Lentil is a staple in many diets around the world and growing in popularity as a quick‐cooking, nutritious, plant‐based source of protein in the human diet. Lentil varieties are usually grown close to where they were bred. Future climate change scenarios will result in increased temperatures and shifts in lentil crop production areas, necessitating expanded breeding efforts. We show how we can use a daylength and temperature model to identify varieties most likely to succeed in these new environments, expand genetic diversity, and give plant breeders additional knowledge and tools to help mitigate these changes for lentil producers.

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Wheat blast is an emerging threat to wheat production, due to its recent migration to South Asia and Sub-Saharan Africa. Because genomic selection (GS) has emerged as a promising breeding strategy, the key objective of this study was to evaluate it for wheat blast phenotyped at precision phenotyping platforms in Quirusillas (Bolivia), Okinawa (Bolivia) and Jashore (Bangladesh) using three panels: (i) a diversity panel comprising 172 diverse spring wheat genotypes, (ii) a breeding panel comprising 248 elite breeding lines, and (iii) a full-sibs panel comprising 298 full-sibs. We evaluated two genomic prediction models (the genomic best linear unbiased prediction or GBLUP model and the Bayes B model) and compared the genomic prediction accuracies with accuracies from a fixed effects model (with selected blast-associated markers as fixed effects), a GBLUP + fixed effects model and a pedigree relationships-based model (ABLUP). On average, across all the panels and environments analyzed, the GBLUP + fixed effects model (0.63 ± 0.13) and the fixed effects model (0.62 ± 0.13) gave the highest prediction accuracies, followed by the Bayes B (0.59 ± 0.11), GBLUP (0.55 ± 0.1), and ABLUP (0.48 ± 0.06) models. The high prediction accuracies from the fixed effects model resulted from the markers tagging the 2NS translocation that had a large effect on blast in all the panels. This implies that in environments where the 2NS translocation-based blast resistance is effective, genotyping one to few markers tagging the translocation is sufficient to predict the blast response and genome-wide markers may not be needed. We also observed that marker-assisted selection (MAS) based on a few blast-associated markers outperformed GS as it selected the highest mean percentage (88.5%) of lines also selected by phenotypic selection and discarded the highest mean percentage of lines (91.8%) also discarded by phenotypic selection, across all panels. In conclusion, while this study demonstrates that MAS might be a powerful strategy to select for the 2NS translocation-based blast resistance, we emphasize that further efforts to use genomic tools to identify non-2NS translocation-based blast resistance are critical.

In severely deficit soil, lentil (Lens culinaris Medic) crop requires micronutrients for increased production. Micronutrient management is, therefore, very important for lentil productivity but mostly ignored. This study was carried out from 2014-2015 to 2016-2017 to understand the effects of zinc (Zn), boron (B) and molybdenum (Mo) on lentil productivity, nodulation and nutrient uptake and how these elements improve soil micronutrient fertility. The experiment was laid out in randomized complete block design and the treatments were replicated thrice. Different combinations of Zn, Mo and B were contrasted with no application of micronutrients. The treatments were Zn alone (Zn), B alone (B), Mo alone (Mo), Zn combined with B (ZnB), Zn with Mo (ZnMo), B with Mo (BMo) and Zn combined with B and Mo (ZnBMo). Doses of Zn, B and Mo were 3, 2 and 1 kg hectare-1, respectively. In this trial, the highest average seed yield (1807 kg ha-1) and yield increment (44%) was obtained in ZnBMo combined application with macronutrients. Single, dual and combined application of Zn, B and Mo had significant effects on yield parameters and yield of lentil (p<0.05). The highest nutrient uptake, maximum nodulation (63.5 plant-1) and the highest protein content (26.6 %) in seed were recorded from the treatment receiving all three micronutrients. The increased lentil yield might be associated with increased nodulation and nutrient uptake by the crop under micronutrient applied treatments. The results suggest that combination of Zn, B and Mo could be applied for increased lentil production in micronutrient deficit soils.

