1. Introduction
Yam (
Dioscorea spp.) is a major strategic crop for sustainable food production in Africa, given its superior productivity compared to other crops [
1]. It is an important tuber crop with major food, commercial and socio-cultural values.
Dioscorea alata is the most widely cultivated species globally, but ranks second to
Dioscorea rotundata with respect to yam quantity produced in Africa [
2]. The significance of yam in terms of production volume and value cannot be over-emphasized. Africa accounts for over 95% of the world’s annual production of about 49 million tons [
3]. This is mostly produced within the yam belt region in West Africa, which includes Benin, Ghana, Ivory Coast, Nigeria and Togo, with Nigeria as the world’s leading yam producer, accounting for more than 65% of worldwide production (72.6 million tonnes) [
3]. Within the yam belt, over 60 million people are directly involved in yam production [
4]. Yam is, therefore, an economically important part of the Gross Domestic Product (GDP) of these top producers and exporters in West Africa. For instance, Ghana’s yam exports between 2017 and 2018 increased to USD 5.4 million [
5] from USD 3.4 million.
Yams are widely used as an important food staple and fallback crop in Africa, Asia, the Caribbean, the Pacific Islands and South America [
6]. Significantly, yams are essentially carbohydrate foods that are laden with valuable nutrients including relatively high protein, fats, ascorbic acid (Vitamin C), and dietary fiber levels [
7]. Yams are also low in saturated fat and sodium [
8]. The yam tuber is a rich source of minerals including copper, calcium, potassium, iron, manganese and phosphorus. A 100 g serving of yam tuber provides about 816 mg of Potassium [
9]. Its high potassium and low sodium balance help to control blood pressure and offer protection against osteoporosis and heart disease. Yam products have a lower glycemic index than potato products, thus providing a more sustained form of energy and better protection against obesity and diabetes [
9]. The proximate composition of edible yam tubers includes water (65 to 75%), protein (1 to 2.5%), fat (0.05 to 0.20%), and carbohydrates which are mainly starch (15 to 25%), as well as fiber (0.5 to 1.5%), and ash (0.7 to 2.0%) [
10]. Yams also contain 8 to 10 mg/100 g of ascorbic acid, most of which is retained during cooking [
7]. Yams are a rich source of vitamin B6, which is useful in reducing the risk of heart disease.
Yam cultivation is best suited to humid and sub-humid lowlands. The most suitable agro-ecological zones for yam production (also called yam agroecology) are deciduous forest and savannah areas [
4], and there is evidence of strong genotype and environment interaction effect [
11]. Thus, multi-location trials are important in yam breeding programs to enable the identification of genotypes with desired performance for broad or particular adaptation [
12]. Stable genotypes are those that show minimal genotype-by-environment interaction across environments [
13,
14].
There exists limited scientific information and data on yams in Eastern Africa [
7]. In Uganda, yams are grown on small-scale farms, often intercropped in banana fields with crops such as coffee, cassava and cocoyam, or as individual plants grown against trees for support. Yams are also mono-cropped on relatively large plots in eastern, northern and north-western Uganda where it has widespread importance [
15]. The crop plays a vital role in smallholder farmers’ livelihoods, particularly in densely populated areas of central, northern, north-western, and eastern Uganda. Yams have become an important cash crop in many parts of Uganda, allowing farmers to earn income from local and cross-border markets. In Uganda, yams are grown within the broad altitude range of 1140 to 2200 masl and wide range of soils, although mainly in clay, clay loam, sandy and sandy loam types [
16]. In most parts of Uganda, yams are planted in March or April and harvested during November and December.
A better understanding of target environments is essential for a yam breeding effort that is committed to developing and identifying improved genotypes which are superior in terms of production, tuber quality and utilization potential [
17]. Hyman et al. [
18] emphasized that target environments composed of a set of farms and seasons are often highly variable and may be the cause of differential phenotypic expressions of plants within a crop under cultivation. Moreover, a major factor limiting efficiency of plant breeding programs is the connection of plant phenotypic expression. This generally depends on the environment and genotype-by-environment interaction (GEI) [
19], which influences the nature, magnitude and predictability of selection. Although GEI poses a big challenge to breeding program efficiency, it cannot be ignored but could instead be exploited [
17]. Characterizing and defining target sets of environments (TSE) for breeding and cultivar recommendation are among the strategies to exploit space and time dimensions of GEI. Environmental profiling helps strategically to locate experimental or selection sites, with greater power in predicting performance of breeding trials.
