Institutional and technological innovations for sustained change in smallholder irrigation schemes in southern and Eastern Africa

Water management systems must become more adaptable to alleviate projected shortfalls. Integrated socio-institutional and technological interventions are required to generate sustained change in irrigation water management and the profitability for smallholders and their schemes. We illustrate this by conducting an ex-post analysis of the ‘Transforming Irrigation in Southern Africa’ (TISA) project, which was implemented in two phases from 2013 to 17 and 2017–2023. The project introduced institutional and technological innovations to smallholder irrigation schemes in Tanzania, Mozambique and Zimbabwe: Agricultural Innovation Platforms as a participatory approach to engage farmers and stakeholders; and soil moisture monitoring tools to support farmer learning. We hypothesised that these innovations, despite differing socioeconomic and biophysical conditions in the three countries, would work synergistically to improve farmers’ adaptive capacity and generate sustained change. In this paper, we test our hypotheses through a synthesis of peer-reviewed TISA literature, focussing on four smallholder irrigation schemes and five factors identified in the literature as critical for increasing farmers’ adaptive capacity. Drawing predominantly on household surveys administered at the beginning, middle and end of the TISA project, we analyse a set of relevant indicators linked to the five factors. In addition to many changes, we found changes in irrigation management, including a reduction in total water use to less than half pre-TISA levels. Further, the changes were sustained when the schemes transitioned from an intensive research-for-development phase into a more operational phase. This research also shows that when governments listen to farming communities and revise institutional arrangements, such as water scheduling and scheme constitutions, this fosters more sustainable irrigated agriculture. We conclude that when initiating development projects for sustained change within smallholder irrigation schemes policy makers and donors must commit sufficient project time and funding for both a development phase and a transition to an operational phase. Programs must take a participatory approach and support multiple interventions including both socio-institutional and technological interventions

Developing pangenomes for large and complex plant genomes and their representation formats

Background The development of pangenomes has revolutionized genomic studies by capturing the complete genetic diversity within a species. Pangenome assembly integrates data from multiple individuals to construct a comprehensive genomic landscape, revealing both core and accessory genomic elements. This approach enables the identification of novel genes, structural variations, and gene presence-absence variations, providing insights into species evolution, adaptation, and trait variation. Representing pangenomes requires innovative visualization formats that effectively convey the complex genomic structures and variations. Aim This review delves into contemporary methodologies and recent advancements in constructing pangenomes, particularly in plant genomes. It examines the structure of pangenome representation, including format comparison, conversion, visualization techniques, and their implications for enhancing crop improvement strategies. Key scientific concepts of review Earlier comparative studies have illuminated novel gene sequences, copy number variations, and presence-absence variations across diverse crop species. The concept of a pan-genome, which captures multiple genetic variations from a broad spectrum of genotypes, offers a holistic perspective of a species’ genetic makeup. However, constructing a pan-genome for plants with larger genomes poses challenges, including managing vast genome sequence data and comprehending the genetic variations within the germplasm. To address these challenges, researchers have explored cost-effective alternatives to encapsulate species diversity in a single assembly known as a pangenome. This involves reducing the volume of genome sequences while focusing on genetic variations. With the growing prominence of the pan-genome concept in plant genomics, several software tools have emerged to facilitate pangenome construction. This review sheds light on developing and utilizing software tools tailored for constructing pan-genomes in plants. It also discusses representation formats suitable for downstream analyses, offering valuable insights into the genetic landscape and evolutionary dynamics of plant species. In summary, this review underscores the significance of pan-genome construction and representation formats in resolving the genetic architecture of plants, particularly those with complex genomes. It provides a comprehensive overview of recent advancements, aiding in exploring and understanding plant genetic diversity

Data-driven strategies to improve nitrogen use efficiency of rice farming in South Asia

Increasing nitrogen use efficiency (NUE) in agricultural production mitigates climate change, limits water pollution and reduces fertilizer subsidy costs. Nevertheless, strategies for increasing NUE without jeopardizing food security are uncertain in globally important cropping systems. Here we analyse a novel dataset of more than 31,000 farmer fields spanning the Terai of Nepal, Bangladesh’s floodplains and four major rice-producing regions of India. Results indicate that 55% of rice farmers overuse nitrogen fertilizer, and hence the region could save 18 kg of nitrogen per hectare without compromising rice yield. Disincentivizing this excess nitrogen application presents the most impactful pathway for increasing NUE. Addressing yield constraints unrelated to crop nutrition can also improve NUE, most promisingly through earlier transplanting and improving water management, and this secondary pathway was overlooked in the IPCC’s 2022 report on climate change mitigation. Combining nitrogen input reduction with changes to agronomic management could increase rice production in South Asia by 8% while reducing environmental pollution from nitrogen fertilizer, measured as nitrogen surplus, by 36%. Even so, opportunities to improve NUE vary within South Asia, which necessitates sub-regional strategies for sustainable nitrogen management