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An experiment was conducted for two consecutive years (2014-15 and 2015-16) at Regional Pulses Research Station, Madaripur and Regional Agricultural Research Station, Jashore, Bangladesh during Rabi (winter) season to evaluate the effect of Zinc (Zn) and Boron (B) on productivity, nodulation, nutrient uptake and quality of fieldpea (Pisum sativum L.) and how these elements can help to manage soil fertility. There were sixteen treatment combinations comprising four levels of Zn (0, 1.0, 2.0 and 3.0 kg ha-1) and four levels of Boron (0, 1.0, 1.5 and 2.0 kg ha-1) along with a blanket dose of fertilizers of N, P, K and S at 12, 22, 30 and 10 kg ha-1 , respectively used in all combination. The experiment was laid out in a split-plot design with three replications. Results showed that the treatment combination of Zn3.0B2.0 produced significantly higher seed yield followed by treatment combination of Zn3.0B1.5. The lowest seed yield was found in control (Zn0B0) combination. Treatment combination of Zn at 3 kg ha-1 and B at 2 kg ha-1 resulted in higher yield increment of 76.3% at Madaripur and 64.3% at Jashore over the control treatment (Zn0B0). Root nodulation and seed protein content was found highest in Zn3.0B2.0 treatment at both the locations. Zinc and Boron uptake by the fieldpea was also significantly affected by the added of Zn and B fertilizer. The combine application of Zn and B was superior to single application. The treatment combination of Zn3.0B2.0 followed by Zn3.0B1.5 showed positive results in improving soil organic matter, N, P, S, Zn and B content in soil for both locations. Hence, the results recommended that combine application of Zn and B either at of 3 and 2 kg ha-1 or at of 3 and 1.5 kg ha-1 , respectively along with blanket fertilizers of N12 P22 K30 S10 kg ha-1 can support for higher yields of fieldpea and help to sustain fertility of calcareous soils.

Lentil (Lens culinaris Medik.) is cultivated under a wide range of environmental conditions, which led to diverse phenological adaptations and resulted in a decrease in genetic variability within breeding programs due to reluctance in using genotypes from other environments. We phenotyped 324 genotypes across nine locations over three years to assess their phenological response to the environment of major lentil production regions and to predict days from sowing to flowering (DTF) using a photothermal model. DTF was highly influenced by the environment and is sufficient to explain adaptation. We were able to predict DTF reliably in most environments using a simple photothermal model, however, in certain site-years, results suggest there may be additional environmental factors at play. Hierarchical clustering of principal components revealed the presence of eight groups based on the responses of DTF to contrasting environments. These groups are associated with the coefficients of the photothermal model and revealed differences in temperature and photoperiod sensitivity. Expanding genetic diversity is critical to the success of a breeding program; understanding adaptation will facilitate the use of exotic germplasm. Future climate change scenarios will result in increase temperature and/or shifts in production areas, we can use the photothermal model to identify genotypes most likely to succeed in these new environments.

Potassium is the key element for mungbean (Vigna radiata L.) productivity. The study was carried out to understand the effects of potassium (K) on mungbean productivity, quality, nutrient content and nutrient uptake and how this element can help to manage soil fertility.Therefore, an experiment was conducted during two consecutive years 2016 and 2017. The experiment was laid out in randomized complete block design considering six treatments with thrice replicates. The treatments were T1 = Control, T2 = 30 kg K ha-1, T3= 40 kg K ha-1, T4= 50 kg K ha-1, T5= 60 kg K ha-1 and T6= 70 kg K ha-1 along with the blanket dose of N15P20S10Zn2B1.5 kg ha-1. Results revealed that application of different levels of potassium showed significant effects on the plant height, number of pods per plant, number of seeds per pod and thousand seed weight which were influenced to obtain higher yield of mungbean. The highest average seed yield (1476 kg ha-1) and highest yield increment (39.5%) of mungbean were produced from the treatment T5. Most of the cases the highest nutrient (N, P, K, S, Zn and B) content was obtained in T5 treatment.The highest K uptake by mungbean, maximum nodulation, the highest protein content in seed and maximum apparent K recovery efficiency (54.8%) were, however, recorded from the treatment receiving of 60kg K ha-1. It was concluded that proper use of K with other nutrients facilitated to improve the productivity and quality of mungbean and also K played a significant role in maintaining soil fertility.