In this study, environments for yam cultivation were defined based on their cultivation methods, farmers’ preferences and the cultivar produced. This helps to understand the distribution and zoning of yam cultivars in Uganda. Several studies have reported a strong genotype and environment interaction (GEI) in yam [
20]. A stability study by Otoo et al. [
2] of seven white yam genotypes in 13 environments in Ghana [
21] showed that genotypes accounted for 8.9%, environment 30.8%, and genotype-by-environment (G × E) 43.7% of the total variation. It was concluded that yam improvement, therefore, should be focused on multiple disease and pest resistance, and performance guaranteeing crop performance stability. Regarding disease incidence, severity, and environmental effects, Pinnschmidt and Hovmøller [
22] explain that one major problem frequently encountered in deploying resistant host plants for disease control is the plasticity of phenotypic expression of resistance across different environments, due to interactions between host genotypes and environment. Earlier reports attributed variation in yam yield performance to inherent genotypic characteristics and preferences for different environmental conditions [
2,
14]. Therefore, careful evaluation is critical for identifying suitable genotypes to give the highest possible yield in different environments [
20]. High yield and stability of genotypes across different environments are very important attributes desired by plant breeders. As a result, breeding materials require testing in diverse environments to assess consistency in genotypic performance, to identify superior varieties for wider or specific adaptation [
23]. Genotypes are considered stable when their genotype-by-environment interaction effect remains insignificant from one environment to another and across years [
24].
The principal aim of our study was to evaluate the effect of genotype-by-environment interaction on yam mosaic virus disease, tuber yield and dry matter content of yam genotypes in six test environments within Uganda. In addition, we examined the magnitude of genotype-by-environment interaction and report yam performances for traits studied in different Ugandan agro-ecologies.
4. Discussion
The overall goal of this study was to evaluate the performance of Ugandan yam genotypes across six test environments for yield, viral disease resistance, and dry matter content. The significant variation expressed in mosaic virus resistance, total yield of yam, and dry matter content of genotypes presents an important opportunity for yam breeding in Uganda. This variability could serve as the foundation for making progress in the genetic improvement of yams via selection for these traits. In this study, genotype × environment effects were highly significant for all traits studied, indicating significant variation in genotype mean performance across environments, which had a significant impact on the studied genotypes. The high genotype-by-environment interaction effect on the several traits suggests that selection for these traits can be effectively achieved by evaluating genotypes in different target environments. Tuber yield and dry matter content in yam, like other quantitative traits, are strongly impacted by genotype–environment interaction [
14,
21]. This characteristic makes it difficult for the selection of such genotypes for universal adaption. According to Nduwumuremyi et al. [
39], the existence of a strong genotype–environment interaction for quantitative variables like tuber yield, dry matter content, and yam mosaic virus might hinder efforts to choose superior genotypes for diverse environments. This is because such performance cannot be duplicated in environments with varying environmental conditions [
40].
Different yam genotypes have intrinsic varietal traits and preferences for various environmental conditions [
21], particularly introduced genotypes in new environments [
41]. As a result, genotypes must be assessed across several locations to discover specific places where they best fit, and where they may achieve their maximum yield potential [
14]. This means that a standard yam variety selection approach for traits such as high dry matter content, high tuber yield, and yam mosaic virus resistance requires additional environments for screening resistance [
2]. Breeders can use stability analysis to measure the level of genotype by environment interaction and classify genotypes as widely or narrowly adapted, based on stability indices [
42]. As a result, breeding programs in Uganda that are aimed at developing yams for the above qualities should subject genotypes to multilocational assessment, with an emphasis on traits that are heavily impacted by environmental variables. Although this technique is more expensive, it provides greater precision in determining the top-performing genotypes in terms of dry matter content, tuber yield, and yam mosaic virus resistance.