How beneficial are seasonal climate forecasts for climate risk management? An appraisal for crop production in Tanzania

Understanding growing period conditions is crucial for effective climate risk management strategies. Seasonal climate forecasts (SCF) are key in predicting these conditions and guiding risk management in agriculture. However, low SCF adoption rates among smallholder farmers are due to factors like uncertainty and lack of understanding. In this study, we evaluated the benefits of SCF in predicting growing season conditions, and crop performance, and developing climate risk management strategies in Kongwa district, Tanzania. We used sea surface temperature anomalies (SSTa) from the Indian and Pacific Ocean regions to predict seasonal rainfall onset dates using the k-nearest neighbor model. Contrary to traditional approaches, the study established the use of rainfall onset dates as the criterion for predicting and describing growing period conditions. We then evaluated forecast skills and the profitability of using SCF in crop management with the Agricultural Production System sIMulator (APSIM) coupled with a simple bio-economic model. Our findings show that SSTa significantly influences rainfall variability and accurately predicts rainfall onset dates. Onset dates proved more effective than traditional methods in depicting key growing period characteristics, including rainfall variability and distribution. Including SCF in climate risk management proved beneficial for maize and sorghum production both agronomically and economically. Not using SCF posed a higher risk to crop production, with an 80% probability of yield losses, especially in late-onset seasons. We conclude that while SCF has potential benefits, improvements are needed in its generation and dissemination. Enhancing the network of extension agents could facilitate better understanding and adoption by smallholder farmers

Critical reflections on transforming smallholder irrigation systems from dysfunctional to functional climate smart agricultural systems

Smallholder irrigation schemes are complex socio-ecological systems and critical components of agri-food systems. However, they are often driven by political objectives, including the production of staple food for food security and sovereignty, and therefore contrary to individual farmers’ aspirations of developing profitable farming enterprises that can adequately support scheme maintenance. This has resulted in dysfunctional schemes with rehabilitation efforts focused on infrastructure refurbishment, which neglect other critical aspects required for successful functioning such as strong market linkages and improved social dynamics. The poor performance of smallholder schemes represents a failure to enhance the livelihoods and food security of households and the development of local economies (Pittock et al., Citation2020). This failure creates an imperative to transform schemes using multiple interventions as leverage across the system to improve farmers’ adaptive capacity and enable schemes to become climate smart agricultural systems. This imperative is made more important because of the significant investment being made by governments and donors in irrigated agriculture

Links between protein-source diversity, household behavior, and protein consumption inadequacy in the Indian rural semi-arid tropics

Our study analyzes the determinants, sources, and levels of protein consumption among 785 households across nine districts in six Indian states in the semi-arid tropics. We found that 80% of these households consumed less protein than recommended and relied on cereals for 60–75% of their protein intake. Notably, even when protein-rich foods are accessible to households, they still consume them insufficiently. We found that their protein intake deficiency is driven by a lack of diversity of protein sources (in particular, legumes, millets, and livestock), as well as by a dearth of women's education and role in household decision-making and low incomes and assets. We advocate for initiatives to raise nutrition awareness, empower women, and adopt a nutrition-centric farming approach

Lower vicine content reduces the reproductive yield performance in faba bean (Vicia faba L.)

Faba bean is a nutritionally and medicinally rich popular legume crop. However, vicine-convicine remain as potential threats for “favism” in human beings. In this study, 189 diverse faba bean accessions have been evaluated for yield component traits and vicine content in seeds followed by a correlation study. Combined genetic variability analysis shows that traits like days to pod initiation (DPI), pod length (PL), test weight (TW) and grain yield have minimally been influenced by the environment. PCA revealed that TW, PL and PW were the primary indicators for deciding yield performance. LC–MS/MS confirms that vicine concentration varied in between 3.489 and 10.025 g/kg and a significant positive correlation (0.40***) was observed between vicine conc. and grain yield of faba bean. Thus, present study demonstrated that the faba bean genotypes containing lower vicine were mostly poor yielding, which might be regulated by vicine in faba bean. Therefore, complete elimination of vicine or development of near-zero vicine faba bean could drastically reduce the yield potential of the crop, hence one has to be very cautious and follow efficient selection strategies while optimizing lower concentration of vicine for development of low vicine varieties. This study shows that faba bean genotypes containing 4.0–5.5 g/kg vicine were fairly productive and also have considerably lower vicine

