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Successful innovation requires employees to have intellectual and technical capacity. This study explored the effects of capacity building through educational learning, organizational training, and coaching on agricultural innovation. A sample of 142 operational-level agriculture scientists working within a public sector agricultural research organisation in Zimbabwe. Six key informants were also consulted. Descriptive statistics, factor analysis, principal component analysis (PCA), correlation analysis, and binary logistic regression analysis were employed. Results showed significant positive relationships between the variables stating that operational scientists receive adequate academic study opportunities from the research organisation and the one stating that they have relevant academic qualifications to help drive agriculture innovation (r = 0.421***). This reflects that once capacitated through educational learning, the employees gain the confidence and ability to innovate, which could be attributed to improved intelligence quotient (IQ). A significant positive relationship was also observed between the variables, stating that research employees required further training and that improving training would significantly improve innovation (r = 0.47***). Lastly, the variables, stating that direct supervisors offer adequate guidance to stimulate innovation positively correlated to the one stating that coaching has helped improve the operational staff's innovativeness (P = 0.493***). This implies that efforts being put in by supervisors significantly contribute to innovation. Budgetary constraints were the leading challenge mentioned by 90.1% of the sample. Notably, there is a critical need to improve physical training workshops, exposure visits, and short courses to enhance innovativeness, as revealed by more than 70% of the respondents. The study also suggests cost-effective strategies to enhance capacity building and consequently stimulate innovation.

Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe’s Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28–35 kg ha-1 yr-1), under high-yield potential environments (17–61 kg ha-1 yr-1), and under low-yield potential environments (0–16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs.

Monitoring genetic gain is required in crop improvement programs in order to assess the effectiveness of breeding initiatives. The periodic measurement of genetic gain will quantify the efficiency of new technologies incorporated into the program. Here, a total of 24 cultivars (20 released from Zimbabwe’s National Breeding program (ZNBP) plus 4 released by the largest and oldest private seed company in Zimbabwe, Seed Co) over the period of 1900–2016, were evaluated across 10 locations in Zimbabwe. The testing locations represented agro-ecologies where maize is optimally grown and where maize production is under threat from climate change-induced abiotic stresses, particularly drought and heat stress, in Zimbabwe. The 24 cultivars were laid out across all the locations using the alpha (0.1) lattice design replicated two times with six incomplete blocks nested in each of the replicates. The genetic gains were estimated at 61 kg ha−1 yr−1, 25 kg ha−1 yr−1, 6 kg ha−1 yr−1, and 2 kg ha−1 yr−1 under optimal, random drought stress, heat stress, and managed drought stress conditions, respectively. The results were comparable with those from other studies where newly released cultivars yielded more than old cultivars. Overall, the results demonstrated that over a century, the ZNBP has been making significant progress in yield increments in its maize genotypes.

AbstractGenetic variation in cotton is crucial when traits are heritable and elucidation of the underlying genetic components of these helps in selecting elite genotypes. A research was done to determine broad-sense heritability of traits through variance components in different cotton genotypes. The trials were laid out in randomized complete design with three replications. Ten cotton genotypes were used in the study. The results revealed highly significant differences among genotypes on all the characteristics. The experimental lines 917–05-7 had the highest yield (1919 kg/ha), the biggest bolls (6.33 g), produced more lint (853.9 kg/ha), and had taller plants (123.9 cm). Significant genotype by environmental interactions were detected which caused low heritability values, low error variance, and low genotype by environment variances, which allowed easier selection of genotypes. Further partitioning of the genotype by environment effects revealed the most stable and highly performing genotypes and these were 907–05-9 and TN96-05-9 which were concluded to be the best performing cotton lines.

Breeding for heat stress tolerance became a priority in sub-Saharan Africa (SSA), as projections are showing an increase in frequency, duration, and severity. In this study, 14 heat stress tolerant-donor lines (HSTDLs) sourced from CIMMYT-India (males) were crossed with 15 locally adapted elite lines (females) developed within the CIMMYT-Zimbabwe maize-breeding program using the North Carolina Design II mating scheme. The resultant 175 single crosses were evaluated alongside five commercial hybrids and adjacent to the trial of parental lines used in the crosses across two locations representing heat stress and optimal environments in Zimbabwe. The design II analysis showed significant (p < 0.01) general combining ability (GCA) effects for exotic heat donor lines and specific combining ability (SCA) effects on grain yield under heat stress, optimal conditions, and across locations; demonstrating additive and non-additive genetic inheritance of grain yield. High Baker’s ratios observed in this study indicate predominance of additive over non-additive gene effects. Three exotic HSTDLs, namely CAL14138, CAL152, and CAL1440, exhibited significant (p < 0.001) and positive GCA effects under heat stress conditions. The results imply that these exotic lines could serve as valuable genetic resources for introgression of heat tolerant alleles into local maize populations for accelerated yield genetic gains. Single crosses, DJ265-15 × VL1018816 and DJ267-9 × CAL1440, exhibited positive and significant (p < 0.01) and (p < 0.05) SCA effects for grain yield under heat stress conditions, respectively. These crosses can be used for further breeding and can contribute to grain yield performance under heat stress conditions. The exotic HSTDLs, CAL14138, CAL152, and VL109126 showed superior per se performance under heat, optimal conditions, and across environments. Overall data demonstrate the potential of exotic HSTDLs for improving the adaptation of maize to heat stress in sub-tropical breeding programs.