The genotype main effect and genotype × environment (GGE) biplot depicts the genotypes’ overall effect as well as genotype × environment interaction [
43]. The “
which−won−where” pattern of the GGE biplot’s polygon view-based interaction is effective for identifying elite genotypes in single or multiple settings [
36,
38]. The use of GGE biplots in this work identified genotypes that coupled high mean performance with high stability, as well as highlighting preferences and adaption to particular situations. In terms of dry matter content, genotype UGY16069 was best suited to the Arua 2021 environment, whereas genotype UGY16003 performed best in Serere 2020. Genotype UGY16054, on the other hand, was well adapted to four environments: Namulonge 2020, Namulonge 2021, Arua 2020, and Serere 2021. Nonetheless, the ranking GGE biplot revealed that genotype UGY16071 performed best overall, despite being rather unstable across the test conditions. However, genotype performance for total weight of yam indicated that UGY16034 was the best performer although unstable, whereas genotype UGY16020 was primarily suited to two environments, Serere 2021 and Serere 2020. Other genotypes were adapted to a single environment, such as UGY16085 in Namulonge 2021, whereas genotype UGY16034 performed particularly well in three environments (Arua 2020, Namulonge 2020, and Arua 2021). A similar outcome was observed for yam mosaic virus, where the most common vertex genotypes were UGY16073, UGY16039, and UGY16003, identified as adapters for different environments. Earlier research on genotype × environment analyses also found this phenomenon of distinct adaptability or environmental preferences by various yam genotypes. In Ghana, in research comprising 12
Dioscorea rotundata genotypes in 16 settings, Otoo et al. [
2] used the GGE biplot to identify uniquely suited cultivars, validating the environmental uniqueness of distinct yam genotypes as per this current study.
According to Dhillon et al. [
44], a genotype is deemed stable if its yielding ability varies little when planted in different conditions. Yan and Tinker [
36] and Gurmu et al. [
45] suggested that stable genotypes are those whose variances remain largely consistent from one environment to the next. A persistently underperforming genotype, on the other hand, may also be stable. Nonetheless, in addition to greater performance for an attribute of interest, stability should always be addressed. According to a report by Purchase et al. [
46], a yield stability index that combined rankings for high yield and stability (based on the AMMI stability value) can reveal genotypes that are stable across environments [
47]. According to the findings of this study, genotype UGY16022 was stable but not the best performer in terms of yam mosaic virus severity score across all contexts. Furthermore, for total yield, genotype UGY16070 was the worst performer, although it was relatively stable compared to other genotypes. For dry matter content, genotype UGY16071 was the best performer but very unstable across the six test environments. For total yield of yam, genotype UGY16070 was the least impressive performer, though it was relatively stable compared to other genotypes. This shows that the genotype (UGY16070) responded positively to favorable environmental conditions and performed well under less favorable settings, implying particular adaptation characteristics.
Yam mosaic viruses have been reported to be widespread in all yam-producing countries around the world. The observed strong negative correction of yam mosaic virus with yield in the current study was desirable since healthy plants produce optimum assimilates which are translocated to the root and stored in tubers as starch [
48]. This suggests that the tuber yield can be increased by simple selection of healthy plants. Adeniji et al. [
49] observed that tuber yield in white yam could be reduced up to 92.8% after inoculation with yam mosaic virus. Yam plants infected with yam mosaic virus become unhealthy and chlorotic, and these plants do not produce optimally due to distorted chlorophyll content [
50]. However, a positive correlation was observed for the relationship between dry matter content and yam mosaic virus.
Certain types of genotypes would be ideal for high-input agriculture under favorable environmental circumstances. The optimal temperature for the growth of yam is between 25 °C and 30 °C, depending on the species. The average annual temperature for the test environments ranged from 18.8 °C to 29.2 °C which is within the range of the optimal temperature required for yam growth and development during the crop growing period. According to Srivastava et al. [
51], nitrogen stress serves as the most serious growth constraint for yam production and they strongly recommend the necessity of including this management factor in the assessment of climate impacts on crop yields. In the current study, the test environments were within the range of critical nutrient requirements for yam. Literature defines certain genotypes as being resistive to environmental situations, and they continue to be the best insurance for farmers under difficult situations. Furthermore, certain genotypes tend to respond well to favorable environments while maintaining moderate yields, dry matter content, and disease resistance under hard conditions. Such genotypes are often chosen for specific settings where they may fully realize their production potential. The yields of locally cultivated genotypes such as UGY16085 and UGY16012 remained highest in the current investigation, despite being unstable across the six environments. The dry matter content of genotypes UGY16022 and UGY16064, on the other hand, remained considerably high across environments, while disease-resistant genotypes throughout the six test environments were UGY16020, UGY16034, UGY16042, and UGY16080. This was obviously reflected in the performance of the genotypes across the various environments. Further, similar observations were drawn from the relationship between dry matter content and total yield of yam where a non-significant weak negative correlation was observed.