Dryland cropping in different Land uses of Senegal using Sentinel-2 and hybrid ML method

In rainfed and dryland agricultural areas with smallholder farms (less than 2 ha), crop diversity is high due to farmers' decisions and local climatic conditions, leading to a complex spatial–temporal distribution of crops. Monitoring and mapping crops is crucial for food security and implementing agricultural support programs. This study aims to map crop types across Senegal using Sentinel-2 satellite imagery and the limited ground reference data available, which has been increasing recently. The study compares conventional supervised classification algorithms to unsupervised classification algorithms using high-resolution satellite imagery. Crop type classification for 2020 in Senegal employed supervised machine learning algorithms, including Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) on the Google Earth Engine (GEE) cloud platform, and the unsupervised Iso-clustering classification algorithm with Spectral Matching Techniques (SMTs). Due to limited ground data, supervised classifiers achieved 45-55% accuracy, whereas the unsupervised semi-automatic approach achieved over 75% accuracy. The study indicates that supervised classifiers' performance depends on ground data quantity, while SMT shows good performance even with limited ground data. This SMT approach is valuable for classifying crop types in dryland areas with smallholder farms and diverse cropping patterns

Genetic analysis of purple pigmentation in rice seed and vegetative parts — implications on developing high-yielding purple rice (Oryza sativa L.)

Pigmentation in rice grains is an important quality parameter. Purple-coloured rice (Oryza sativa L.) indicates the presence of high anthocyanin with benefits of antioxidant properties. However, the genetic mechanism of grain colour is not fully understood. Therefore, the study focused on understanding pigmentation in grain pericarp and vegetative parts, and its relationship with blast resistance and enhanced grain yield. Three local cultivars from the northeastern region (NER) of India — Chakhao Poireiton (purple), Mang Meikri (light brown), and Kala Joha (white) — along with high-yielding varieties (HYVs) Shasharang (light brown) and Sahbhagi dhan (white) were used to develop biparental populations. The findings suggested that pigmentation in vegetative tissue was governed by the inter-allelic interaction of several genes. Haplotype analysis revealed that Kala3 complemented Kala4 in enhancing purple pigmentation and that Kala4 is not the only gene responsible for purple colour as evident by the presence of a desired allele for markers RID3 and RID4 (Kala4 locus) in Chakhao Poireiton and Kala Joha irrespective of their pericarp colour, implying the involvement of some other additional, unidentified genes/loci. RID3 and RID4 together with RM15191 (Kala3 locus) could be employed as a reliable marker set for marker-assisted selection (MAS). Pericarp colour was strongly correlated with colour in different vegetative parts, but showed a negative correlation with grain yield. Pb1, reported to be associated with panicle blast resistance, contributed to leaf blast resistance. Transgressive segregants for improved pigmentation and high yield were identified. The selection of lines exhibiting coloured pericarp, high anthocyanin content, aroma, blast resistance, and increased yield compared to their respective HYV parents will be valuable resources in the rice breeding programme

Milestones in Biology, Genetics, and Breeding of Pearl Millet

Pearl millet is a fascinating species for conducting basic research in biology and genetics; and for applied research in breeding. With a small number of large somatic chromosomes, pearl millet lends itself to investigation in classical and molecular cytogenetics. Its short life cycle, protogynous flowers and ability to set a large number of seeds per panicle make pearl millet highly suitable for studying flow of genes between cultivated annual species and related wild species. Centre of origin, domestication, primary and secondary gene pools of pearl millet helped in selection of suitable geographical area for collecting unique and diverse germplasm resources. The outcrossing nature of pearl millet provided the basis of exploitation of heterosis at commercial scale. Another important discovery related to pollination of pearl millet was role of pollen in reducing the infection of ovary by pathogens of ergot and smut. Knowledge of photoperiod response helped in extending the crop cultivation in new seasons and geographical regions; in controlling flowering in order to facilitate hybridization; and in selecting suitable sites for offseason nurseries. Outcrossing rate of above 85%, ease of inbred development, discovery of cytoplasmic male sterility and fertility restorer genes, lack of any negative association of cytoplasmic male sterility with growth and development, diseases and insect-pests, expression of positive and high magnitude of heterosis in productivity of hybrids and economic seed production provided a perfect platform for commercial exploitation of heterosis in pearl millet for the benefit of farming community. The genome of a reference genotype Tift 23D2B1-P1-P5 has been reported to contain an estimated 38,579 genes. Thus, a good understanding of biology and genetics of pearl millet has helped tremendously in breeding for higher productivity and stability