A robust early warning system can alert to the presence of food crises and related drivers, informing decision makers on food security. To date, decision-makers in Zimbabwe still rely on agriculture extension personnel to generate information on wheat production and monitor the crop. Such traditional methods are subjective, costly and their accuracy depends on the experience of the assessor. This study investigates Sentinel-2 NDVI and time series utility as a wheat-monitoring tool over the wheat-growing areas of Zimbabwe's Bindura, Shamva, and Guruve districts. NDVI was used to classify and map the wheat fields. The classification model's evaluation was done by creating 100 reference pixels across the classified map and constructing a confusion matrix with a resultant kappa coefficient of 0.89. A sensitivity test, receiver operating characteristic (ROC) and area under the curve (AUC) were used to measure the model's efficiency. Fifty GPS points randomly collected from wheat fields in the selected districts were used to identify and compute the area of the fields. The correlation between the area declared by farmers and the calculated area was positive, with an R2 value of 0.98 and a Root Mean Square Error (RMSE) of 2.23 hectares. The study concluded that NDVI is a good index for estimating the area under wheat. In this regard, NDVI can be used for early warning and early action, especially in monitoring programs like ‘Command Agriculture’ in Zimbabwe. In current and future studies, the use of high-resolution images from remote sensing is essential. Furthermore, ground truthing is always important to validate results from remote sensing at any spatial scale.

Fall armyworm [Spodoptera frugiperda (J./E. Smith); FAW] is negatively impacting sustainable maize production, particularly in smallholder farming systems in sub-Saharan Africa. Two sets of germplasm (commercial cultivars and experimental hybrids, and local and exotic inbred lines) were evaluated under managed and natural FAW infestation to identify FAW tolerant material with superior grain yield performance. Significant genotypic effects on foliar FAW damage, ear FAW damage, and grain yield were observed. Commercial cultivars were significantly more affected by FAW infestation than experimental hybrids, as evidenced by high foliar and ear damage scores, yet they out-yielded experimental genotypes. The introduced FAW donor lines (CML338, CML67, CML121, and CML334) showed better tolerance to FAW, individually and in hybrid combinations. Local inbred lines, SV1P, CML491, and CML 539, also showed FAW tolerance. Hybrids and open pollinated varieties were more vulnerable to FAW damage at early growth stages, but they grew out of it through the mid to late whorl stages. Inbred lines showed increasing damage as they grew to maturity. Husk cover, ear rot, anthesis date, and plant height were highly correlated with FAW tolerance. The identified local and exotic lines with FAW tolerance will contribute to FAW resistance breeding in southern Africa.

The production of agricultural commodities faces increased risk of pests, diseases and other stresses due to climate change and variability. This study assesses the potential distribution of agricultural pests under projected climatic scenarios using evidence from the African coffee white stem borer (CWB), Monochamus leuconotus (Pascoe) (Coleoptera: Cerambycidae), an important pest of coffee in Zimbabwe. A species distribution modeling approach utilising Boosted Regression Trees (BRT) and Generalized Linear Models (GLM) was applied on current and projected climate data obtained from the WorldClim database and occurrence data (presence and absence) collected through on-farm biological surveys in Chipinge, Chimanimani, Mutare and Mutasa districts in Zimbabwe. Results from both the BRT and GLM indicate that precipitation-related variables are more important in determining species range for the CWB than temperature related variables. The CWB has extensive potential habitats in all coffee areas with Mutasa district having the largest model average area suitable for CWB under current and projected climatic conditions. Habitat ranges for CWB will increase under future climate scenarios for Chipinge, Chimanimani and Mutare districts while it will decrease in Mutasa district. The highest percentage change in area suitable for the CWB was for Chimanimani district with a model average of 49.1% (3 906 ha) increase in CWB range by 2080. The BRT and GLM predictions gave similar predicted ranges for Chipinge, Chimanimani and Mutasa districts compared to the high variation in current and projected habitat area for CWB in Mutare district. The study concludes that suitable area for CWB will increase significantly in Zimbabwe due to climate change and there is need to develop adaptation mechanisms.