical software version 4.0.2. The results showed differences among the genotypes for the traits evaluated. The RGB-image method traits exhibited comparable or better broad sense heritability to the conventionally measured traits. Significant correlation existed between the RGB-image method traits and the conventionally measured traits. Genotypes 73-33, Gha-GAF 1723, Zam-ICGV-SM 07599, and Oug-ICGV 90099 were among the most resistant genotypes to ELS and LLS, and they represent suitable sources of resistance to LSD for the groundnut breeding programs in Western Africa.

Tomato is an important component of every Ghanaian meal, and its cultivation contributes significantly to livelihood improvement. The demand for tomato in Ghana outstrips supply, and therefore local production is augmented by imports from neighbouring countries. Despite the importance of tomato in Ghana, past tomato-breeding programmes have been unsystematic and had not led to the development of new varieties that meet the needs of consumers as well as environmental stresses. This review outlined tomato production trends, constraints and past tomato improvement programmes in Ghana, which mainly focused on germplasm collection, morphological and agronomic characterization, molecular evaluation, diversity study, as well as screening germplasm against biotic and abiotic stresses. The established variability and the outcomes of the evaluations against the various biotic and abiotic stresses have not been utilized in the development of new varieties. This work will serve as a reference for developing future tomato-breeding programmes.

Tomato (Solanum lycopersicum L.) is the second most important vegetable crop in the world due to its high level of nutrition particularly in vitamins and antioxidants. It is grown in several ecologies of the world due to its adaptability and ease of cultivation. Besides field conditions, tomatoes are grown in controlled environments which range from hydroponics and simple high tunnel structures to highly automated screen houses in advanced countries. However, the yield and quality of the fruits are highly influenced by the environment. This results in unpredictable performances in different growing environments in terms of quality, a phenomenon known as genotype by environment (G × E) interaction which confounds selection efficiency. Various approaches are employed by plant breeders to evaluate and address the challenges posed by genotype by environment interaction. This chapter discusses various field and controlled environments for growing tomatoes and the effect of these environments on the performance of the crop. The various types of genotype × environment interactions and their effect of the tomato plant are discussed. Finally, efforts are made to suggest ways and methods of mitigating the confounding effects of genotype × environment interaction including statistical approaches.

Marker-assisted selection (MAS) is a complementary tool for conventional breeding where a molecular marker linked to a trait is indirectly selected. Many studies conducted have been able to identify and develop markers for traits such as disease and pest resistance and other abiotic stresses. Despite the availability of these markers, the technology has been extensively used in tomato breeding for the identification of some economic traits in particular disease resistance. In developed countries, MAS is utilized routinely in breeding programs, but this cannot be said for developing countries such as Africa. It is high time Africa as a continent looks at the importance of the technology and invests in it. In addition to MAS, other strategies such as marker-assisted backcrossing and recurrent selection have also been employed for breeding in tomato. The use of MAS in crop improvement will not only reduce the cost of developing new tomato varieties but will also increase the precision and efficiency of selection in the breeding program as well as lessen the number of years required to come up with a new crop variety.